Edge IoT Industrial Immersive Technologies and Spatial Computing Continuum

AIOTI. All igh s ese ed.
Edge IoT Indus ial Imme si e
Technologies and Spa ial
Compu ing Con inuum
Release 1
AIOTI WG Resea ch and Inno a ion
30 Ap il 2024
© AIOTI. All igh s ese ed.
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1. Execu i e Summa y
This posi ion pape on edge In e ne o Things (IoT) indus ial imme si e echnologies c ea ed by
he Alliance o IoT and Edge Compu ing Inno a ion (AIOTI) aims o p o ide he ision o he
con e gence o edge IoT, a i icial in elligence (AI), digi al wins (DT), imme si e iple s (IMT),
in elligen mesh connec i i y, IoT o senses (IoTS), so wa e-de ined au oma ion (SDA) and spa ial
compu ing echnologies o c ea e an indus ial eal-digi al- i ual con inuum. Such con inuum
is made o imme si e en i onmen s, which a e compu e -gene a ed i ual wo lds whe e use s
can sense as i hey we e physically embodied in ha gene a ed pe cep ion con ex .
The con e gence o hese echnologies in o indus ial imme si e solu ions ad ances he
in eg a ion and applica ion o edge in elligen imme si e echnologies combining augmen ed
eali y (AR), i ual eali y (VR), mixed eali y (MR), and ex ended eali y (XR) wi h concep s like
me a e ses, omni e se, mul i e ses, nex gene a ion spa ial web, Web 4.0 as pa o u u e i ual
wo lds.
Such con e gence o indus ial imme si e echnologies a he edge can imp o e e iciency,
educe down ime, enhance sa e y, and be e decision-making in indus ial se ings. Howe e ,
o be e ec i ely deployed, i bo h equi es a s ong in e disciplina y collabo a ion and p esen s
challenges like obus ha dwa e (HW) design and cos -e ec i e a ailabili y, da a secu i y and
p i acy p ese ing me hods, and e ec i e indus ial wo k low in eg a ion. As echnology
ad ances, he adop ion o such con e gence in indus y is expec ed o g ow, o e ing
ans o ma i e bene i s ac oss a ious sec o s and e ical ma ke s, including indus ial
manu ac u ing, p oduc ope a ions, design and main enance, aining and collabo a ion, da a
isualisa ion, mobili y and logis ic, ene gy, au omo i e, ae ospace, and heal hca e.
The EU ecognises Web 4.0 as a e olu iona y echnological shi owa d an imme si e,
seamlessly in e connec ed wo ld, iewing i ual wo lds as a c i ical ansi ion componen
[12][13][11]. Swi echnological p og ess in edge IoT, AI, imme si e echnologies, and enhanced
connec i i y in as uc u e ha e enabled he easibili y o i ual wo lds. These i ual
en i onmen s a e key o he EU Digi al Decade a ge s [16], in luencing how indi iduals li e,
wo k, c ea e, and sha e con en and how businesses unc ion, inno a e, p oduce, and engage
wi h consume s.
Edge IoT indus ial imme si e echnologies c ea e o imi a e he physical wo ld h ough digi al
simula ion (Phygi al [1]) and i ual sensa ions gi ing he use a unique expe ience o he h ee-
dimensional (3D) spa ial compu ing en i onmen . Phygi al is a mix o "physical" and "digi al,"
combining he physical and digi al wo lds o comple e one mixed expe ience.
Edge spa ial compu ing (ESC) is a no el compu ing pa adigm ocusing on unde s anding and
in e ac ing wi h he physical wo ld in a 3D space close o he sou ce. Spa ial compu ing
encompasses he p ocesses and ools o cap u ing, p ocessing, and in e ac ing wi h 3D da a.
These echnologies enable human-compu e in e ac ion ha simula es in e ac ions in eal-wo ld
physical en i onmen s a he han being limi ed o sc eens and machines.
ESC enhances he capabili ies o au onomous edge IoT de ices, obo ics, and machines o
in e ac mo e na u ally wi h humans. I in eg a es wi h VR, AR, MR, XR, na u al use in e ace,
con ex ual, a ec i e, and ubiqui ous compu ing in a 3D space, u ilising compu e , and
machine/compu e ision o comp ehend eal-wo ld scena ios.
The opics p esen ed in his AIOTI posi ion pape a e aligned wi h he AIOTI S a egic Resea ch
and Inno a ion Agenda (SRIA) and illus a e he e olu ion o hese opics in o con e gence
ing edien s o edge indus ial imme si e echnologies.
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Table o Con en
2.1 Vi ual eali y .................................................................................................................................................. 15
2.2 Augmen ed Reali y ....................................................................................................................................... 15
2.3 Mixed eali y .................................................................................................................................................. 17
2.4 Ex ended eali y ............................................................................................................................................. 18
2.5 Me a e se ...................................................................................................................................................... 20
2.6 Omni e se ...................................................................................................................................................... 25
2.7 Mul i e se ....................................................................................................................................................... 26
2.8 Spa ial Web 4.0 - In e ne o Humans and Machines E olu ion ................................................................ 27
3.1 In e ne o Things ............................................................................................................................................ 31
3.2 In e ne o Things Senses ............................................................................................................................... 33
3.3 In e ne o Things Digi al Twins E ol ing o Imme si e T iple s .................................................................. 35
3.4 Vi ual Replicas wi h Ac i e Fo ce Feedback ............................................................................................ 36
3.4 Edge Compu ing ........................................................................................................................................... 37
3.5 Spa ial Compu ing ........................................................................................................................................ 38
3.6 Edge A i icial In elligence ........................................................................................................................... 40
3.7 Spa ial Gene a i e Edge A i icial In elligence Technologies .................................................................. 41
3.8 Imme si e In elligen Mesh Connec i i y .................................................................................................... 43
3.8 In eg a ion o Sensing and Communica ions ............................................................................................. 48

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Lis o Figu es
Figu e 2-1 IoT - “In e ne ” and “Things” e olu ion. ......................................................................................................... 7
Figu e 2-2 Ga ne Hype Cycle o eme ging echnologies 2022. Sou ce: [32] .......................................................... 8
Figu e 2-3 Ga ne impac ada o 2024. Sou ce: [31]. ................................................................................................ 9
Figu e 2-4 Edge IoT indus ial imme si e echnologies. ............................................................................................... 11
Figu e 3-1 Edge IoT imme si e echnologies. ............................................................................................................... 14
Figu e 3-2 Illus a ion o he concep s o a ious imme si e echnologies – VR, AR, MR. Sou ce: [7] .................... 17
Figu e 3-3 XR applica ion landscape. Sou ce: Adap ed om F os & Sulli an ......................................................... 20
Figu e 3-4 Ve ses cha ac e is ics. Sou ce: Adap ed om [8] ..................................................................................... 21
Figu e 3-5 The concep o e ses in he con ex o imme si e echnologies. .......................................................... 22
Figu e 3-6 Me a e se in e disciplina i y. ........................................................................................................................ 23
Figu e 3-7 The indus ial me a e se. Sou ce: Adap ed om [37]. .............................................................................. 25
Figu e 3-8 In e ne and Web cha ac e is ics. ................................................................................................................ 27
Figu e 3-9 Web e olu ion. ............................................................................................................................................... 28
Figu e 4-1 Edge imme si e echnologies con e gence ac oss he alue chain. .................................................... 31
Figu e 4-2 Edge IoT key a ibu es cha ac e ised by 6As and 6Cs. ............................................................................ 32
Figu e 4-3 Edge imme si e mul i-senso y communica ions o p o iding in o ma ion and in elligence. ............. 34
Figu e 4-4 IIoT and XR a ic cha ac e is ics. Sou ce: Adap ed om Nokia. ............................................................ 43
Figu e 4-5 The e olu ion o high-capaci y op ical ib e anspo ne wo ks. Sou ce: [60]. ...................................... 45
Figu e 4-6 Senso y communica ions h oughpu and la ency equi emen s. Sou ce: [43]. .................................... 46
Figu e 4-7 Imp o ing suppo o he XR in 5G-Ad anced. Sou ce: Adap ed om [34]. ......................................... 47
Figu e 8-1 Edge imme si e echnologies ecosys em. Sou ce: Nokia. ...................................................................... 56
Figu e 8-2 IEEE P2874 D2 sys em design componen s. Sou ce: [55]. .......................................................................... 58
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Lis o Tables
Table 3-1 Typical exis ing VR, AR, and MR sys em speci ica ions and echnical equi emen s [21]. .................... 20
Table 4-1 Ac ua ion and modali ies wi hin a mul i-senso y communica ion o media ed social ouch [19]. ..... 35
Table 4-2 QoS equi emen s o mul i-modal s eams [1]. ........................................................................................... 44
Table 4-3 Requi emen s o wea ables, indus ial wi eless senso s, and ideo su eillance use cases [1]. ........... 45
Table I-1 S anda disa ion ac i i ies ela ed o imme si e echnologies ac oss a ious SDOs. ............................... 72
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Lis o Ac onyms
3C Connec ed Collabo a i e Compu ing
3D Th ee dimensional
AI A i icial In elligence
AIOTI Alliance o IoT and Edge Compu ing Inno a ion
AIOTI SRIA AIOTI S a egic Resea ch and Inno a ion Agenda
AoI A eas o In e es
API Applica ion P og amming In e ace
AR Augmen ed Reali y
BIM Building in o ma ion Modelling
CBDC Cen al Bank Digi al Cu ency
DAO Decen alised Au onomous O ganisa ion
dApp Decen alised app
DeFi Decen alised inance
DL Deep Lea ning
DLT Dis ibu ed Ledge Technologies
DoF Deg ees o F eedom
DT Digi al Twin
E2E End o End
ESC Edge Spa ial Compu ing
FoV Field o View
FPS F ames pe Second
FW Fi mwa e
HMD Head-Moun ed Display
HMI Human-Machine In e ace
HW Ha dwa e
IMT Imme si e T iple s
IoT In e ne o Things
IIoT Indus ial In e ne o Things
IoT DT IoT Digi al Twin
IoTS In e ne o Things Senses
IT In o ma ion Technology
ITM Imme si e T iple s
JCAS Join Communica ion and Sensing
LoRa Long Range Radio
LoRaWAN Long Range Wide A ea Ne wo k
MEC Mul i-access Edge Compu ing
ML Machine Lea ning
MR Mixed Reali y, Machine Reasoning
NFT Non-Fungible Token
NLP Na u al Language P ocessing
NUI Na u al Use In e ace
PCCR Pupil Cen e Co nea Re lec ion
QoE Quali y o Expe ience
QoS Quali y o Se ice
RAN Radio Access Ne wo ks
RF Radio F equency
SDK So wa e De elopmen Ki
SLAM Simul aneous Localiza ion And Mapping
SoS Sys ems o Sys ems
SRIA S a egic Resea ch and Inno a ion Agenda
SW So wa e
UI Use In e ace
VR Vi ual Reali y
VV&T Ve i ica ion, Valida ion and Tes ing
Wi-Fi Wi eless Fideli y
XAI Explainable AI
XR eX ended Reali y
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2. Vision and Objec i es
Fusion and con e gence o echnologies spa ks inno a ion, allowing o c oss-pollina ion o
ideas, he c ea ion o no el app oaches, and ans o ms indus ial landscape by enabling new
edge IoT de ices, sys ems, se ices, and business models. De eloping cu ing-edge IoT indus ial
imme si e echnologies and spa ial compu ing equi es a holis ic, in e disciplina y app oach as
a d i e o knowledge c ea ion, esea ch, and inno a ion. Collabo a ion be ween he disciplines
is hus a i al complemen o he g ow o he disciplines hemsel es.
The ision o indus ial imme si e echnologies using and con e ging se e al echnology
enable s is o c ea e a highly ad anced and in e connec ed indus ial landscape. This
landscape le e ages he con e gence o edge IoT, AI, gene a i e heu is ics, Web 4.0, DT, IMT,
IoTS, AR, VR, MR, XR, SDA and e se echnologies (me a e se, omni e se, mul i e se). These
concep s ep esen laye s o in e connec ed i ual spaces. The me a e se e e s o a single,
uni e sal i ual wo ld. The omni e se is a ne wo k o mul iple me a e ses, po en ially ope a ed
by di e en en i ies bu in e connec ed seamlessly, allowing use s o na iga e om one o
ano he wi hou lea ing he i ual en i onmen . The mul i e se ex ends his idea u he in o a
i ually in ini e numbe o di e se uni e ses wi hin b oade na a i es.
As a esul , hese echnological de elopmen s ha e he po en ial o e olu ionise indus ial
p ocesses, aining, and collabo a ion h ough edge IoT and spa ial echnologies. These
echnologies co e he Connec ed Collabo a i e Compu ing (3C) con inuum ha equi es
in elligen o ches a ion, o op imise secu i y and sus ainabili y aspec s.
The IoT concep en ails wo main componen s: In e ne and Things. These ep esen
echnologies ha a e e ol ing and ad ancing in hei own pa hs as illus a ed in Figu e 2-1.
Figu e 2-1 IoT - “In e ne ” and “Things” e olu ion.
The In e ne expands in o no el decen alised web pa adigms and 3D spa ial ep esen a ion,
including holog aphic ep esen a ions and imme si e echnologies. Things a e becoming
in elligen , mobile, and au onomous, based on sel -X ea u es such as sel -con igu a ion, sel -
awa eness, and sel -diagnos ic, using edge AI o p ocess in o ma ion om mul iple senso s and
con ol mul iple ac ua o s based on mul i-p o ocol in elligen connec i i y, hus enabling
de ices o adap o hei en i onmen s, op imise hei pe o mance, and an icipa e
main enance needs wi hou human in e en ion.
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3. De ini ions and Taxonomy
IoT and edge compu ing esea ch and inno a ion add ess IoT/edge con inuum dis ibu ed
a chi ec u es, in elligen connec i i y. End- o-end (E2E) secu i y, he e ogenous IoT edge mesh,
IoT DTs, AI, IoT swa m sys ems, IoTS, us wo hiness, e i ica ion, alida ion, and es ing (VV&T),
s anda disa ion, and he con e gence o all he abo e in o he In e ne o In elligen Things.
Imme si e echnology e e s o any echnology ha blu s he line be ween he physical and
digi al wo lds, c ea ing a sense o p esence and engagemen o he use . Imme si e
echnologies aim o anspo use s o i ual en i onmen s o enhance hei eal-wo ld
expe iences by o e laying digi al in o ma ion on o hei physical su oundings h ough eal- ime
in e ac ions in physical, digi al, i ual, cybe , and spa ial en i onmen s.
Imme si e echnologies ha e eme ged as a e olu iona y app oach o c ea ing digi al
expe iences ha eel eal o use s.
By inco po a ing a ious ools and sys ems, imme si e echnology encompasses eal- ime
in e ac ions in physical, digi al, i ual, cybe , and spa ial en i onmen s using a b oad spec um
o expe iences ha blu he bounda ies be ween he physical and digi al wo lds, p o iding
inno a i e ways o in e ac , explo e, and lea n.
