Moni o ing o  he daily li ing ac i i ies
insma home ca e
Jan Vanus1* , Jana Beleso a1, Radek Ma inek1, Jan Nedoma2, Ma cel Fajkus2, Pe Bilik1 and Jan Zidek1
Abs ac
One o he key equi emen s o echnological sys ems ha a e used o secu e inde-
penden housing o senio s in hei home en i onmen is moni o ing o daily li ing
ac i i ies (ADL), hei classi ica ion, and ecogni ion o ou ine daily pa e ns and habi s
o senio s in Sma Home Ca e (SHC). To moni o daily li ing ac i i ies, he use o a
empe a u e, CO2, humidi y senso s, and mic ophones a e desc ibed in expe imen s in
his s udy. The i s pa o he pape desc ibes he use o CO2 concen a ion measu e-
men o de ec ing and moni o ing oom´s occupancy in SHC. In second pa ocuses
his pape on he p oposal o an implemen a ion o A i icial Neu al Ne wo k based
on he Le enbe g–Ma qua d algo i hm (LMA) o he de ec ion o human p esence
in a oom o SHC wi h he use o p edic i e calcula ion o CO2 concen a ions om
ob ained measu emen s o empe a u e (indoo , ou doo ) Ti, To and ela i e ai humid-
i y H. Based on he long- e m moni o ing (1 mon h) o ope a ional and echnical
unc ions (un egula ed, uncon olled) in an expe imen al Sma Home (SH), LMA was
ained h ough he da a picked up by he senso s o CO2, T and H wi h he aim o
indi ec ly p edic CO2 leading o he elimina ion o CO2 senso om he measu emen
p ocess. Wi hin he ealized expe imen , inpu pa ame e s o he neu onal ne wo k and
he numbe o neu ons o LMA we e op imized on he basis o calcula ed alues o
Roo Mean Squa ed E o , he co ela i e coe icien (R) and he leng h o he meas-
u ed aining ime ANN. Wi h he use o he ained ne wo k ANN, we ealized a s ic ly
con olled sho - e m (11 h) expe imen wi hou he use o CO2 senso . Expe imen al
esul s e i ied high me hod accu acy (>95%) wi hin he sho - e m and long- e m
expe imen s o lea ned ANN (1.6.2015–30.6.2015). Fo lea ned ANN (1.2.2014–
27.2.2014) was e i ied wo se me hod accu acy (>60%). The o iginal con ibu ion is
a e i ica ion o a low-cos me hod o he de ec ion o human p esence in he eal
ope a ing en i onmen o SHC. In he hi d pa o he pape is desc ibed he p ac ical
implemen a ion o oice con ol o ope a ing echnical unc ions by he KNX ech-
nology in SHC by means o he in-house de eloped applica ion HESTIA, in ended o
bo h he desk op sys em e sion and he mobile e sion o he Windows 10 ope a ing
sys em o mobile phones. The esul an applica ion can be con igu ed o any build-
ing equipped wi h he KNX bus sys em. Voice con ol implemen a ion is an in-house
solu ion, no hi d-pa y so wa e is used he e. U iliza ion o he oice communica ion
applica ion in SHC was p o en on he expe imen al basis wi h he combina ion o
measu emen CO2 o ADL moni o ing in SHC.
Keywo ds: Voice ecogni ion, Addi i e noise, KNX, ETS, C#, Sma home ca e, Ac i i ies
o daily li ing, Le enbe g–Ma qua d algo i hm, Bland–Al man me hod
Open Access
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RESEARCH
Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
DOI 10.1186/s13673-017-0113-6
*Co espondence:
[email p o ec ed]
1 Depa men o Cybe ne ics
and Biomedical Enginee ing,
Facul y o Elec ical
Enginee ing and Compu e
Science, VSB-Technical
Uni e si y Os a a, 17.