IoT and edge compu ing enable inno a ion and b oad adop ion in imme si e echnologies and
applica ions by b inging he no el elemen s o con e ging echnologies o he edge and eal-
ime in e ac ion be ween he physical and i ual wo lds. An o e iew o edge imme si e
echnologies is illus a ed in Figu e 3-1.
Figu e 3-1 Edge IoT imme si e echnologies.
The IoT de ices, mobile compu ing uni s, and lee s o hese in e connec ed de ices a e
e ol ing, and he amoun o in o ma ion gene a ed and exchanged by hese de ices g ow
signi ican ly a he ne wo k edge.
Consequen ly, he cons ain s due o ex emely high la ency and ne wo k bandwid h usage will
limi he ans e o hese massi e olumes o da a o he cloud. Using AI p ocessing capabili ies
a he ne wo k edge can unleash he po en ial o da a gene a ed by senso s and de ices.

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2.1 Vi ual eali y
VR is a compu e -gene a ed simula ion o an en i onmen using 3D compu e modelling, which
imme ses use s in a wholly digi al en i onmen , o en using a head-moun ed display and hand
con olle s o simula e he physical p esence in he i ual wo ld.
The imme sion is achie ed h ough hand-held con olle s o glo es i ed wi h senso s, VR
headse s o head-moun ed displays (HMDs) ha co e he use 's ield o ision, deli e ing
con en ha esponds o he use 's mo emen s and ansla e hem in o ac ions o simula e he
physical p esence in he i ual wo ld, hus allowing use s o in e ac in hose wo lds.
VR in ol es componen s and cha ac e is ics like imme si e expe iences ha p o ide a sense o
imme sion in a compu e -gene a ed en i onmen dis inc om he physical en i onmen .
The imme sion in he i ual wo ld happens by making use o mul iple senses, including ision,
hea ing, and some imes ouch ( h ough hap ic eedback), o enhance he ealism o he i ual
en i onmen by using IoTS de ices. Ad anced VR sys ems may also include ol ac o y (smell)
and gus a o y ( as e) elemen s o deepen he imme si e expe ience u he .
The in eg a ion o 3D g aphics and en i onmen s in o i ual spaces is achie ed by making use
o 3D compu e modelling, one o he mos in e es ing ypes o g aphic design, and is designed
o be in e ac i e and esponsi e o he use 's ac ions. This equi es subs an ial compu ing powe
o main ain eal- ime ende ing and in e ac ion. An in e es ing o e ing in his domain is he
open-sou ce lib a y o easy 3D da a p ocessing, ML and isualisa ion and called Open3D [45].
S anda ds ela ed o VR (see Table I-1) p o ide guidelines on sys em design, use in e ac ion,
con en c ea ion, and heal h and sa e y conside a ions o ensu e a high-quali y use
expe ience, p omo ing in e ope abili y be ween di e en VR de ices and so wa e, and
add essing po en ial heal h impac s associa ed wi h p olonged VR use.
2.2 Augmen ed Reali y
IoT, edge compu ing and AR a e echnologies ha a e changing how we in e ac wi h he
wo ld. AR combines eal-wo ld iews wi h compu e -gene a ed elemen s o c ea e an
imme si e expe ience. IoT and edge compu ing b ing he in e ac ions wi h he physical wo ld,
da a collec ion, da a s o age and p ocessing close o he ne wo k's edge, making AR mo e
accessible, cos -e ec i e, and secu e.
AR blends digi al con en wi h he eal wo ld, allowing use s o see and in e ac wi h i ual
objec s o in o ma ion o e laid on o hei physical su oundings h ough edge IoT de ices
sc eens, headse s, and sma glasses.
AR can be de ined as an in e ac i e expe ience o a eal-wo ld en i onmen whe e he objec s
ha eside in he eal wo ld a e enhanced by compu e -gene a ed pe cep ual in o ma ion,
ac oss mul iple senso y modali ies, including isual, audi o y, hap ic, soma osenso y, and
ol ac o y. The echnical aspec s o AR in ol e in eg a ing digi al in o ma ion wi h he use 's
en i onmen in eal- ime. Unlike VR, which c ea es an a i icial en i onmen , AR uses he exis ing
en i onmen and o e lays new in o ma ion on op o i , c ea ing an ac ual “augmen a ion” o
he sensed eali y. AR can be expe ienced h ough a ious de ices, including sma phones,
able s, AR glasses, and HMD c ea ing Phygi al mixed expe iences.
F om a scien i ic and echnical s andpoin , AR sys ems a e designed o combine eal and i ual
wo lds, in e ac in eal- ime and align i ual and eal objec s.
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The key componen s o AR sys ems include senso s and came as o cap u e eal-wo ld inpu s,
p ocessing o in e p e he senso inpu , de ec ea u es o he eal wo ld, and de e mine he
loca ion and o ien a ion o a de ice wi hin i , p ojec ion sys ems o display i ual images, display
de ices o p esen he in eg a ed digi al in o ma ion o he use . This can include sc eens, op ical
p ojec ion sys ems, o ouchsc eens, enabling use s o see and in e ac wi h he augmen ed
i ual objec s.
S anda ds ela ed o AR (see Table I-1) aim o ha monize he echnical c i e ia, ensu e
in e ope abili y be ween di e en AR de ices and SW, and enhance he use expe ience by
se ing benchma ks o pe o mance, sa e y, and p i acy.
AR sys ems ypically consis o se e al key componen s such as a pe cep ion senso , e.g., a
came a ha cap u es he eal-wo ld en i onmen and eeds i in o he AR sys em, a p ocesso
o pe o m image p ocessing on he inpu o he came a o iden i y and ack ea u es in he
eal wo ld, a display ha p esen s he digi al con en and in o ma ion supe imposed on he eal-
wo ld iew (e.g., sma phone sc een, a HMD, a p ojec ed image), acking and alignmen o
align i ual con en wi h he eal-wo ld en i onmen (e.g., ma ke -based acking, ea u e-
based acking, o simul aneous localisa ion and mapping- simul aneous localiza ion and
mapping (SLAM)), in e ac ion ha allows use s o in e ac wi h i ual con en (e.g., ia ges u es,
oice commands, o a handheld con olle ), SW ha includes he p og amming ha makes he
AR expe ience implemen ed using a ious AR SW de elopmen ki s (SDKs).
Wi h edge compu ing, he p ocessing equi ed o AR applica ions can un on edge de ices
a he han elying on cloud compu ing and emo e se e s. This signi ican ly educes cloud-
based la ency o AR sys ems and da a ansmission cos s. As a esul , IoT and edge compu ing
make AR mo e accessible and imp o es he o e all use expe ience. AR applica ions ha un
a he edge a e also less suscep ible o he cybe h ea s aced by cloud-based AR applica ions
(which a e much mo e ulne able o hacking and da a he ). This is because edge compu ing
keeps da a local, making i a less suscep ible o a acks, as da a isn' equi ed o a el o
emo e cloud se e s and back. IoT and edge compu ing enables AR expe iences in eal- ime,
which posi i ely impac s li e spo s b oadcas ing, ansla ion, and p oduc isualisa ion.
AR and VR a e di e en echnologies wi h speci ic uses and applica ions. The di e ences
be ween AR and VR a e as ollows: AR enhances he eal wo ld by supe imposing compu e -
gene a ed elemen s, while VR c ea es an en i ely a i icial en i onmen ha eplaces he eal
wo ld.
AR is in e ac i e and allows use s o iew and in e ac wi h hei eal-wo ld su oundings, while
VR is designed o imme se use s in a wholly digi al en i onmen . AR sys ems ypically use a
came a o cap u e he eal wo ld and display digi al con en supe imposed on i . VR sys ems
usually use head-moun ed displays o ully imme se use s in digi al con en . The imme sion le el
o VR apps is g ea e han AR and has been p o en bene icial o aining pu poses. The key
di e ences be ween AR and VR lie in hei ela ionship o he eal and digi al wo lds. AR
enhances he eal wo ld wi h compu e -gene a ed elemen s, while VR comple ely eplaces i
wi h a digi al en i onmen .
Knowing he di e ence be ween AR and VR is impo an o unde s anding hei po en ial uses
and limi a ions and he di e en oles Edge compu ing plays o each echnology. I also helps
o be e unde s and he impac s o hese echnologies in di e en indus ial sec o s and ac oss
hese sec o s.
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2.3 Mixed eali y
MR e e s o blending physical and digi al wo lds o p oduce new en i onmen s and
isualisa ions whe e physical and digi al objec s coexis and in e ac in eal- ime. MR
encompasses a wide ange, om AR, whe e eal-wo ld en i onmen s a e augmen ed wi h
i ual objec s, o VR, whe e i ual en i onmen s inco po a e elemen s om he eal wo ld and
use s a e imme sed in a simula ed digi al en i onmen o a digi al eplica o eali y. This
con inuum highligh s he luidi y be ween he pu ely physical and i ual wo lds, wi h MR as an
in e media y s a e ha in eg a es bo h aspec s. The le el o augmen a ion can a y om a
simple in o ma ion display o he addi ion o i ual objec s and e en comple e augmen a ion
o he eal wo ld. MR includes all a ian s whe e i ual and eal en i onmen s a e mixed and
a ian s whe e eal objec s a e included in he i ual wo ld.
MR combines elemen s o VR and AR, allowing use s o coope a e wi h i ual objec s ancho ed
o he eal-wo ld and in e ac ing wi h i . MR in ol es wea ing a headse ha o e lays digi al
con en on o he use 's en i onmen while main aining awa eness o he physical wo ld. MR,
when in eg a ed wi h IoT, edge compu ing, and AI, can signi ican ly enhance imme si e
expe iences ac oss a ious domains, om indus ial applica ions o e e yday consume use. The
concep s o VR, AR, MR imme si e echnologies a e illus a ed in Figu e 3-2.
Technical and scien i ic aspec s o MR in ol e seamless in eg a ion by he seamless blend o
eal and i ual wo lds, equi ing sophis ica ed sensing, p ocessing, and display echnologies,
eal- ime in e ac ions wi h bo h eal and i ual elemen s occu in eal- ime, demanding high
compu a ional e iciency and esponsi e inpu /ou pu sys ems, spa ial egis a ion by aligning
i ual objec s wi h he eal wo ld o main ain he illusion o coexis ence, necessi a ing
ad anced compu e ision, senso usion, and acking echnologies.
Figu e 3-2 Illus a ion o he concep s o a ious imme si e echnologies – VR, AR, MR. Sou ce: [7]
To p opose a compa ison, di e en ly om MR, o iginal AR applica ions we e dependen on he
sensing sys ems and hei ex e nal e e ences (like ma ke s) o enable spa ial compu ing. These
solu ions we e e ec i e (e.g., AR pla o ms) bu could no in e ac wi h he en i onmen ou side
he ma ke excep when complex s uc u ed solu ions we e used. Senso - usion solu ions
nowadays o e come hose limi a ions, and he wo e ms a e o en swapped in a common
language.
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Key componen s and echnologies used in MR sys ems include ad anced displays, such as
HMDs o sma glasses, which can o e lay i ual con en on o he physical wo ld, en i onmen al
sensing using came as, dep h senso s, and o he echnologies o cap u e de ailed in o ma ion
abou he su ounding en i onmen , spa ial compu ing enabling de ices o unde s and and
in e ac wi h he physical space a ound hem, including objec ecogni ion and spa ial
mapping, hap ic eedback p o iding ac ile eedback o enhance he sense o physical
in e ac ion wi h i ual objec s.
S anda ds ela ed o MR (see Table I-1) aim o p o ide a amewo k o e minology, sys em
design, use expe ience, and in e ope abili y among MR de ices and applica ions o ensu e
compa ibili y, sa e y, and p i acy ac oss he di e se ecosys em o MR echnology and
applica ions.
In VR, use s a e imme sed in a simula ed digi al en i onmen o a digi al eplica o eali y. In AR
digi al in o ma ion is o e laid on images o eali y iewed h ough a de ice. The le el o
augmen a ion can a y om a simple in o ma ion display o he addi ion o i ual objec s and
e en comple e augmen a ion o he eal wo ld. Howe e , MR includes all a ian s whe e i ual
and eal en i onmen s a e mixed and a ian s whe e eal objec s a e included in he i ual
wo ld.
Edge de ices suppo MR and ha e new senso s ha enable he i ual a a a o main ain eye
con ac and eplica e he acial emo ions o ac ual people. Wi h u he ad ancemen in he
echnology, a a a s will be able o exp ess human emo ions be e and employ body language,
gi ing he imp ession o a eal dialogue in i ual en i onmen s.
2.4 Ex ended eali y
XR is an umb ella e m ha co e s imme si e echnologies anging om VR o MR, and AR. The
combina ion o in elligen wi eless and cellula connec i i y and XR echnologies enables new
mobile expe iences o consume s and indus ial use s and opens a b oad ange o business
oppo uni ies o se ice.
XR is a e m ha encompasses he en i e spec um o eal and i ual combined en i onmen s
and human-machine in e ac ions gene a ed by compu e echnology and wea ables. XR
echnology aims o blend he digi al and physical wo lds in a seamless and imme si e way,
le e aging he s eng hs o VR, AR, and MR o c ea e expe iences ha could ange om en i ely
syn he ic en i onmen s (VR) o eal-wo ld se ings augmen ed wi h digi al o e lays (AR) and
en i onmen s whe e physical and digi al objec s coexis and in e ac in eal- ime (MR).
The u u e echnological landscape is p o oundly eshaped by he con e gence o IoT, edge
compu ing, AI, and indus ial imme si e echnologies such as XR, all wi hin he amewo k o
eme ging In e ne Web 4.0 echnologies. This con e gence is expec ed o b ing abou a new
digi al in e ac ion and au oma ion e a ac oss a ious indus ies and aspec s o daily li e.
Key aspec s and objec i es o XR include imme si e expe iences ha could ei he augmen he
eal wo ld wi h digi al con en (AR), blend he eal and i ual wo lds (MR), o c ea e a ully
imme si e i ual en i onmen (VR), in e ac i i y ac oss he spec um o XR by in e ac ing wi h
digi al objec s o e laid on o he eal wo ld o na iga ing and manipula ing an en i ely i ual
space, mul i-senso y engagemen using mul iple senses, no jus sigh and sound bu po en ially
ouch ( h ough hap ic eedback) and o he senses
The aim o XR is o c ea e mo e imme si e and compelling expe iences, eal- ime p ocessing o
complex da a, including spa ial mapping, objec ecogni ion, and seamless in eg a ion o
i ual and eal elemen s and he use o wea able and non-wea able edge IoT de ices h ough
a a ie y o HMDs ( o VR and MR), sma glasses ( o AR), mobile de ices, and e en u u e
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echnologies ha may p o ide mo e unob usi e ways o blend digi al and physical
expe iences.
S anda ds and guidelines o XR (see Table I-1) a e ocused on ensu ing in e ope abili y be ween
de ices, de ining consis en use expe ience me ics, and add essing e hical conside a ions and
p i acy conce ns o acili a e he widesp ead adop ion o XR echnologies by p o iding a solid
amewo k o de elope s, manu ac u e s, and con en c ea o s o ollow.
XR s eaming enables da a-in ensi e AR and VR applica ions o be collec ed in eal- ime by
mobile de ices. This opens new ields o applica ion o imme si e echnologies in he IoT
en i onmen .
The elemen s speci ic o he imme si e echnologies ep esen ed by XR a e Field o View (FoV),
which de ines an obse able a ea o he ange o ision (e.g., 200m) an indi idual can see ia
an XR de ice such as HMD when he use is s a ic wi hin a gi en XR en i onmen ; Deg ees o
F eedom (6DoF), which desc ibes he posi ion and o ien a ion o an objec in space by h ee
componen s o ansla ion and h ee componen s o o a ion (e.g., swi els le and igh -
yawing, il s o wa d and backwa ds - pi ching, pi o s side o side - olling). A six deg ees o
eedom (6DoF) expe ience allows o mo ing up and down (ele a ing/hea ing - Y T ansla ion),
mo ing le and igh (s a ing/swaying - X T ansla ion), mo ing o wa d and backwa ds
(walking/su ging - Z T ansla ion) in addi ion o yawing, pi ching, and olling. Hap ics a e
mechanisms and echnologies o ac ile eedback o enhance he in e ac ion expe ience wi h
onsc een in e aces ia ouch, ib a ion, and o ce eedback, c ea ing a i ual sense o ouch.
HMDs a e used as de ices wi h minia u e displays o p ojec ion echnology in eg a ed and
moun ed on helme s/ha s o in o eyeglasses o c ea e a i ual sense o sigh and sound.
Posi ional acking using 6DoF allows edge de ices o es ima e hei posi ion ela i e o he
en i onmen by combining HW and SW o de ec he absolu e posi ion. Head acking e e s o
he mo emen o he use 's head and is used o mo e he images displayed o ma ch he head's
posi ion. O ien a ion acking uses accele ome e s, gy oscopes, and magne ome e s o
de e mine how he use 's head u ns. Eye acking acili a es and seizes he way he use 's eyes
a e looking using ligh om in a ed came as, which is di ec ed owa d he pa icipan 's pupils,
inducing e lec ions in bo h he pupil and he co nea. These cen e co neal e lec ions (PCCR),
can p o ide in o ma ion abou he mo emen and di ec ion o he eyes. Eye acking is u ilised
o cap u e and analyse isual a en ion using hea maps, gaze eplays, and ou pu me ics o
a eas o in e es (AoI), conside ing he ime o i s ixa ion and ime spen . Full body acking is
de ined as he p ocedu e o acing humanlike mo emen s o he i ual subjec wi hin he
imme si e en i onmen s by eco ding in eal- ime ia HMDs and mul iple mo ion con olle
pe iphe als, he scene loca ion coo dina es o mo ing objec s o ca ch he mo emen o he
en i e body o he use . Inside-ou acking e e s o he posi ional acking echnique commonly
used in XR echnologies o ack he posi ion o HMDs and mo ion con olle accesso ies. The
di e ence compa ed wi h ou side-in acking is he came a loca ion o o he senso s used o
de e mine he objec 's posi ion in space. The XR edge de ices use an inside-ou acking wa ch
o de e mine how i s posi ion changes abou he en i onmen . Ou side-in acking e e s o
posi ional acking, whe e ixed ex e nal senso s a e placed a ound he iewe o decide he
headse 's posi ion and associa ed acked pe iphe als [7].
A summa y o exis ing ypical XR key pe o mance indica o s (KPIs) is p esen ed in Table 3-1. AR
can be conside ed a simple e sion o MR, and ad anced AR echnologies may be me ged
in o MR, while ul ima e XR may only consis o MR and VR.

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Table 3-1 Typical exis ing VR, AR, and MR sys em speci ica ions and echnical equi emen s [21].
Speci ica ion
VR
AR
MR
Sc een
Occlusion
T anslucen
T anslucen
Display
HMD
OHMD
OHMD
En i onmen
Vi ual
Passi e i ual & eal
Passi e i ual, ac i e i ual, eal
Uplink Da a Ra e
150 kbps
0.02 - 1.0 Gbps
0.02 - 1.0 Gbps
Downlink Da a Ra e
0.02 - 1.0 Gbps
0.02 - 1.0 Gbps
0.02 - 1.0 Gbps
La ency
20 - 1000 ms
20 ms
10 ms
Re esh Ra e
∼90 Hz"
∼90 Hz
∼90 Hz
Pixels-pe - Deg ee
10 - 15
30 - 60
30 - 60
Field-o - View
100◦-
150◦
20◦ - 50◦
20◦ - 50◦
The p og ession owa ds Web 4.0 in ol es he In e ne becoming mo e in elligen and
au onomous. Technologies like he seman ic Web enhance da a connec i i y h ough be e -
s uc u ed, linked da a ha machines can unde s and and p ocess. In an XR con ex , his means
dynamically gene a ed con en ha is con ex ually ele an o wha he use sees o in e ac s
wi h. Blockchain echnologies ensu e secu e, decen alised p ocessing and s o age o he
massi e amoun s o da a gene a ed by edge IoT de ices and used in XR en i onmen s.
Figu e 3-3 XR applica ion landscape. Sou ce: Adap ed om F os & Sulli an
The con e gence o IoT, edge compu ing, AI, and XR wi hin he In e ne Web 4.0 amewo k is
poised o c ea e a mo e connec ed, esponsi e, and imme si e digi al u u e. This will enhance
cu en applica ions and open new possibili ies in how humans li e, machines ope a e, wo k,
and in e ac wi h humans and o he machines in physical, digi al, i ual, and cybe
en i onmen s. Figu e 3-3 illus a es he expec ed applica ion landscape o XR imme si e
echnology.
2.5 Me a e se
The e ms " e se," "me a e se," "omni e se," and "mul i e se" a e pa o he u u e de elopmen
o imme si e echnologies, and each e m ep esen s a concep , anging om digi al, i ual,
and cybe ecosys ems abou he uni e se. "Ve se" is a gene al su ix ha deno es a ype o
uni e se and is used as a sho hand in a ious con ex s o e e o a uni e se o a pa icula
imme si e en i onmen wi hin a b oade con ex .
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Ve ses a e dynamic concep s in digi al echnology ha o e imme si e digi al expe iences ha
seamlessly in e connec people, places, machines, objec s, and in o ma ion in eal- ime,
anscending he cons ain s o he physical wo ld.
The me a e se displays six cha ac e is ics as illus a ed in Figu e 3-4: imme si eness, which e e s
o a compu e -gene a ed i ual en i onmen su icien ly ealis ic o use s o eel
psychologically and emo ionally in ol ed and h ough senso y pe cep ion (e.g., sigh , sound,
ouch, empe a u e, and p essu e) and exp essions (e.g., ges u es and signs), i is possible o
unde s and i ; spa io empo al ha ep esen s he limi s o he eal wo ld due o he ini eness o
space and he i e e sibili y o ime, which e e s o he b eak o space and ime limi a ions in
he me a e se, a i ual space- ime con inuum pa allel o he eal one; sus ainabili y
ep esen ing a high deg ee o independence and a closed economic cycle indica es ha he
me a e se main ains a consis en alue sys em and a closed economic loop; in e ope abili y
ha implies ha use s can seamlessly mo e be ween i ual wo lds (i.e., sub- e ses) wi hou
in e up ing he imme si e expe ience, conside ing ha he digi al asse s used o ende ing o
econs uc ing i ual wo lds can be in e changed be ween di e en pla o ms; scalabili y,
which is he abili y o emain e icien wi h he numbe o concu en use s/a a a s, he le el o
scene complexi y, scope, and ange o in e ac ions be ween use s/a a a s and he e ogenei y,
conside ing he exis ence o he e ogeneous i ual spaces wi h dis inc implemen a ions,
he e ogeneous physical de ices wi h di e en in e aces, he e ogeneous da a ypes,
he e ogeneous communica ions modes, and di e se human psychology. A a a s can
seamlessly a e se a ious i ual wo lds, including sub- e ses, o expe ience a digi al
en i onmen and pa icipa e in i ual economic ac i i ies h ough physical in as uc u es and
a me a e se incen i e [8][61].
Figu e 3-4 Ve ses cha ac e is ics. Sou ce: Adap ed om [8]
The me a e se in eg a es a sense o imme sion, eal- ime in e ac i i y, and use ins umen s while
including pla o ms and de ices ha wo k seamlessly wi h each o he , mul iple people and
machines ha in e ac simul aneously, and use cases ac oss sec o s. The me a e se emb aces
and augmen s eali y wi h i ual con en and expe iences ha can enhance he expe iences
in i ual spaces.
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Figu e 3-5 The concep o e ses in he con ex o imme si e echnologies.
A me a e se is a digi al uni e se c ea ed by con e ging enhanced physical and pe sis en
i ual eali y. The me a e se desc ibes i ual wo lds, whe e use s, ep esen ed by a a a s,
engage in 3D en i onmen s, pe o ming in e ac ions o build social and economic connec ions
[18]. This concep o igina ed in Neal S ephenson's 1992 science ic ion no el "Snow C ash," which
po ays an imme si e i ual ealm [38]. In "Snow C ash," he me a e se is imagined as a u u e
e sion o he In e ne , a uni ied and imme si e i ual wo ld enabled by VR and AR headse s.
These i ual wo lds a e compu e -simula ed en i onmen s inhabi ed by use s who can c ea e
pe sonal a a a s. Use s independen ly explo e, pa icipa e in ac i i ies, and communica e
wi hin hese spaces. A a a s can ange om ex ual and g aphical ep esen a ions o li e ideo
a a a s wi h audi o y and ac ile eedback.
The me a e se is an in e disciplina y concep as illus a ed in Figu e 3-6 ha encompasses an
in e connec ed ne wo k o sha eable and pe sis ing i ual wo lds, AR, and he In e ne ha
allows end use s o expe ience a sense o social p esence and spa ial awa eness in a h ee-
dimensional i ual space and pa icipa e in an ex ensi e i ual economy. The me a e se
concep is o en associa ed wi h science ic ion and VR bu is also being de eloped as a
po en ial u u e eali y. Va ious echnologies such as VR/AR, 3D modelling and anima ion SW,
game engines, cloud, and edge compu ing, blockchain, in elligen connec i i y ne wo ks, AI
and ML a e u ilised o c ea e and suppo a me a e se.
The indus ial me a e se welds physical-digi al-cybe usion and human augmen a ion o
indus ial applica ions. I inco po a es digi al ep esen a ions o physical indus ial en i onmen s,
IoT de ices, sys ems, asse s, and spaces ha people manage, con ol, communica e and
in e ac wi h.
These echnologies con inue o de elop and imp o e as he me a e se p og esses allowing o
c ea ing imme si e b and expe iences o i ual s o e on s, allowing people and machine o
in e ac wi h each o he in a new way, acili a ing emo e collabo a ion and communica ion
and sha e in o ma ion seamlessly ega dless o loca ion.
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Figu e 3-6 Me a e se in e disciplina i y.
The idea o he me a e se ha pos ula es as a hypo he ical i e a ion o he In e ne as a single,
uni e sal, and imme si e i ual wo ld is acili a ed by o he imme si e echnologies such as AR,
VR, MR. A me a e se is a ne wo k o 3D i ual wo lds ocused on social connec ions. I is an
open, sha ed, and pe sis en i ual space whe e use s can be digi al a a a s. The p emise o
he me a e se is ha use s can do e e y hing in he i ual wo ld ha hey can do in he eal
wo ld. The me a e se combines concep s o imme si e echnologies (VR, AR) and digi al
second li e.
The me a e se is a collec ion o e e y i ual wo ld buil using blockchain echnology. These
include gaming plane s, NFT galle ies, cu a ed lands, o digi al s ee s. The NFTs a e blockchain-
based okens ha each ep esen a unique asse designed o be c yp og aphically e i iable,
unique, o sca ce and easily ans e able. An NFT can be conside ed an i e ocable digi al
ce i ica e o owne ship and au hen ici y o a gi en digi al o physical asse . The me a e se is
no one place; i is a collec ion o no el digi al spaces ha people and machines call he nex
i e a ion o he In e ne . The me a e se di e s om online social pla o ms in e ms o he space
be ween cen alisa ion and decen alisa ion. Me a e se de elops digi al spaces ha allows
use s o use a single iden i y o a el ac oss and h ough he g owing ne wo k o i ual
landscapes. This makes i mo e like a mi o o he eal wo ld.
The e m me a e se is widely used ac oss a ious ields, including echnology, gaming, social
media, and academia. Howe e , i had ye o be o malised by a uni e sally accep ed
s anda dized de ini ion. The me a e se concep can be de ined as a collec i e i ual sha ed
space c ea ed by he con e gence o i ually enhanced physical eali y, pe sis en i ual
spaces, and he In e ne . I ep esen s an expansi e ne wo k o 3D i ual wo lds and simula ions
ha suppo he con inui y o iden i y, objec s, his o y, paymen s, and en i lemen s.
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Imme si e echnologies bene i om Web 4.0 us and secu i y ea u es o o e expe iences
ha a e no only isually and senso ially compelling bu also p o oundly engaging h ough eal
owne ship, economic pa icipa ion, and social in e ac ion. This can lead o mo e meaning ul
and sus ained engagemen in i ual spaces, as use s a e no jus passi e consume s bu ac i e
pa icipan s in hese digi al ecosys ems.
The syne gies be ween Web 4.0 and imme si e echnologies a e unlocking new possibili ies o
i ual expe iences, ede ining how we in e ac wi h digi al con en , engage wi h communi ies,
and ansac in i ual en i onmen s. As hese echnologies ad ance, hey a e likely o c ea e
mo e imme si e, in e ac i e, and inclusi e i ual wo lds ha closely mi o he complexi y and
ichness o he physical wo ld.
Web 4.0 embodies a new e a o he In e ne , concei ed as a decen alised online ecosys em
ounded on blockchain echnology. Unlike he p esen In e ne e sion (Web2), domina ed by
cen alised pla o ms and se ices owned by a hand ul o la ge co po a ions, Web 4.0 aims o
e u n con ol and owne ship o he use s.
The echnological ad ances i b ings ha e he po en ial o p o oundly change he way one
in e ac s wi h he digi al ealm, c ea ing a mo e open, anspa en , and use -empowe ed
in e ne .
The u u e o echnology, pa icula ly wi h he con e gence o IoT, edge compu ing, AI, and
indus ial imme si e echnologies, is poised o g oundb eaking de elopmen s, especially when
in eg a ed wi h eme ging concep s like he me a e se, he omni e se, he mul i e se, and
In e ne Web 4.0. This u u e e sion o he In e ne is expec ed o be mo e au onomous,
in elligen , and seamlessly in eg a ed in o e e yday objec s. I could le e age blockchain o
secu i y and decen alisa ion, acili a e mic o ansac ions wi hin he a ious e ses, and suppo
sophis ica ed AI-d i en in e ac ions.