lis opadu 15, 708 33, Os a a
Po uba, Czech Republic
Full lis o au ho in o ma ion
is a ailable a he end o he
a icle
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
In oduc ion
Moni o ing he ac i i ies o daily li ing (ADLs) and de ec ion o de ia ions om p e i-
ous pa e ns is c ucial o assessing he abili y o an elde ly pe son o li e independen ly
in hei communi y and in ea ly de ec ion o upcoming c i ical si ua ions. “Aging in
place” o an elde ly pe son is one key elemen in ambien assis ed li ing (AAL) ech-
nologies [1]. Fo ecogni ion [2–15] and classi ica ion o ADL [16, 17] a e used a ious
ma hema ical me hods such as Hidden Ma ko Model (HMM), Linea Disc iminan
Analysis (LDA) and Suppo Vec o Machines (SVM) [18, 6], A i icial Neu al Ne wo ks
(ANN) [11] o adap i e-ne wo k-based uzzy in e ence sys em (ANFIS) [19, 20]. Fo
de ec ion o ADL in SHC i is possible o use RFID [21], PIR [22], CO2 [23] senso s o
p esence senso s, on he basis o which p obabili y models o he people’s beha io in SH
[24] can be buil , espec ing he p i acy [25] o SHC esiden s [26]. One o he ways o
pe o ming he ADL is mo ion de ec ion [27, 28] and alls o senio s [29, 30] which may
end agically in he case o la e in e en ion. The e o e, i is necessa y o design such a
echnology solu ion sys em ha will allow a ange o se ices including da a collec ion
and analysis o long- e m ends in beha io s and physiological pa ame e s (e.g. ela ing
o sleep o daily ac i i y); wa nings, ala ms and eminde s; and social in e ac ion [31].
An example migh be he echnology sys em AAL [32]. The p oposed echnology sys-
ems need o be based on he eal needs o SHC esiden s [1]. Fo he com o and a
eeling o sa e y [33] o he SH esiden s, senso s a e designed o use o ad anced mobile
de ices in di e se scena ios, by de eloping wea able senso s, and by using nume ous
senso s embedded in he en i onmen in SHC [34]. Fo example, Liu in es iga es he
impo ance o spa io empo al easoning and unce ain y easoning in he design o
Sma Homes. Acco dingly, a amewo k o applying a me hodology e e ed as Rule-
based In e ence Me hodology using he E iden ial Reasoning in conjunc ion wi h Sma
Home F amewo k conside ing spa io empo al aspec s o ADL is ou lined [35]. Nou y
sol ed a e y in e es ing way o ADL implemen a ion in SH by de ec ing he ene gy con-
sump ion o he SH [36]. Ano he al e na i e o he e ec i e implemen a ion o ADL
moni o ing can also be used o he IoT concep wi hin he SH inclusion in he concep o
Sma Ci ies [37].
The objec i e o he a icle is o desc ibe and e alua e new app oaches o he echnical
solu ion o moni o ing he p esence o pe sons in indi idual ooms o in elligen build-
ings (IB) (SH, SHC) o de e mine he occupancy o he moni o ed spaces wi h he pos-
sibili y o using he in o ma ion ob ained o de e mine he ADL by exis ing echnology
sys ems ha can be used in he SHC.
The aim o he i s pa o he a icle is he use and p ocessing o in o ma ion om
ope a ionally measu ed non-elec ical quan i ies de e mining he indoo en i onmen
in he SHC using ope a ional echnological uni s o he de e mina ion o he ADL in
a eal-wo ld SHC en i onmen . To ob ain an o e iew o he occupancy o indi idual
ooms o he SHC ( ime o a i al, ime o depa u e, numbe o pe sons), he indi ec
measu emen o CO2 concen a ion (ppm) wi h ope a ional CO2 (ppm) senso s is used.
The aim o he second pa o he a icle is o use ANN o p edic he measu ed
quan i ies o he pu pose o moni o ing he ADL in a eal-wo ld SHC en i onmen . I
desc ibes he p ocess o using he mul ilaye o wa d ANN o p edic he cou se o CO2
concen a ion om he measu ed empe a u e Ti (°C), ela i e humidi y H (%) in he
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
in e io o he SHC in he selec ed oom R104 and om he ou doo empe a u e ead-
ings To (°C), wi h he g adien algo i hm o e o backp opaga ion using he Le enbe g–
Ma qua d (LMA) p edic ion. Fo he classi ica ion o p edic ion quali y, a co ela ion
analysis (co ela ion coe icien R), calcula ed RMSE (Roo Mean Squa ed E o ) and
Mean Absolu e Pe cen age E o (MAPE) and Bland–Al man me hod a e used.
The hi d pa o he a icle aims o connec and es he c ea ed HESTIA applica-
ion o isualiza ion and oice con ol o ope a ional echnical ea u es using eal-wo ld
KNX echnology o de e mine he ADL. As complemen a y in o ma ion o mo e p e-
cise de e mina ion o ac i i ies o SHC inhabi an s, he p esence o pe sons in he SHC
oom is moni o ed using he CO2 senso and he p edic ion o he CO2 cou se om he
measu ed Ti (°C), he ela i e humidi y H (%) in he in e io o he selec ed oom o
he SHC and he measu ed ou doo empe a u e To (°C) using he abo e me hods. The
applica ions desc ibed below may be used o de ec ing ADL in he SHC.
Desc ip ion o  he used echnologies
The Sma wo- loo wooden house (he ea e Sma Home; loo a ea o :
12.1m×8.2m; (Fig.1) was buil as a aining cen e o he Mo a ian-Silesian Wood
Clus e (MSWC). The wooden house (SHC) was buil o a passi e s anda d in acco d-
ance wi h s anda ds ČSN 75 0540-2 and ČSN 730540-2(2002).
Desc ip ion o  he used echnologies
Fo hea ing, cooling and o ced en ila ion, BACne (Building Au oma ion and Con ols
Ne wo k) echnology is used in he SHC. Ligh ing, blinds and mains socke s a e con-
olled by KNX echnology, which is in e connec ed wi h BACne (Fig.2).
Visualiza ion and a chi ing o measu ed alues o non-elec ic quan i ies a e ealized
in he mas e isualiza ion sys em Desigo Insigh , o example measu emen o empe a-
u e, humidi y, CO2 o moni o ing and con ol o he indoo en i onmen o indi idual
Fig. 1 Sma home—wooden house, aining cen e o he Mo a ian-Silesian wood clus e (MSWC)
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
ooms o SHC. To pe o m he e alua ion o he measu ed non-elec ical quan i ies, he
alues o CO2, empe a u e (T) and ela i e humidi y ( H) in selec ed ooms ha e been
chosen and measu ed by means o ai quali y senso QPA 2062. The echnical pa am-
e e s o he senso a e as ollows:
•Tempe a u e indoo Ti, (senso (QPA 2062), (wi hin 0 and 50°C/−35 o 35°C, accu-
acy ±1K) implemen ed in BACne echnology) and Tempe a u e ou doo T0, (sen-
so AP 257/22, measu ing ange −30…+80°C, esolu ion: 0.1°C), implemen ed in
KNX echnology).
•Rela i e humidi y ( H) measu emen (senso (QPA 2062), (wi hin 0 and 100%, accu-
acy±5%), implemen ed in BACne echnology),
•CO2 measu emen (senso (QPA 2062), (wi hin 0 and 2000ppm, accu acy ±50ppm,
implemen ed in BACne echnology).
Fo he ac ual expe imen oom R104 was used (Fig.3) in he SHC.
Fi s pa —use o  CO2 senso s o de e mining he p esence andoccupa ion
o a oom in he SHC
Moni o ing o ADL o occupancy o he SHC ooms se es o mo e accu a ely and
e icien ly egula e he ope a ional- echnical unc ions in he SHC ( educ ion o ope -
a ing cos s and ene gy consump ion, com o o con olling ope a ional echnical unc-
ions in he SHC and objec secu i y) and o indi ec moni o ing o daily ac i i ies o
senio s in o de o p e en bo de line and c i ical si ua ions ( all o an elde ly pe son,
inju y, dea h). In connec ion wi h ADL moni o ing, ca bon dioxide (CO2) concen a-
ions can be used in occupied SHC ooms. The ac ual measu emen o CO2 is p ima ily
pe o med in o de o con ol he quali y o he indoo en i onmen (ai ) in indi idual
SHC ooms, o ensu e hygienic condi ions and o con ol he HVAC in he SHC. Ai
quali y in ooms has a signi ican impac on pe sonal well-being and people’s a en ion.
Fig. 2 Sma Home building—block scheme o he building au oma ion echnology pa (including com-
munica ion modules o he building hea ing echnology pa and he hea s o age echnology pa )
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
Highe CO2 concen a ions lead o p ema u e a igue, while p olonged exposu e may
lead o headaches o o he ailmen s [38]. The concen a ion o CO2 is he mos common
con aminan in indoo building en i onmen s. In in e io s o buildings he e is always
highe concen a ion han ou side. The main sou ce o he inc ease in CO2 concen a-
ion in he in e io o he IB is abo e all human. Du ing b ea hing, oxygen and CO2 a e
exchanged. CO2 p oduc ion is in di ec p opo ion o physical ac i i y. The ca bon diox-
ide concen a ion is gi en in ppm (pa s pe million) [39].
F om he measu ed alues o CO2 concen a ion (Fig.4) in oom R104 i is possible
o de e mine he ime o a i al o depa u e o a pe son o/ om he moni o ed space
(Fig.5). This is based on he assump ion ha i he CO2 inc eases hen he e is a pe son
Fig. 3 G ound loo o he SHC wi h indica ion o he senso s used o measu ing empe a u e, ela i e
humidi y and CO2 in oom R104
Fig. 4 Measu ed wa e o m o CO2 (ppm) in R104 o SHC (1.2.2014–27.2.2014)

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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
p esen (sou ce o CO2). When he pe son lea es he moni o ed space, he inc ease in
CO2 concen a ion:
•s agna es o emains cons an (Fig.5), poin s 2–3, 5–6, 7–8, 15–16, 18–19, 20–21,
24–25; i.e. closed windows, doo s, no o ced en ila ion,
• apid dec ease (Fig.5), poin s 19–20, 23–24), open window o doo s,
•g adually (Fig.5), poin s 4–5, 9–10, 11–12, closed windows, doo s, no o ced en ila-
ion.