The con e gence o hese echnologies signi ies a echnological shi , as well as a cul u al and
economic one, po en ially al e ing how we pe cei e and in e ac wi h he digi al and physical
wo lds. This con e gence p omises a mo e in eg a ed, imme si e, and in e ac i e u u e.

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4. Indus ial Imme si e Enabling Technologies Con e gence
The con e gence o indus ial imme si e enabling echnologies e e s o he in eg a ion and
syne gis ic applica ion o a ious ad anced echnologies o c ea e imme si e, in e ac i e, and
highly e icien indus ial en i onmen s. The goal is o enhance ope a ional e iciency, imp o e
sa e y, secu i y, and os e inno a ion in indus ial se ings.
In indus ial imme si e en i onmen s, edge compu ing p o ides he mechanisms o dis ibu ing
da a p ocessing and ede ines he IoT landscape by mo ing da a p ocessing and analy ics a
he edge by using AI/ML echniques and ensu ing an ad anced le el o embedded secu i y.
Figu e 4-1 Edge imme si e echnologies con e gence ac oss he alue chain.
Edge compu ing is a key ing edien o indus ial imme si e echnologies ha allows an e ec i e
deploymen o eal- ime applica ions, conside ing ha he p ocessing is pe o med close o he
da a sou ce. I also educes he o de o magni ude o ansmi ed da a, by no ansmi ing he
ex ensi e amoun o aw da a c ea ed by IoT de ices, a he jus sending smalle amoun o
da a, hanks o s o age and local p ocessing capabili ies.
3.1 In e ne o Things
IoT ep esen s a dynamic global ne wo k in as uc u e endowed wi h sel -con igu ing
capabili ies, u ilizing s anda d in e ope able communica ion p o ocols. This ne wo k in eg a es
physical and i ual “ hings” - each possessing unique iden i ies, physical cha ac e is ics, and
i ual pe sonali ies - h ough in elligen in e aces, enabling seamless in eg a ion in o he
in o ma ion ne wo k. In his ecosys em, “ hings” ac i ely pa icipa e in business, in o ma ional,
and social p ocesses, capable o in e communica ion and en i onmen al in e ac ion.
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They au onomously eac o eal-wo ld e en s and in luence ou comes by execu ing p ocesses
ha igge ac ions and gene a e se ices, wi h minimal o no human o e sigh . Se ice-o ien ed
in e aces acili a e hese in e ac ions by allowing emo e que ying and modi ica ion o hei
s a es and ela ed in o ma ion, all while add essing secu i y and p i acy conce ns.
In he con ex o indus y digi isa ion, IoT and Indus ial IoT (IIoT) me ge key a ibu es o
ad anced In e ne echnology, mobile sys ems, and pe asi e connec i i y wi h indus ial
con ol unc ionali ies, including sensing, ac ua ing, and con olling. In e ope abili y, pla o m
in eg a ion, and s anda disa ion a e c ucial in he digi iza ion o indus ial applica ions. IoT, IIoT,
and indus ial con ol sys ems inco po a e essen ial a ibu es like in eg i y, a ailabili y, and
con iden iali y, c ucial o applica ion deploymen wi hin and ac oss a ious indus ial sec o s.
Edge compu ing is de ined as a pa adigm ha can be implemen ed using di e en
a chi ec u es buil o suppo an IoT dis ibu ed in as uc u e o da a p ocessing (signals, image,
oice, e c.) wi h edge IoT de ices ope a ing close o he poin s o collec ion (da a sou ces) and
u ilisa ion. The edge compu ing dis ibu ed pa adigm p o ides compu ing capabili ies o he IoT
nodes and de ices o he edge o he ne wo k (o edge domain) o imp o e he pe o mance
(ene gy e iciency, la ency, e c.), ope a ing cos , secu i y and eliabili y o applica ions and
se ices. Edge compu ing pe o ms da a analysis by minimising he dis ance be ween IoT nodes
and de ices and educing he dependence on cen alised esou ces ha se e hem while
minimising ne wo k hops.
IoT edge compu ing capabili ies include a s eady ope a ing p ocedu e ac oss di e en
pla o m in as uc u es o deli e p ocessing se ices o emo e IoT de ices, applica ion
in eg a ion, o ches a ion, and se ice deli e y equi emen s. The edge compu ing echnologies
a e mean o p ope ly conside HW limi a ions and cos cons ain s, o e ec i ely handle limi ed
o in e mi en ne wo k connec ions, and o implemen me hods o sa is y he mos di e se
equi emen se s, e.g., IoT applica ions equi ing low la ency o g ea ly di e ing in da a a es.
Fo in elligen IoT applica ions, he edge compu ing concep is mi o ed in he de elopmen o
di e en edge compu ing le els (mic o, deep, me a), ha inco po a e he compu ing and
in elligence con inuum om he senso s/ac ua o s, p ocessing uni s, con olle s, ga eways, on-
p emises se e s o he in e ace wi h mul i-access, og, and cloud compu ing.
Figu e 4-2 Edge IoT key a ibu es cha ac e ised by 6As and 6Cs.
Edge IoT and indus ial imme si e echnology de elopmen s a e cha ac e ised by six key
a ibu es, collec i ely known as he 6As: Any hing (any de ice) ans e ed om/ o Anyone
(any pe son/machine), loca ed Anywhe e, a Any ime (in any con ex ), using Any pa h (any
ne wo k) o op imal connec i i y based on pe o mance and economic conside a ions, all o
p o ide Any se ice (any business). The in elligen edge IoT pa adigm has e ol ed, leading o
he c ea ion o IoT ecosys ems buil on ounda ional elemen s e med he 6Cs: Collec (di e se
de ices o a ying complexi y and in elligence enhance eal- ime da a collec ion), Connec
(ubiqui ous connec ions be ween hese di e se de ices and da a), Cache (da a s o age wi hin
dis ibu ed IoT compu ing en i onmen s), Compu e (ad anced da a p ocessing), Cognise
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(analy ics and eal- ime AI p ocessing), and Collabo a e (c ea ing/de eloping new
in e ac ions, se ices, and business models h ough collabo a ion) [41][40].
The IoT ans o ms e e yday objec s in o ich ecosys ems o in o ma ion ha enhance ou li es.
I in luences he u u e In e ne landscape, impac ing secu i y and p i acy while po en ially
na owing he digi al di ide. As AI and IoT inc easingly ely on ne wo k connec i i y, hei
ulne abili y o secu i y h ea s g ows. The AI in IoT ma ke size was es ima ed a USD 9.17 billion
in 2023, USD 10.75 billion in 2024, and is expec ed o g ow a a CAGR o 17.35% o each USD
28.11 billion by 2030 [50].
The u u e success o he In e ne as a d i e o economic and social inno a ion hinges on how
hese new echnologies ackle such challenges. In eg a ing AI wi h IoT opens new oppo uni ies,
om scien i ic b eak h oughs o enhancing human in elligence and me ging i wi h he physical
and digi al ealms. The con e gence o IoT wi h echnologies like AI, DLTs, hype connec i i y,
dis ibu ed edge compu ing, and au onomous sys ems equi es heigh ened human-cen ic
sa egua ds and e hical conside a ions in hei design and implemen a ion [40].
The IoT b idges he gap be ween he i ual, digi al, and physical ealms by in eg a ing people,
machines, p ocesses, da a, and hings, gene a ing knowledge h ough IoT applica ions and
pla o ms. I add esses secu i y, p i acy, and us issues ac oss hese dimensions in a ime o
inc easing echnology, compu ing powe , connec i i y, ne wo k capaci y, and sma de ice
p oli e a ion. IoT is a key d i e o digi al and imme si e ans o ma ion in his con ex .
The p ima y added alue o IoT/IIoT and edge compu ing is he con ex ualisa ion and
onboa ding o he imme si e echnologies in he indus ial sec o s. The in elligen edge IT de ices
used in imme si e en i onmen s a e equipped wi h sensing, connec i i y, p ocessing, and
analy ics o unde s and complex si ua ions by agg ega ing in o ma ion, applying AI pa e ns
and inco po a ing use beha iou . This allows he decision-making p ocesses o be aligned wi h
a local, global con ex , isualise he e en and add a g aphical anima ion o ac ual and u u e
scena ios.
In elligen connec i i y, edge compu ing and IoT a e shaping he u u e o imme si e
echnologies. Thanks o highe bandwid hs, lexible ex e nal compu ing capaci ies, indus ial
imme si e applica ions a e eme ging in a ious indus ial sec o s.
IoT connec s physical and i ual wo lds. Da a om IoT-enabled de ices is collec ed, con e ed
in o in o ma ion, and made isible in eal- ime h ough in e ac ions in physical, digi al, i ual,
cybe , and spa ial en i onmen s. Imme si e echnologies ep esen he IoT, by augmen ing he
wo ld wi h in o ma ion de i ed om he IoT o e en imme sing humans and machines in he new
c ea ed spa ial en i onmen s.
3.2 In e ne o Things Senses
The no ion o "senses" wi hin he con ex o IoT likely e e s o he ex ension and enhancemen o
IoT capabili ies h ough ad anced senso y echnologies ha mimic human senses such as sigh ,
hea ing, ouch, smell, and as e. These senso y echnologies enable IoT de ices o pe cei e hei
en i onmen nuancedly, leading o mo e sophis ica ed da a collec ion, in e p e a ion, and
in e ac ion capabili ies in imme si e con ex s.
Sigh (Vision): This sense is media ed by ision senso s, which enable one o pe cei e ligh ,
colou s, shapes, and mo emen s. I 's essen ial o na iga ing ou en i onmen and ecognising
objec s and indi iduals. Came as and image ecogni ion echnologies allow IoT de ices o see
hei en i onmen . This can be used in applica ions such as imme si e sys ems, au onomous, and
quali y con ol in manu ac u ing.
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Hea ing (Audi ion): Hea ing is he abili y o pe cei e sounds by de ec ing ib a ions. I 's c ucial
o communica ion h ough language, ecognising sounds in he en i onmen . Mic ophones
and ad anced sound p ocessing echnologies enable de ices o hea and espond o audio
cues.
Tas e (Gus a ion): Tas e is he abili y o de ec la ou s in subs ances, including swee ness,
sou ness, sal iness, bi e ness, and umami (sa ou y). I 's i al o as ing ood and d inks and o
a oiding ha m ul subs ances. This is an e ol ing sense in IoT and eme ging in a eas like
en i onmen al moni o ing and ood sa e y.
Smell (Ol ac ion): The sense o smell allows us o de ec and di e en ia e odou s. I 's closely
linked o as e and memo y, signi ican ly in luencing he pe cep ion o la ou s and emo ional
memo ies. The IoT ad ances include senso s capable o de ec ing chemical composi ions o
speci ic gases ha mimic he human senses o smell.
Touch (Tac ile Sense): Touch is he abili y o pe cei e p essu e, empe a u e, and pain. I 's
essen ial o physical in e ac ion wi h he en i onmen and connec ion wi h humans, animals,
hings, and o he machines. Senso s ha de ec p essu e, empe a u e, o ib a ion allow IoT
de ices o " eel" physical in e ac ions in imme si e en i onmen s. This sense is c ucial o
wea ables, IoT de ices, and obo ics in eal and imme si e en i onmen s, e.g., in human-human
collabo a ion o human- obo -in e ac ion.
Tac ile IoT is o med by ne wo ks ha combine ul a-low la ency wi h ex emely high a ailabili y,
eliabili y, and secu i y, enabling he deli e y o physical sensa ions o ac ile expe iences
emo ely in eal and imme si e en i onmen s in eal- ime h ough ad anced hap ic
echnologies and high-speed ne wo ks.
Balance and Spa ial O ien a ion (Ves ibula Sense): Ves ibula sense helps main ain balance
and spa ial o ien a ion. I 's go e ned by he de ec ion o posi ion in ela ion o g a i y and
mo emen .
The sense o sigh is c ucial in connec ing pe cep ion o physical eali y, whe eas hea ing o e s
addi ional p oo o wha 's eal. When u he e i ica ion is needed beyond sigh and sound, one
na u ally seeks o ouch he objec o close examina ion. Touch p o ides he de ini i e
pe cep ual expe ience o a i m eali y, and his sense o imme sion can be enhanced h ough
ad anced media and senso y echnology. The Figu e 4-3 illus a es he ex ension o he use o
senses and he models de eloped o p o ide in o ma ion and imp o e he imme si e
expe ience wi h mo e mul i-senso y communica ion and in elligence.
Figu e 4-3 Edge imme si e mul i-senso y communica ions o p o iding in o ma ion and in elligence.
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Humans ha e addi ional senses, including p op iocep ion ( he sense o body posi ion and
mo emen ), he mocep ion ( he sense o empe a u e), and nocicep ion ( he sense o pain).
IoTS in imme si e applica ions need o ensu e in e ope abili y, eliabili y, and secu i y in IoT
applica ions e lec ing he ad ancemen s and in eg a ions o senso y capabili ies wi hin he
imme si e IoT edge ecosys em, enabling use s o expe ience and manipula e objec s in a i ual
o emo e en i onmen as i hey we e di ec ly in e ac ing wi h hem.
Hap ic echnology is pa o he e olu ion o he IoTS, in eg a ing imme si e echnologies wi h
de ices and algo i hms capable o gene a ing ouch sensa ions, including o ce eedback and
ex u e simula ion, allowing use s o eel he shape, ex u e, s i ness, and o he p ope ies o
i ual objec s.
The use o hap ic echnology o ouch-based social in e ac ions is called social ouch
echnology (STT). I add esses ci cums ances whe e human communica ion pa ne s engage in
social ouch media ed h ough echnology and si ua ions whe e humans in e ac wi h a i icial
social agen s ( i ual) ha can espond o applying social ouches. Fo ad anced imme si e
applica ions, hap ics o mul i-senso y communica ions is complemen ed by mixing hap ics
sensing and ac ua ion wi h o he modali ies, such as ision and sound, in a VR/AR con ex [19].
Table 4-1 Ac ua ion and modali ies wi hin a mul i-senso y communica ion o media ed social ouch [19].
Meaning
Type o ouch
Body Loca ion
Modali ies
Ac ua ion
A ec ion
Abs ac , Con ac ,
Hug, Squeeze, S oke,
Kiss, P ess, Tickle
Hand, Abdomen,
Leg, A m, Ches ,
To so, Back, Side, Lips
Touch, Vision, Audi ion
Vib o ac ile,
Tempe a u e, Fo ce
G ee ing
Handshake
Hand
Touch, Vision, Audi ion
Tempe a u e, Fo ce
Inclusion
Holding Hands
Hand
Touch
Tempe a u e, Fo ce
Play ul Agg ession
A m W es ling
Hand
Touch
Fo ce
Symbolic
Abs ac , Poke
Hand, Cheek, Finge ,
A m
Touch, Vision, Audi ion
Vib o ac ile, Fo ce
The Table 4-1 shows he ypes o ac ua ion and modali ies communica ed o e lec di e en
ypes o social ouch and meanings.
3.3 In e ne o Things Digi al Twins E ol ing o Imme si e T iple s
The expansion o imme si e echnologies ans o ms DTs in o imme si e iple s, de ined as he
dynamic spa ial, digi al, and i ual ep esen a ions o a physical objec o sys em, spanning
hei li ecycle, and upda ing om eal- ime condi ions and spa ial da a. They use imme si e
en i onmen s, simula ion, ML, and easoning o assis decision-making and c ea e eal- ime
a a a s o imme si e applica ions.
The con e gence o IIoT, AI, ML, DTs, and IMTs combined wi h XR a e he backbone o he
de elopmen o he indus ial me a e se by inc easing he in elligen capabili ies o he
elemen s in he imme si e indus ial spaces and changing how digi al models and physical
p oduc s in e ac using SDA in he u u e indus ial p ocesses and Indus y 5.0.
Imme si e iple s in eg a e IoT, edge and spa ial compu ing, AI, ML, and so wa e analy ics wi h
spa ial ne wo k g aphs o c ea e li ing imme si e simula ion models ha upda e, change, and
mo e in space as hei physical coun e pa s change. The key componen s o he imme si e
iple s include eal- ime da a in eg a ion o accu a ely eplica e IoT edge de ices in a i ual
3D space. This da a includes ope a ional da a, en i onmen al condi ions, physical pa ame e s,
spa ial coo dina es, and o he ele an in o ma ion.
As pa o he imme si e en i onmen s and a ious e ses, he imme si e iple s apply complex
simula ions and models ha can p edic u u e s a es, conduc analyses, and op imize sys ems
h ough simula ions be o e physical changes a e made.

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They co e he en i e li ecycle o hei physical coun e pa s, om design and de elopmen
h ough ope a ion o decommissioning, p o iding aluable insigh s a each s age. E ec i e
imme si e iple s can in eg a e wi h o he imme si e sys ems and pla o ms, ensu ing da a lows
seamlessly be ween di e en applica ion a eas.
IMTs ad ance imme si e echnologies by p o iding a de ailed, eal- ime digi al, i ual, and
spa ial eplica o physical objec s, p ocesses, sys ems, o en i onmen s. These i ual spa ial
models a e no s a ic; hey a e upda ed om eal- ime da a, enabling hem o accu a ely
simula e he cu en s a e o hei physical coun e pa s. In eg a ing IMTs wi h imme si e
echnologies like VR, AR, and MR d i es inno a ion ac oss a ious sec o s.
By inco po a ing eal- ime da a in o imme si e en i onmen s, IMTs make VR and AR expe iences
mo e ealis ic and in e ac i e. Use s can explo e and in e ac wi h i ual eplicas ha e lec he
s a us o he physical wo ld, including dynamic changes and eal- ime eedback. IMTs in
imme si e en i onmen s enable emo e eams o collabo a e mo e e ec i ely by in e ac ing
wi h he same i ual model om di e en loca ions and spa ial con ex s.
In an indus ial con ex , NFTs can ep esen physical asse s (e.g., IoT de ices, machines), digi al
asse s (SW, da a), o in ellec ual p ope y. The blockchain's immu able ledge ensu es ha each
asse 's his o y, om c ea ion h ough a ious owne ships o changes, is pe manen ly eco ded
and easily e i iable.
NFTs a e used o c ea e and manage IMTs and DTs o physical asse s, including moni o ing,
simula ion, and con ol. IoT de ices and hei imme si e iple s and digi al wins can ack and
eco d eal- ime asse use, condi ion, and loca ion da a. When pai ed wi h NFTs, his da a
becomes pa o he asse 's unique digi al oo p in on he blockchain, enhancing aceabili y
and secu i y.
By p ocessing da a a he edge, close o whe e i 's gene a ed, companies can quickly upda e
an NFT's s a us o e lec eal- ime changes, which is c ucial o dynamic and high- alue asse
managemen .
Edge AI algo i hms can analyse da a om imme si e iple s and DTs o op imise pe o mance,
p edic main enance needs, and enhance ope a ional e iciency. NFTs ensu e ha he da a
and models a e uniquely linked o speci ic asse s, adding a laye o secu i y and au hen ici y.
In eg a ing NFTs wi h IoT, edge compu ing, AI, and blockchain echnologies wi h imme si e
iple s and DTs holds signi ican po en ial o ans o ming indus ial ope a ions, supply chains,
and digi al asse managemen . This con e gence enhances ope a ional e iciency and
anspa ency and opens new a enues o asse u ilisa ion and alue c ea ion in indus ial
imme si e echnologies.
The syne gy be ween imme si e iple s and imme si e echnologies c ea es oppo uni ies o
mo e in e ac i e, accu a e, and e icien applica ions ac oss a ious sec o s. By b idging he
gap be ween he physical and digi al wo lds h ough 3D spa ial ep esen a ion and eal- ime
s amp, his in eg a ion enhances he ealism and applicabili y o imme si e expe iences and
unlocks new po en ials o inno a ion, collabo a ion, and lea ning.
3.4 Vi ual Replicas wi h Ac i e Fo ce Feedback
In eg a ing ac i e o ce eedback mechanisms can en ich sys ems such as imme si e iple s
ha ea u e i ual eplicas o physical spaces. This can signi ican ly enhance he human
in e ac ion wi h hese i ual eplicas. This allows indi iduals o no jus expe ience, bu also
ac i ely manipula e a i ual eplica o a physical space.
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Use s can exp ess ac ions in de ail, including manipula ing he posi ion and o ien a ion o an
objec and applying p ecise amoun s o p essu e o speci ic poin s on objec s.
These i ual in e ac ions can be used o con ey ideas, o di ec ly ansmi ed o obo ic de ices
on-si e ha execu ion o changes in he physical en i onmen . This s eamlines he
communica ion o complex ideas and ins uc ions h ough in ui i e ac ion.
3.4 Edge Compu ing
Edge compu ing mo es se ice p o isioning close o p oduce s and use s o such se ices. I
can p o ide educed la ency, mobili y suppo , and acili a e da a analy ics o be done close
o he da a sou ce and c ea es he possibili y o educed ene gy consump ion.
The con e gence o he IoT and edge compu ing wi h imme si e echnologies, such as VR, AR,
and MR, is c ea ing a ans o ma i e syne gy ha signi ican ly ad ances he capabili ies and
applica ions o each echnology. This in eg a ion b ings a new e a o imme si e expe iences
mo e in e ac i e, esponsi e, and in eg a ed wi h he eal wo ld.
The syne gies c ea ed by IoT, edge compu ing, AI, and imme si e echnologies enhanced eal-
ime in e ac i i y and p o ided low la ency by p ocessing da a close o he sou ce. This allows
use s o expe ience eal- ime in e ac ion wi h i ual en i onmen s wi h minimal delay, making
expe iences like VR and AR-guided applica ions mo e seamless and e ec i e.
Wi h IoT de ices gene a ing as amoun s o da a, edge compu ing enables eal- ime da a
analy ics. This le s imme si e applica ions dynamically adjus con en based on immedia e use
in e ac ions and en i onmen al condi ions, enhancing pe sonalisa ion and esponsi eness.
IoT de ices and edge compu ing pla o ms can p o ide eal- ime in o ma ion abou he
physical en i onmen , which can be in eg a ed in o AR and VR applica ions o c ea e mo e
con ex ually awa e imme si e expe iences and imp o e con ex ual and spa ial awa eness.
Spa ial compu ing, IoT, and imme si e echnologies combine o enable ad anced spa ial
compu ing capabili ies, whe e he physical and digi al spaces a e mo e igh ly in eg a ed. Use s
can in e ac wi h digi al objec s ha a e awa e o and esponsi e o hei en i onmen 's physical
layou and objec s, enabling mo e na u al and in ui i e in e ac ions.
IoT de ices and edge compu ing can ga he da a on use p e e ences, heal h me ics, and
en i onmen al condi ions. This allows imme si e applica ions o ailo expe iences in eal- ime o
he indi idual's needs and con ex , imp o ing accessibili y, pe sonalisa ion, and use sa is ac ion.
Wea able IoT de ices, edge compu ing p ocessing, and AI can enhance imme si e
expe iences h ough biome ic da a, enabling applica ions o adjus based on he use 's
physical esponses. This can lead o mo e engaging and pe sonalised con en .
Edge p ocessing educes he need o cons an high-bandwid h connec i i y o he cloud,
making i mo e easible o deploy imme si e echnologies in bandwid h-cons ained
en i onmen s ha inc ease he scalabili y and e iciency o he echnology. Edge compu ing
can educe he ene gy consump ion o da a p ocessing o IoT de ices, ex ending he ba e y
li e o wea able and po able imme si e echnology de ices.
AI can boos IoT and edge compu ing by o e ing mo e in elligen da a analysis ools and
acili a ing eal- ime au onomous decision-making.
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I also o esees main enance equi emen s in indus ial con ex s o ailo s' use in e ac ions in
i ual se ings acco ding o beha iou and p e e ences. AI's ole in comp ehending and
handling he complexi y o in e ac ions wi hin mul i e se en i onmen s, whe e se e al i ual
wo lds coexis , is essen ial.
The syne gies be ween IoT, edge compu ing, and imme si e echnologies d i e signi ican
ad ances ac oss a ious sec o s by enhancing in e ac i i y, con ex ual awa eness, use
expe ience, and scalabili y. This in eg a ion is pa ing he way o inno a i e applica ions ha
we e p e iously challenging o impossible o achie e, p edic ing a new e a o digi al in e ac ion
ha muddies he lines be ween he physical and i ual wo lds.
3.5 Spa ial Compu ing
Spa ial compu ing is a ounda ional echnology ha enables imme si e echnologies and
b idges he digi al and physical wo lds. I in eg a es he unde s anding and managemen o
physical space in o compu ing, allowing digi al objec s o exis and in e ac in h ee dimensions
in a way ha mi o s eal-li e expe iences. This capabili y is cen al o he de elopmen and
e ec i eness o imme si e echnologies such as VR, AR, and MR. He e is how spa ial compu ing
plays a pi o al ole:
Spa ial compu ing enables ealis ic in e ac ions ha allow accu a e mapping and
unde s anding o eal-wo ld en i onmen s and ansla e ha in o ma ion in o digi al con ex s.
This enables imme si e echnologies o place i ual objec s in eal spaces so ha hey appea
and beha e as i hey a e uly pa o ha space.
Spa ial compu ing is used in AR o o e lay digi al con en on o he physical wo ld seamlessly,
making i possible o use s o in e ac wi h i ual objec s using hei eal physical mo emen s.
Spa ial compu ing makes i ual en i onmen s mo e belie able and imme si e by
unde s anding he spa ial ela ionships be ween objec s and accu a ely in e p e ing use
mo emen s and in e ac ions. In VR, his means c ea ing a digi al space ha use s can na iga e
and in e ac wi h na u ally and in ui i ely, signi ican ly enhancing he eeling o p esence wi hin
a i ual en i onmen .
In MR applica ions, spa ial compu ing is essen ial o blending eal and i ual wo lds o enable
de ices o ecognise and eac o physical spaces and objec s, allowing o he in eg a ion o
digi al con en in o he physical wo ld a a le el o complexi y and in e ac i i y p e iously
una ainable. This includes ecognising su aces and bounda ies, spa ial audio, and in e ac ions
ha conside he physics o he use ’s en i onmen .
The ole o spa ial compu ing is o allow o a digi al access o he eal physical wo ld by
ans o ming eal objec s and asse s in o si ua ed, digi alized, seman ically unc ional and
dynamic digi al en i ies. To accomplish his goal, spa ial compu ing is no limi ed o geome y
econs uc ion o he su oundings, bu also usually implemen s a seman ic unde s anding o he
scene, using objec ecogni ion, segmen a ion, iden i ica ion, and s a e es ima ion. The esul is
a comple e digi al cap u e o he ex en , space, spa ial loca ion, unc ionali y, dynamic s a e
o any spa ial en i y.
Spa ial compu ing enables na u al use in e aces (NUIs) ha allow use s o in e ac wi h digi al
en i onmen s ins inc i ely, using ges u es, speech, and mo emen . This emo es he need o
adi ional inpu de ices like keyboa d and mouse, making he echnology mo e accessible and
engaging o a b oade ange o use s. Wi h spa ial compu ing, designe s and de elope s can
c ea e expe iences ha le e age he h ee-dimensional space, leading o inno a i e
in e ac ion and engagemen .
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This includes spa ially awa e applica ions and se ices o educa ion, aining, en e ainmen ,
and mo e, o e ing use s no el ways o lea n, explo e, and connec wi h con en .
Spa ial compu ing echnologies, combined wi h mul iple senso s, IoT, edge compu ing, AI,
machine ision, and p ocessing algo i hms, allow o p ecise acking o use mo emen s and
he accu a e posi ioning o i ual objec s in eal spaces and e ses. This p ecision is i al o
applica ions ha equi e exac in e ac ions and eal- ime spa ial in e ac ions, such as mobile
au onomous IoT sys ems.
The de elopmen s and adop ion o spa ial compu ing on he web accele a e as web s anda ds
e ol e and in e ne speeds inc ease. The ends a e a ec ed by he ad ancemen s in indus ial-
edge imme si e echnologies ha u he blu he lines be ween physical and digi al spaces,
leading o mo e inno a i e applica ions and changing how we in e ac wi h he web and he
physical wo ld.
Web 4.0 is en isioned as a mo e in elligen , au onomous, and decen alised In e ne i e a ion,
elying on AI, enhanced da a p ocessing, and 3D imme si e echnologies. Spa ial compu ing
ex ends his ision by adding a laye o spa ial in elligence o he In e ne , enabling in e aces
and expe iences ha a e mo e in ui i e and in eg a ed wi h he use 's physical en i onmen .
In eg a ing spa ial compu ing wi h IoT means his da a can be u ilised o c ea e highly
con ex ual and in e ac i e maps o en i onmen s. IoT de ices can in e ac wi h spa ial
compu ing sys ems o c ea e en i onmen s ha unde s and and espond o human and
machine p esence and ac i i ies. Edge IoT in ol es he deploymen o nume ous senso s and
de ices ha collec da a om hei en i onmen . In eg a ing spa ial compu ing wi h edge IoT
and imme si e echnologies means his da a can be u ilised o c ea e highly con ex ual and
in e ac i e maps o en i onmen s.
Edge compu ing p ocesses da a a o nea he sou ce o da a gene a ion, which is c ucial o
spa ial compu ing applica ions ha equi e low la ency, such as au onomous ehicles o
in e ac i e imme si e applica ions. I also allows o ins an aneous eac ions and adjus men s in
dynamic en i onmen s, which is essen ial o applica ions like au onomous d i ing o obo ic
su ge y. Edge AI and machine lea ning can analyse and lea n om he spa ial da a collec ed,
enhancing he capabili ies o spa ial compu ing applica ions. Based on he low o people o
goods, hey can p edic pa e ns and sugges op imisa ions o spa ial layou s in indus ies like
e ail o manu ac u ing. They can also imp o e ges u e and oice ecogni ion sys ems ha
in e ac wi h spa ial compu ing en i onmen s, making hem mo e in ui i e and esponsi e.
Imme si e echnologies a e na u al ex ensions o spa ial compu ing, p o iding use s wi h
imme si e expe iences ha blend eal and i ual wo lds and enhance he ealism o i ual
en i onmen s by accu a ely eplica ing he physics and geome y o eal-wo ld spaces and
enabling a sha ed i ual wo kspace whe e physical bounda ies a e no longe a limi a ion,
allowing eal- ime collabo a ion and in e ac ion.
In eg a ing spa ial compu ing wi h Web 4.0, IoT, edge compu ing, AI, and imme si e
echnologies could lead o a mo e in ui i e, e icien , and in e ac i e digi al u u e. This
con e gence p omises o eshape how we in e ac wi h digi al sys ems and he physical wo ld,
making ou in e ac ions mo e synch onised and con ex -awa e.
Spa ial compu ing p o ides he echnical unde pinning o imme si e echnologies o lou ish,
and o AR, VR, MR o be in eg a ed in an XR uni ied app oach o e ing ools and amewo ks
ha b ing digi al and physical ealms close oge he . As spa ial compu ing e ol es, i will
con inue o expand he capabili ies and applica ions o imme si e echnologies, making hem
mo e in eg a ed in o daily li es and wo k.
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The o al ib e op ical spec um a ailable is mo e han 1000 THz, and co e ne wo ks ha will
p o ide connec i i y capaci y o imme si e applica ions ely almos en i ely on ib es.
The Figu e 4-5 shows he e olu ion o high-capaci y op ical anspo ib e ne wo ks and he
leading echnologies ha ha e impac ed he e olu ion. The limi s o op ical ib e echnology
a e compa able o Moo e’s Law, which shows he exponen ial g ow h in he numbe o de ices
in semiconduc o ci cui s and o simila log g adien s g owing by a ac o o 1.4 pe yea [60].
Mesh ne wo king in ol es a ne wo k opology whe e nodes connec di ec ly, dynamically, and
non-hie a chically o as many o he nodes as possible and coope a e o e icien ly ou e da a
o and om use s in eal and i ual en i onmen s. This sel -healing, lexible ne wo king app oach
ensu es high eliabili y and scalabili y. Imme si e in elligen mesh connec i i y enhances
imme si e expe iences by acili a ing high-bandwid h, low-la ency connec ions essen ial o VR,
AR, and MR applica ions. I ensu es use s elish seamless, ealis ic, imme si e expe iences wi hou
in e up ions o delays.
Technologies con e gence le e ages AI o op imisa ion and pe sonalisa ion o manage
ne wo k esou ces dynamically, adap ing o use beha iou and en i onmen al changes o
op imise pe o mance and enhance use expe iences in eal and imme si e en i onmen s. This
includes AI-d i en con en deli e y, ne wo k secu i y, and use in e ace adap a ion.
The imme si e echnologies employ he mesh ne wo k in as uc u e o p o ide obus , ex ensi e
co e age o ensu e use s can access imme si e, in elligen se ices any ime, anywhe e, o any
de ice by c ea ing lexible, e icien wo kspaces ha ely on a mix o eal and i ual
in e ac ions. The in eg a ion o hese echnologies could p o ide he nex -gene a ion digi al
in as uc u e, o e ing unp eceden ed le els o in eg a ion, in e ac ion, and imme sion in digi al
en i onmen s.
Figu e 4-6 Senso y communica ions h oughpu and la ency equi emen s. Sou ce: [43].

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The ad ancemen , de elopmen , and oll-ou o in elligen connec i i y echnologies and
ne wo ks a e c i ical as imme si e echnologies equi e ubiqui ous communica ion and eal- ime
in e ac ion. The h oughpu and la ency equi emen s o di e en componen s o he imme si e
echnologies landscape a e illus a ed in Figu e 4-6, which clea ly show ha VR equi es
signi ican ly highe h oughpu and lowe la ency han ideo applica ions. As a esul , he
deg ee o which imme si e echnologies can achie e ull imme sion and b oad accessibili y
hinges on deploying and adop ing connec i i y op ions like op ical ib e, 5G, Wi-Fi 7, and
o hcoming echnologies such as 6G.
Imme si e expe iences equi e s ingen low la ency and high bandwid h pe o mance o
deli e imme si e en i onmen s and eal- ime beha iou . The capabili ies o new Wi-Fi p o ocols
enable he ull po en ial o imme si e applica ions, suppo ing esponsi e, engaging AR, VR, MR,
XR and e ses expe iences by p o iding mul i-gigabi speeds o ins an aneous da a exchange,
powe e iciency o deli e apid, e icien da a ans e s and bounded la ency and high
eliabili y o lag- ee expe iences in conges ed en i onmen s.
Wi-Fi se es as one o he ounda ions o connec i i y o new and eme ging imme si e
applica ions. The 6 GHz spec um o Wi-Fi 6E and Wi-Fi 7 ensu es ha edge de ices deli e ing
imme si e expe iences mee he high s anda ds o QoS and QoE pe o mance, in e ope abili y,
and secu i y.
Wi eless and cellula 5G/6G and beyond echnologies a e he ones o e ing he high-
bandwid h, low-la ency communica ion necessa y o suppo seamless in e ac ions be ween
physical, digi al, and i ual spaces.
To u he boos XR pe o mance, 5GAd anced (s a ing wi h 3GPP Rel-18 - Table I-1) in oduces
se e al he e ogeneous enhancemen s and ac i i ies handled wi hin a ious 3GPP Se ice and
Sys ems Aspec s (SA) and Radio Access Ne wo ks (RAN) g oup, including bo h XR-speci ic
enable s and se ice-agnos ic enhancemen s. An o e iew o hese inno a ions is illus a ed in
Figu e 4-7.
Figu e 4-7 Imp o ing suppo o he XR in 5G-Ad anced. Sou ce: Adap ed om [34].
The 3C connec ed collabo a i e compu ing me ges he IoT, ne wo k echnologies, edge
compu ing, AI in as uc u e and pla o ms and in eg a e hem in o di e en applica ions ac oss
indus ial sec o s.
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The 3C ecosys em, which spans semiconduc o s, IoT, pla o ms, AI, compu a ional capaci y a
edge and cloud en i onmen s, communica ion echnologies, connec i i y in as uc u e, da a
managemen , and applica ions a e essen ial o la ge-scale pilo s ha se up end- o-end
in eg a ed in as uc u es and pla o ms and b ing oge he playe s om di e en segmen s o
he connec i i y alue chain and beyond o demons a e he con e gence o echnologies in
di e en indus ial sec o s.
Some applica ions will need da a om IoT loca ed in a eas no co e ed by wi eless o
mobile/cellula ne wo ks, and 6G will in eg a e sa elli e connec i i y o add ess hese speci ic
cases. Wi h such in eg a ion, he ATAWAD (AnyTime, AnyWhe e AnyDe ice/Any hing) alue
p oposi ion will be eached, and imme si e applica ions will ake ad an age o ha e olu ion.
3.8 In eg a ion o Sensing and Communica ions
In eg a ing ad anced IoT senso y echnologies and in elligen mesh connec i i y is essen ial o
con e ging edge imme si e echnologies. Edge AI and imme si e in elligen mesh connec i i y
allow o he classi ica ion, de ec ion, localisa ion, and es ima ion o an objec 's a ibu es and
o he unc ions. The IoT is expec ed o combine sensing and communica ion echnologies in o
a ully in eg a ed sys em. Sys ems inco po a ing join communica ion and sensing (JCAS)
unc ionali ies ep esen a signi ican inno a ion o 6G ha will acili a e nume ous eme ging
imme si e echnologies and applica ions and enable he concep o a pe cep i e ne wo k.
The communica ion componen o an JCAS sys em would mean connec ing he digi al,
physical, and human wo lds in eal- ime wi h all ex eme equi emen s coming om he
imme si e echnology alue chain (Figu e 4-1). The sensing componen , on he o he hand, will
p o ide us wi h he capabili y o sense he wo ld and o p o ide con ex in o ma ion o c ea e
he digi al map o he en i onmen , which is a p e equisi e o c ea ing he DTs and seamless
in eg a ion o he physical, digi al, i ual, and cybe wo lds. Wi h JCAS in 6G and beyond, we
will ha e he capabili y o no only localise objec s ha a e pa o he ne wo k bu also o sense
and in eg a e objec s ha a e no connec ed o he ne wo k. Fo eal- ime imme si e
applica ions, in eg a ing a human model wi h a DT ep esen a ion o he physical wo ld en ails
exchanging mul imodal da a, such as hap ics, posi ion, eloci y, and in e ac ions, as well as he
senses in he IoT con ex , including human ges u es, head mo emen s and pos u e, eye
con ac , acial exp essions, emo ions, e c. [44].
The JCAS in eg a ion is en isioned in di e en ways, om loosely coupled o ully in eg a ed,
sha ed spec um, sha ed HW, o sha ed signal p ocessing module and ne wo k p o ocol s acks,
and e en using he same wa e o m o bo h communica ions and sensing. Sensing unc ionali y
can be in oduced as a se ice wi h a low inc emen al cos as i le e ages equipmen and
spec um deployed o communica ion pu poses. JCAS can ex end he capabili y o cellula
ne wo ks by adding see-and- eel unc ionali ies. The edge de ices can sense hei su oundings
and exchange hei sensing esul s h ough communica ion links. F om a ne wo k pe spec i e,
he widely deployed base s a ions o legacy cellula se ice could be e-used o wide-a ea
seamless RF sensing. Inco po a ing AI, communica ions, posi ioning, and sensing capabili ies,
he cellula ne wo k could in elligen ly use he physical wo ld wi h he digi al wo ld and p o ide
a ious new se ices o consume s and indus y cus ome s [1].
Sys ems wi h JCAS unc ionali ies a e s ill in hei ea ly s ages, and du ing he nex ew yea s, a
subs an ial amoun o addi ional esea ch will be needed. They will also sha e esou ces in he
ime, equency, and space domains and essen ial componen s, including HW, wa e o ms, and
signal p ocessing. This implies ha he signals o he cellula sys em will be used o signi ican ly
inc ease he sensing capabili ies in addi ion o he communica ion ne wo k anspo ing senso
da a.
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In eg a ing communica ion and sensing can add ambien IoT o budge - iendly and powe -
e icien edge de ices ha acili a e he connec ion o nume ous objec s and i ems o ne wo ks,
allowing o many applica ions. The d i ing o ces behind ambien IoT a e ene gy ha es ing,
s o age, and backsca e ing echniques. Ene gy ha es ing and s o age can include di e se
ene gy sou ces, including RF signals, ligh , ib a ions, and he mal ene gy. Di e en ene gy
sou ces ha e a ying le els o a ailabili y and ene gy densi y. The backsca e ing echnique
can in ol e a ew o he ac o s. Backsca e ing, combined wi h ac i e signal gene a ion (e.g.,
powe ampli ie s), minimises powe consump ion in Ambien IoT de ices. In backsca e ing, he
ansmi ed signal e lec s con inuous wa es om a eade , modula ed wi h in o ma ion o
communica ion. Ambien IoT's eliance on ene gy ha es ing and backsca e ing holds he
po en ial o ad ance low-cos , main enance- ee, and en i onmen ally sus ainable IoT
solu ions.
The combined unc ionali y o communica ion and sensing also acili a es eme ging secu e
p oximi y se ices. Such echnology ensu es he secu e and p i a e exchange o da a be ween
de ices in close physical p oximi y, enabling applica ions like mobile paymen , in elligen
access con ol, communica ion o e e y hing and IIoT. The sensing ea u e ac s as he
au hen ica ion mechanisms o sa egua d he communica ion and p e en unau ho ized
access o da a b eaches. JCAS also allows secu e communica ion links by localising po en ial
ea esd oppe s, p e en ing he decoding o malicious da a, and ac i a ing ocussed coun e -
a ack measu es based on enc yp ion and au hen ica ion p o ocols in combina ion wi h
dynamic beam o ming o special il e ing.
The ambien IoT edge de ices can be used as pa o he imme si e spaces o p o ide eal- ime
in o ma ion abou he en i onmen al condi ions in he physical wo ld.
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5. Imme si e Physical-Digi al-Vi ual Spa ial Compu ing Con inuum
The imme si e physical, digi al, i ual, and spa ial compu ing con inuum e e s o he seamless
in eg a ion and in e ac ion ac oss physical, digi al, and i ual en i onmen s acili a ed by
ad anced compu ing co e ing edge, swa m, spa ial, og and cloud echnologies. This
con inuum is buil on he ounda ion o p ocessing da a and p o iding capabili ies o enable
compu e s o unde s and and manipula e spa ial da a ep esen ing he physical wo ld and i s
dynamics in digi al, i ual and 3D spa ial o ms.
The key elemen s o his con inuum include he physical, digi al, i ual and 3D spa ial spaces.
The physical space is de ined by he angible, eal-wo ld en i onmen , which includes
e e y hing om he physical layou o a oom o he na u al en i onmen ou side. Spa ial
compu ing echnologies in his domain o en in ol e sensing and a ec physical space, such
as obo ics and IoTS de ices.
The digi al space is de ined by he digi al ep esen a ion o in o ma ion, including he physical
wo ld's digi al wins and pu ely digi al da a and p ocesses. This space is whe e da a om he
physical wo ld is collec ed, p ocessed, and analysed o c ea e ac ionable insigh s o simula ions.
The i ual space encompasses ully digi al en i onmen s ha can be expe ienced wi h high
deg ee o imme sion h ough echnologies like VR, AR, and MR. These spaces a e no bound by
he physical laws o he eal wo ld, allowing o expe iences conside ably di e en om eal-li e
in e ac ions.
The con inuum emphasises he luid mo emen and in e ac ion be ween hese spaces,
p o iding a comp ehensi e amewo k o unde s anding how digi al in o ma ion and i ual
expe iences a e inc easingly in eg a ed in o ou physical wo ld.
Spa ial compu ing suppo s 3D space and e e s o he compu a ional echniques and
echnologies ha enable he abo e in e ac ions, including compu e ision, senso usion, and
spa ial easoning, allowing compu e s o pe cei e and in e ac wi h he 3D wo ld.
The imme si e physical, digi al, i ual, and spa ial compu ing con inuum ep esen s an
eme ging ision whe e he bounda ies be ween hese spaces become inc easingly blu ed,
enabling mo e na u al and in ui i e in e ac ions wi h and h ough echnology. This con inuum is
abou he echnologies and c ea ing expe iences ha enhance human and machine
capabili ies, imp o e e iciency, and enable new o ms o c ea i i y and exp ession in imme si e
applica ions.
The con e gence and syne gies be ween imme si e echnologies (VR, AR, and MR) and
holog aphic echnologies ep esen a signi ican e olu ion in how we in e ac wi h digi al
in o ma ion and he physical wo ld. This con e gence c ea es new possibili ies o in e ac ion,
isualisa ion, and communica ion, blending he physical and digi al ealms.
In eg a ing holog aphic displays wi h VR and AR echnologies can enhance he sense o
imme sion and ealism. Holog ams can be p ojec ed in o he physical space, allowing use s o
iew and in e ac wi h 3D images wi hou needing headse s o speci ic iewing angles. This
in eg a ion can make i ual mee ings, elep esence, and emo e collabo a ion mo e li elike
and engaging.
By combining holog aphic echnology wi h spa ial compu ing and ges u e ecogni ion, use s
can in e ac wi h holog ams di ec ly wi hou wea ables. This syne gy allows o c ea ing
in e aces and applica ions whe e in o ma ion can be manipula ed wi h hands o body
mo emen s, elimina ing he need o con olle s o wea able de ices.
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Al e na i ely, using con olle s o wea ables ha can p o ide addi ional o ms o eedback, such
as ib o ac ile, esis i e, and ac i e o ce eedback, allows he use o ha e a iche expe ience
o he digi al en i onmen o i ual eplica. These addi ions could enable humans o exp ess
ac ions in g ea e de ail, including he amoun o applied p essu e equi ed o handle asks ha
equi e g ea p ecision and sub le y. These addi ions can also be used in applica ions whe e
ision alone does no p o ide su icien in o ma ion, o example, due o an obs uc ed iew.
Edge imme si e echnologies equi e pa icipan s o use hei de ices (like VR headse s) o
expe ience digi al con en . The in eg a ion wi h holog aphic echnology enables mul iple use s
o iew and in e ac wi h he same digi al con en simul aneously in a sha ed physical space,
os e ing collabo a ion and making sha ed expe iences mo e na u al and accessible.
Cu en AR echnology o e lays digi al con en on o he eal wo ld h ough sc eens o AR
glasses, which can some imes lack dep h and spa ial accu acy. Holog aphic echnology can
p o ide be e dep h cues and spa ial posi ioning, making digi al con en appea as hough i
is genuinely pa o he physical wo ld.
The con e gence o imme si e and holog aphic echnologies has se e al challenges, including
ha dwa e limi a ions, cos , and he need o de elop holog aphic display echnologies u he .
As hese echnologies ad ance, hey p omise o c ea e mo e na u al, in ui i e, and accessible
ways o in e ac wi h digi al con en , leading o inno a ions ha could eshape edge imme si e
applica ions whe e digi al and physical eali ies a e seamlessly blended, o e ing en iched,
in e ac i e, and accessible expe iences.

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6. Indus ial Imme si e Sys ems o Sys ems In eg a ion
In eg a ing indus ial imme si e sys ems wi h IoT, edge compu ing, AI, and indus ial imme si e
echnologies, such as VR, AR, MR and e ses (e.g., me a e se, omni e se, mul i e se) and Web
4.0 echnologies p esen s a ans o ma i e oppo uni y o indus ies, enabling mo e e icien
ope a ions, enhanced decision-making, and imme si e, in e ac i e expe iences. The
in eg a ion o hese ad anced echnologies in o cohesi e sys ems o sys ems (SoS) aces se e al
signi ican challenges:
In e ope abili y and S anda disa ion
Challenge: Di e en de ices and sys ems o en use p op ie a y p o ocols and da a o ma s,
making seamless communica ion and da a exchange di icul . This lack o in e ope abili y can
hinde he in eg a ion p ocess and limi he po en ial bene i s o a ully connec ed ecosys em.
Impac : Wi hou s anda disa ion, indus ies may ace inc eased cos s and complexi y in
in eg a ing dispa a e sys ems, po en ially leading o siloed in o ma ion, and educed
ope a ional e iciency.
Scalabili y and Flexibili y
Challenge: As he numbe o connec ed de ices g ows, he sys em mus scale wi hou
signi ican pe o mance losses. Addi ionally, he sys em needs he lexibili y o in eg a e new
echnologies and adap o changing ope a ional equi emen s.
Impac : Failu e o add ess scalabili y and lexibili y can esul in ine iciencies o cos ly upg ades.
T us , Da a P i acy and Secu i y
Challenge: In eg a ing IoT, edge compu ing, and AI inc eases he amoun o da a collec ed,
p ocessed, and s o ed, aising signi ican da a p i acy and secu i y conce ns. P o ec ing his
da a agains unau ho ised access and ensu ing compliance wi h egula ions such as GDPR
becomes mo e complex in a highly in e connec ed en i onmen .
Impac : B eaches o non-compliance can esul in signi ican inancial penal ies, loss o
cus ome us , and damage o he company's epu a ion.
Real- ime Da a P ocessing and Decision Making
Challenge: Indus ial imme si e sys ems o en equi e eal- ime o nea - eal- ime da a p ocessing
and decision-making capabili ies. Achie ing his le el o pe o mance, especially in complex
en i onmen s wi h high da a olumes, is challenging.
Impac : Delays in da a p ocessing o decision-making can lead o missed oppo uni ies o
op imisa ion, educed ope a ional e iciency, and po en ially unsa e condi ions in c i ical
indus ial p ocesses.
IoT, Edge Compu ing and AI In as uc u e
Challenge: Implemen ing edge compu ing in as uc u e equi es signi ican in es men in HW,
SW, and in e ope able pla o ms. Addi ionally, managing and main aining his in as uc u e,
especially ac oss dis ibu ed loca ions, can be complex and esou ce-in ensi e.
Impac : Wi h adequa e in es men and managemen , he bene i s o edge compu ing, such
as educed la ency and imp o ed da a p i acy, may be ully ealised, impac ing he o e all
e ec i eness o he in eg a ed sys em.
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AI Model Accu acy and T us wo hiness
Challenge: De eloping obus and bias- ee AI models is di icul , especially when dealing wi h
complex, eal-wo ld da a. Ensu ing hese models can ope a e e ec i ely e hically, and sa ely
(wi hou causing any ha ms o human) in an indus ial con ex is a signi ican challenge.
Impac : Inaccu a e o biased AI models can lead o inco ec decisions, ine iciencies, and
po en ial ha m, unde mining us in he sys em and limi ing i s e ec i eness.
Use Accep ance, Adop ion and T aining
Challenge: The success o in eg a ed sys ems also depends on use accep ance and he
a ailabili y o aining. Use s need o us he echnology and unde s and how o in e ac
e ec i ely.
Impac : Use esis ance o a lack o p ope aining can hinde he adop ion and e ec i e use
o in eg a ed sys ems, educing hei po en ial bene i s.
The in eg a ion o IoT, edge compu ing, and AI in o indus ial imme si e sys ems o sys ems
p esen s a p omising u u e o indus ies. O e coming challenges ela ed o in e ope abili y,
scalabili y, p i acy, eal- ime p ocessing, in as uc u e, AI accu acy, and use accep ance is
c ucial o ealising he ull po en ial o hese echnologies. Add essing hese challenges equi es
a collabo a i e e o among echnology p o ide s, indus y s akeholde s, and egula o y bodies
o de elop s anda ds, bes p ac ices, and inno a i e solu ions ha pa e he way o success ul
in eg a ion and adop ion.
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7. Indus ial Imme si e T us wo hiness
C ea ing a us wo hy amewo k o IoT, edge compu ing, AI, and indus ial imme si e
echnologies, such as VR, AR, MR and e ses (e.g., me a e se, omni e se, mul i e se), equi es
a comp ehensi e app oach in eg a ing sys em enginee ing dependabili y p inciples.
Dependabili y in his con ex encompasses a ibu es such as a ailabili y, eliabili y, sa e y,
in eg i y, and main ainabili y, which a e c i ical o indus ial applica ions whe e e o s o
down imes can lead o signi ican isks o losses. These p inciples can be applied o build a
us wo hy amewo k o indus ial imme si e echnologies by conside ing sys em p ope ies
implemen ed o speci ic imme si e echnologies and applica ions.
A ailabili y equi es implemen ing indus ial imme si e edundan solu ions wi h edundan HW
and SW sys ems o ensu e ha i one componen ails, ano he can ake o e wi hou dis up ing
he imme si e expe ience. This is c ucial in indus ial se ings whe e down ime can be cos ly. This
implies a obus ne wo k in as uc u e ha ensu es a obus , eliable, in elligen connec i i y ha
can suppo imme si e applica ions seamless and con inuous ope a ion, including p o isions o
ne wo k ailu es.
Reliabili y equi es aul ole ance o be embedded in he imme si e sys em design, allowing he
sys em o con inue ope a ion e en in he p esence o aul s. This includes e o de ec ion and
co ec ion mechanisms ha can iden i y and mi iga e issues wi hou in e up ing he use
expe ience. This implies he use o mechanisms o a s uc u ed au oma ed upg adabili y and
upda abili y app oach, allowing egula SW/ i mwa e/algo i hms upda es and pa ches o
add ess ulne abili ies and bugs and imp o e sys em pe o mance, ensu ing he eliabili y o he
imme si e echnology, bu also a subs an ial imp o emen o he cu en sensing echnologies
being mo e accu a e, eliable, cos wo hy in e o de ec ion.
Sa e y equi es con inuous isk assessmen and mi iga ion o iden i y po en ial sa e y haza ds
when using imme si e echnologies in indus ial en i onmen s. To add ess hese isks, i is c i ical
o de elop and implemen mi iga ion s a egies and p o ide comp ehensi e use aining and
clea guidelines on he sa e use o imme si e echnologies, including measu es o p e en
physical and psychological ha m.
Secu i y and da a in eg i y equi e da a enc yp ion and secu i y p o ocols o p o ec sensi i e
in o ma ion ansmi ed o s o ed by imme si e sys ems, ensu ing da a in eg i y and
con iden iali y. Au hen ica ion and access con ol mechanisms a e i al in indus ial-edge
imme si e echnologies o p e en unau ho ised access o imme si e sys ems, ensu ing ha only
au ho ised pe sonnel can use o modi y he sys em.
Main ainabili y equi es using modula design app oaches ha allow o easy eplacemen o
upg ading o componen s wi hou a ec ing he o e all sys em ope a ion. This acili a es quicke
epai s and upda es, enhancing sys em main ainabili y. As imme si e echnologies ope a e
online and in e ac wi h each o he emo ely and ia he In e ne , emo e diagnos ics and
suppo capabili ies a e manda o y o enable imely iden i ica ion and esolu ion o issues,
minimising he need o on-si e main enance and educing down ime.
Usabili y is based on he use -cen ed design p inciple o ensu e ha imme si e echnologies'
design ocuses on use needs and e gonomics, making sys ems in ui i e and s aigh o wa d o
use, which is essen ial o adop ion and e ec i eness in indus ial se ings. This app oach equi es
he implemen a ion o eedback mechanisms o collec ing use eedback on he sys em's
pe o mance and usabili y, allowing o con inuous imp o emen based on eal-wo ld use.
E hical conside a ions ela ed o p i acy p o ec ion mus be en o ced by implemen ing
measu es o p o ec pe sonal and sensi i e da a collec ed o used by imme si e echnologies.
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This has o be combined wi h p ac ices ha include anspa ency and accoun abili y abou
imme si e echnologies' capabili ies, limi a ions, and use o da a, ensu ing accoun abili y o
hei pe o mance and impac .
C ea ing a us wo hy amewo k o indus ial imme si e echnologies in ol es a holis ic
app oach ha in eg a es sys em enginee ing dependabili y p inciples wi h conside a ions o
usabili y, including explainabili y and in e p e abili y mechanisms o AI-based models, e hical
issues, and he speci ic needs o indus ial en i onmen s. By add essing hese aspec s,
o ganisa ions can de elop and deploy imme si e echnologies ha a e e ec i e, engaging,
eliable, sa e, and us wo hy.
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High-quali y, obus , eliable, and a o dable imme si e echnologies: De elopmen o
in eg a ed and minia u ised semiconduc o s, IoT de ices, edge p ocessing, and AI/ML
echnologies o implemen ing in elligen IIoT imme si e echnologies.
In eg a ion o imme si e echnology: De elopmen o sys em-o -sys ems concep s,
app oaches, and amewo ks o in eg a ing edge IoT indus ial imme si e echnologies and
he spa ial compu ing con inuum wi h exis ing sys ems in a ious indus ies. De elopmen o
web-based 3D imme si e solu ions o enhance digi al expe iences on web-based pla o ms
ha elimina e he need o app downloads, p o iding immedia e and uni e sal access on
a ious de ices.
In e ope abili y and S anda disa ion: Wi h a as a ay o edge IoT imme si e de ices,
pla o ms, and echnologies, ensu ing in e ope abili y among di e en sys ems is a signi ican
challenge. S anda disa ion e o s a e c ucial o enable seamless communica ion and
in eg a ion ac oss de ices and pla o ms. Especially he in e lock and syne gy be ween he
se e al SDOs in ol ed in he imme si e echnology domain calls o a join wo ld-wide e o
in deli e ing aligned and non-con o e sial echnical speci ica ions manda ed by he
di e en Wo k G oups.
Da a P i acy and Secu i y: While edge compu ing can enhance da a p i acy, he
inc eased dis ibu ion o da a p ocessing poin s expands he a ack su ace o po en ial
b eaches. Ensu ing obus secu i y measu es ha can ope a e e ec i ely in decen alised
en i onmen s is essen ial.
Scalabili y: As he numbe o connec ed edge IoT imme si e de ices and he olume o
da a hey gene a e g ow, de eloping scalable solu ions ha can handle his inc ease
e icien ly wi hou comp omising pe o mance is a signi ican challenge.
Complexi y in Deploymen and Managemen : The con e gence o hese echnologies
inc eases he complexi y o deploying and managing ully imme si e sys ems. New skill se s
and knowledge a e needed o implemen and main ain hese in eg a ed sys ems
e ec i ely.
E hical and Socie al Implica ions: The widesp ead adop ion o imme si e echnologies aises
e hical ques ions conce ning p i acy, su eillance, and he po en ial displacemen o jobs
due o au oma ion and AI/ML in oduc ion. This is also a conce n as he mo e sophis ica ed
he HMDs ge he mo e bioda a hey will collec , e en eaching he poin o p i a e medical
da a. Add essing hese conce ns equi es ca e ul conside a ion and he de elopmen o
e hical guidelines and policies. Eu opean egula ions play a pi o al ole in his ega d and
mus ollow close he ad ancemen o he echnology in he ield o imme si e echnologies.
In e disciplina y In eg a ion: The de elopmen o imme si e echnologies equi es
engagemen in in e disciplina y ac i i ies ha demand compa ing disciplines,
unde s anding disciplines, and hinking be ween disciplines o s imula e he co-c ea ion o
solu ion-o ien ed ans e able knowledge. The imme si e echnology design ocuses on
in eg a ed esea ch h ough mul idisciplina y g oup wo k o expe s and non-expe s
in e connec ed in o a ansdisciplina y amewo k, as he imme si e concep is a
mul idimensional complex o disciplina y in e ela ions ha equi e lea ning o hink a he
in e aces be ween disciplines.
Collabo a ion Ac oss he Technology Spec um: IoT, connec i i y, compu ing, and AI a e
con e ging, and s akeholde s in di e en segmen s o he alue chain need o wo k
oge he , including chip manu ac u e s, supply chain p o ide s, IoT and elec onic
communica ions ne wo k equipmen p o ide s, AI solu ions de elope s, edge, cloud se ice
p o ide s, and imme si e applica ions p o ide s.

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10. Conclusions
The con e gence o IoT, edge compu ing, AI, and indus ial imme si e echnologies holds g ea
p omise o ans o ming indus ies and enhancing human capabili ies. Howe e , ealising his
po en ial equi es o e coming signi ican challenges, including in e ope abili y, p i acy, ene gy
consump ion, secu i y, legal and e hical conside a ions.
Success in his endea ou depends on collabo a i e e o s among esea ch communi ies,
echnologis s, indus y leade s, s anda disa ion bodies, policymake s, and he b oade socie y
o de elop inno a i e solu ions and amewo ks ha can e ec i ely add ess hese challenges
while maximising he bene i s o hese con e ging imme si e echnologies.
Concen a ed and aligned e o s in echnological de elopmen , o ches a ion,
s anda disa ion, in e ope abili y, and esea ch a he Eu opean le el a e needed o o e come
he challenges and use he oppo uni ies ha a ise om he con e gence o IoT, edge
compu ing, AI, and indus ial imme si e echnologies.
The con e gence and usion o echnologies such as IoT, AI, in elligen connec i i y wi h DTs,
imme si e iple s, and cloud da a exchange acili a e he de elopmen and deploymen o
VR, AR, MR, XR, and a ious e ses (me a e se, omni e se, mul i e se), inhe en ly equi e a highly
in e disciplina y app oach. The mul idisciplina y na u e o hese echnologies in ol es mul iple
ields, such as compu e science, elec ical enginee ing, da a science, use expe ience design,
cogni i e science, and mo e.
The sys ems-o -sys ems in eg a ion o hese echnologies signi ies a echnological shi , as well as
a cul u al and economic one, po en ially al e ing how we pe cei e and in e ac wi h he digi al
and physical wo lds. This con e gence p omises a mo e in eg a ed, imme si e, and in e ac i e
u u e.
Technological Syne gy: The con e gence o IoT, AI, in elligen connec i i y, and imme si e
echnologies such as VR, AR, MR, and XR a he edge, combined wi h DTs and imme si e iple s,
c ea es a powe ul pla o m o inno a ion in indus ial applica ions. This syne gy acili a es
ad anced simula ions, eal- ime ope a ions, and enhanced use in e ac ions, d i ing o wa d
he concep o he indus ial e ses.
Eu opean Indus ial Leade ship: Eu opean leade ship in sec o s such as au omo i e, ae ospace,
manu ac u ing, ene gy, and heal h p o ides a solid ounda ion o he adop ion and in eg a ion
o hese con e ging echnologies. This exis ing indus ial base can pionee he de elopmen o
sys ems-o -sys ems in eg a ion c ucial o ealizing indus ial e ses.
Ma u i y o he Indus ial Me a e se: The indus ial me a e se is cu en ly mo e ad anced han
i s consume coun e pa s, p ima ily due o he highe eadiness and immedia e applicabili y o
DTs and AI in indus ial se ings. This ma u i y o e s a s a egic ad an age in deploying hese
echnologies mo e apidly and e ec i ely.
Gene a i e and Con ex ual Technologies: The ole o nex -gene a ion IoT and gene a i e AI in
c ea ing con ex -awa e, dynamically adap i e indus ial en i onmen s is signi ican . These
echnologies allow o mo e sophis ica ed and ailo ed imme si e expe iences, enhancing
ope a ional e iciency and decision-making p ocesses.
In es in Resea ch and De elopmen : Encou age and und esea ch and inno a ion p ojec s
in eg a ing AI, IoT, DTs, imme si e iple s, in elligen connec i i y, and imme si e echnologies.
This in es men should sol e speci ic indus ial challenges and push he bounda ies o wha 's
cu en ly possible in imme si e asse s accu acy and eal- ime da a analy ics.
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Alloca e signi ican esou ces owa ds esea ch and de elopmen o con inuously ad ance he
capabili ies o edge IoT and imme si e echnologies. This should include he explo a ion o new
ma e ials, senso s, algo i hms, and use in e aces.
P omo e S anda ds and In e ope abili y: De elop and p omo e indus y-wide s anda ds o
ensu e in e ope abili y among di e en echnologies and pla o ms. This will acili a e sys ems-
o -sys ems in eg a ion and allow seamless in e ac ions be ween a ious componen s o he
indus ial me a e se. Align he ac i i ies wi h he egula ions and equi emen s in he Eu opean
Da a, AI, Cybe secu i y and Chips Ac s.
Implemen Pilo P ojec s and Scalabili y Tes s: Encou age he de elopmen o a Eu opean
amewo k o add ess he e i ica ion, alida ion and es ing o AI-based imme si e
echnologies. Launch pilo p ojec s wi hin key indus ial sec o s o es he easibili y and
e ec i eness o hese echnologies. E alua e pe o mance, ga he use eedback, and scale
success ul p ac ices ac oss o he sec o s and ma ke s.
S imula e Regula o y and Policy Suppo : Wo k closely wi h egula o y bodies o c ea e
guidelines ha suppo he deploymen o he imme si e edge IoT, AI, DTs, IMTs, in elligen
connec i i y, IoTS, SDA, spa ial compu ing e ses and Web 4.0, while ensu ing sa e y and e hical
conside a ions. P omo e policies ha encou age he adop ion o nex -gene a ion echnologies
in indus ial se ings.
Ex end Public-P i a e Pa ne ships: Es ablish pa ne ships be ween public au ho i ies, esea ch,
academic ins i u ions, and indus y leade s. These collabo a ions can accele a e echnology
ans e , scale inno a ions, and align s a egic in e es s ac oss sec o s.
Enhance Skills and Educa ion: Implemen aining p og ams and upda e educa ional cu icula
o include skills ele an o eme ging echnologies like AI, IoT, and imme si e echnologies.
P epa ing a wo k o ce adep a na iga ing and op imising hese echnologies is c ucial.
S eng hen In e disciplina y Collabo a ion: Fos e collabo a ion and coo dina ion be ween
Eu opean pa ne ships and ini ia i es o enhance he in e disciplina y exchange o knowledge
and o spu inno a ion in edge IoT and imme si e echnologies. Es ablish join ask o ces o
inno a ion clus e s whe e hese collabo a ions can h i e.
Enhance IoT and Edge Compu ing, HW, SW, AI Technology S ack and Da a In eg a ion: In es in
de eloping obus HW, AI, da a, and da a se s ha can wi hs and indus ial en i onmen s and
e icien ly suppo imme si e echnologies. Pa allelly, p omo e SDA o allow lexible, scalable,
and cos -e ec i e solu ions.
Imp o e Wo k low In eg a ion: Design in eg a ion p o ocols and ools ha enable seamless
embedding o IoT and imme si e echnologies in o exis ing indus ial wo k lows o suppo he
in eg a ion o sys ems o -sys ems o imme si e applica ions. P o ide modula solu ions ha can
be cus omised o di e en indus ial needs o minimise dis up ion and enhance adop ion.
C ea e In e disciplina y p ojec s: Es ablish dedica ed esea ch and inno a ion p ojec s ocused
on he con e gence o hese echnologies. These p ojec s can se e as e e ences o
in e disciplina y inno a ion, b inging oge he expe s om a ious ields o ocus on sha ed goals
and challenges in indus ial imme si e echnologies and applica ions ac oss indus ial sec o s
and pla o ms. By c ea ing hese p ojec s, collabo a i e e o s can be s eamlined and mo e
e ec i ely di ec ed owa ds inno a i e solu ions ha span mul iple indus ies and disciplines. This
will ul ima ely enhance he de elopmen and deploymen o in eg a ed echnologies in he
ealm o IoT, AI, and imme si e en i onmen s.
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Secu e Da a and P o ec P i acy by P o iding a T us wo hy F amewo k o Imme si e
Technologies De elopmen : Implemen ad anced dependable measu es ailo ed o he
imme si e edge compu ing en i onmen o p o ec sensi i e indus ial da a and p o ide
us wo hy design and ope a ion mechanisms o indus ial imme si e applica ions. Adop us -
p ese ing echnologies, o ensu e ha da a exploi a ion does no comp omise sys em
obus ness, eliabili y, scalabili y, in e ope abili y, secu i y, sa e y, and eliabili y.
Es ablish Collabo a i e Pla o ms: C ea e pla o ms whe e p o essionals om di e en disciplines
can mee , sha e ideas, and collabo a e on p ojec s. This could be h ough egula
in e disciplina y wo kshops, semina s, and join esea ch ini ia i es.
Fos e Academic and Indus y Pa ne ships: Encou age pa ne ships be ween academia and
indus y o combine heo e ical knowledge wi h p ac ical applica ions. These pa ne ships can
p o ide mu ual bene i s—academics gain insigh in o eal-wo ld challenges, and indus y
playe s access cu ing-edge esea ch.
Secu e Digi al and Connec i i y In as uc u e: As eliance on in e connec ed echnologies
g ows, obus cybe secu i y measu es a e essen ial. De elop secu e connec i i y in as uc u e
and p o ocols o p o ec sensi i e indus ial da a and main ain ope a ional in eg i y agains
h ea s. Upg ade ne wo k in as uc u e o suppo high-speed, low-la ency communica ions
essen ial o imme si e and edge compu ing applica ions including he expansion o 5G/6G
ne wo ks and ad anced Wi-Fi echnologies.
Suppo S a ups and Inno a ion: Encou age s a ups by p o iding inancial, echnical, and
men o ship suppo . S a ups o en d i e inno a ion in cu ing-edge imme si e echnologies, and
hei agile na u e enables apid adap a ion and de elopmen o no el solu ions.
Du ing he nex decade Eu opean indus ies can e ec i ely le e age he con e gence o edge
IoT, AI, and imme si e echnologies o ans o m indus ial ope a ions, enhancing e iciency,
sa e y, and decision-making capabili ies while os e ing a compe i i e edge in he global
ma ke .
By add essing and adop ing hese ecommenda ions, Eu opean indus ial sec o s can enhance
hei global compe i i eness and lead in de eloping and applying sus ainable, cu ing-edge
echnologies wi hin he indus ial imme si e echnologies and applica ions, os e ing g ow h and
inno a ion in a apidly e ol ing win digi al and g een physical and i ual landscape.
This posi ion pape on edge IoT indus ial imme si e echnologies will be ollowed by a new
posi ion pape on edge IoT indus ial imme si e applica ions ac oss indus ial sec o s, which is
planned o be eleased in he au umn o 2024.
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Con ibu o s
Edi o s:
O idiu Ve mesan, SINTEF
Vale io F ascolla, In el
Re iewe :
Dami Filipo ic, AIOTI Sec e a y Gene al
Con ibu o s (alphabe ic o de ):
Alain Pagani, Ge man Resea ch Cen e o A i icial In elligence, Ge many
Albena Miho ska, Resea ch and De elopmen and Inno a ion Conso ium, Bulga ia
Bjö n Debaillie, imec, Belgium
Cian O Mu chu, Tyndall Na ional Ins i u e, I eland
Daniela Buleand a, SIMAVI, Romania
F ancesco Chinello, Aa hus Uni e si y, Denma k
F ançois Fische , FSCOM, F ance
Geo ge Suciu, BEIA Consul In e na ional SRL, Romania
Ignacio Lacalle, Uni e si a Poli ecnica de Valencia, Spain
Ilia Pie i, In acom Telecom Solu ions, G eece
Jesus Angel Ga cia Sanchez, Ind a Sis emas
Joachim Hilleb and, Vi ual Vehicle Resea ch, Aus ia
Kons an inos Koumadi is, Aa hus Uni e si y, Denma k
Ma in Se ano, Insigh SFI esea ch Cen e o Da a Analy ics, I eland
Ma hias Ha mann, imec, Belgium
Monica Flo ea, SIMAVI, Romania
Mi ko P esse , Aa hus Uni e si y, Denma k
Na alie Samo ich, Ene cou im, Po ugal
O idiu Ve mesan, SINTEF, No way
Philippe Sayegh, VERSES, The Ne he lands
Pie e Y es Dane , 48deg79min-Consul ing, F ance
Ranga Rao Venka esha P asad, Technical Uni e si y Del , Ne he lands
Ronald Maandonks, Signi y, The Ne he lands
Roumen Nikolo , Vi ech, Bulga ia
Roy Bah , SINTEF, No way
Se gio Gusme oli, Poli ecnico di Milano, I aly
Udayan o Dwi A mojo, Aal o Uni e si y, Finland
Vale io F ascolla, In el, Ge many
Vasileios Ka agiannis, Aus ian Ins i u e o Technology, Aus ia
Ve onica Quin una Rod iguez, O ange, F ance
Vladimi Poulko , Technical Uni e si y o So ia, Bulga ia
© AIOTI. All igh s ese ed.
70
Acknowledgemen s
All igh s ese ed, Alliance o IoT and Edge Compu ing Inno a ion (AIOTI). The con en o his
documen is p o ided ‘as-is’ and o gene al in o ma ion pu poses only; i does no cons i u e
s a egic o any o he p o essional ad ice. The con en o pa s he eo may no be comple e,
accu a e o up o da e. No wi hs anding any hing con ained in his documen , AIOTI disclaims
esponsibili y (including whe e AIOTI o any o i s o ice s, membe s o con ac o s ha e been
negligen ) o any di ec o indi ec loss, damage, claim, o liabili y any pe son, company,
o ganisa ion o o he en i y o body may incu as a esul , his o he maximum ex en pe mi ed
by law.
This pape was p epa ed by i s au ho (s) and con ibu o (s) in hei pe sonal capaci y. The
opinions exp essed in his pape a e he indi idual au ho (s) and con ibu o (s) own and do no
e lec he iew o AIOTI o i s membe s. The s a emen s, opinions and da a con ained in his
pape and he p esen a ion o ma e ials he ein do no imply he exp ession o any opinion
wha soe e by AIOTI o i s membe s. AIOTI hold no esponsibili y o any b each o damage o
people o p ope y esul ing om any ideas, me hods, ins uc ions, o p oduc s e e ed o in his
pape .
© AIOTI. All igh s ese ed.
71
Abou AIOTI
AIOTI is he mul i-s akeholde pla o m o s imula ing IoT and Edge Compu ing Inno a ion in
Eu ope, b inging oge he small and la ge companies, academia, policy make s and end-use s
and ep esen a i es o socie y in an end- o-end app oach. We wo k wi h pa ne s in a global
con ex . We s i e o le e age, sha e, and p omo e bes p ac ices in he IoT and Edge
Compu ing ecosys ems, be a one-s op poin o in o ma ion on all ele an aspec s o IoT
Inno a ion o i s membe s while p oac i ely add essing key issues and oadblocks o economic
g ow h, accep ance, and adop ion o IoT and Edge Compu ing Inno a ion in socie y. AIOTI’s
con ibu ion goes beyond echnology and add esses ho izon al elemen s ac oss applica ion
domains, such as ma chmaking and s imula ing coope a ion in IoT and Edge Compu ing
ecosys ems, c ea ing join esea ch oadmaps, d i ing con e gence o s anda ds and
in e ope abili y, and de ining policies.