I is also possible o de e mine, based on he dispe sion o CO2 concen a ion, he
manne o dispe sion o CO2 in he space o he oom [opening he window, swi ching
on o ced en ila ion, na u al sca e ing o CO2 (ppm)] (Fig.6).
Resul s i s pa
The expe imen s desc ibed abo e (Figs.4, 5, 6) ha e shown ha CO2 can be used o
ADL moni o ing, occupancy de ec ion and classi ica ion o de e mina ion o beha iou
o he occupan s o he SHC, SH o IB. In o ma ion ob ained du ing he measu emen o
CO2 (ppm) can also be used o de e mine he indoo en i onmen quali y o each space
in he SHC, SH o IB.
Discussion
In o ma ion abou he quali y o he in e nal en i onmen in an IB is p o ided by em-
pe a u e senso s (indoo , ou doo ) Ti, To (°C) and ai humidi y senso s H (%). This
in o ma ion is c ucial o he com o and occupancy o sepa a e ooms o IB. The cos
o high-quali y empe a u e and ai humidi y senso s is app oxima ely in he ange o
Fig. 5 Measu ed wa e o m o CO2 (ppm) in R104 o SHC (1.2.2014–27.2.2014). (dd.mm.yyyy hh:mm:ss): 1
a i al (5.2.2017 7:42:00), 2 depa u e (5.2.2017 7:53:00)—closed window, 3 a i al (5.2.2017 8:12:00), 4 depa -
u e (5.2.2017 8:22:00)—closed window, be ween poin s 5 (5.2.2017 8:34:00) and 6 (5.2.2017 8:43:00) s agna-
ion o CO2 concen a ion (ppm), 6 a i al (5.2.2017 8:43:00), 7 depa u e (5.2.2017 8:53:00), 8 a i al (5.2.2017
9:03:00), 9 depa u e (5.2.2017 9:14:00), 10 a i al (5.2.2017 9:24:00), 11 depa u e (5.2.2017 9:34:00), 12 a i al
(5.2.2017 9:44:00), 13 depa u e (5.2.2017 9:55:00), 14 a i al (5.2.2017 10:03:00), 15 depa u e (5.2.2017
10:14:00), 16 (5.2.2017 10:23:00), 17 a i al (5.2.2017 10:35:00), 18 depa u e (5.2.2017 10:54:00), 19 doo s open
(5.2.2017 11:04:00), 20 doo s close (5.2.2017 11:14:00), 21 a i al (5.2.2017 11:24:00), 22 depa u e (5.2.2017
11:34:00), 23 doo s open (5.2.2017 11:44:00), 24 doo s close (5.2.2017 11:54:00) 25 a i al (5.2.2017 12:24:00) 26
depa u e (5.2.2017 12:35:00)
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
Eu o uni s. The cos o senso s o he measu emen o CO2 mo es he p ice a ank
highe o se e al ens o Eu o. In he Czech Republic (CR), he emphasis is placed on he
u iliza ion o a good he mal insula ion o la ge buildings, which can inally p o ide ce -
ain ene gy sa ings. This is ealized o big o ice buildings, schools, hospi als, esiden ial
dwellings, amily houses and blocks o la s. The in e nal en i onmen o econs uc ed
insula ed buildings is con inuously ge ing wo se wi h he inc ease in CO2 concen a-
ions and humidi y H. Many in es o s in he CR do no ake his ac in o accoun . To
dec ease he concen a ion o CO2 in a oom we can easily open a window and a doo , o
o use a o ced en ila ion as he pa o a complex solu ion p o ided by HVAC echnol-
ogy (Hea ing, Ven ila ion and Ai Condi ioning). Rega ding he echnology u iliza ion in
connec ion wi h he au oma iza ion o buildings, i is necessa y o p o ide he measu e-
men o CO2 concen a ion be o e he implemen a ion o HVAC con olled echnology.
Second pa — he op imized a i icial neu al ne wo k model wi hLe enbe g–
Ma qua d algo i hm o de ec ing human p esence inSHC
Di e en ypes o senso s and echnological equipmen wi h ega d o obus ness,
quali y, design, capi al and ope a ing cos s a e used o de e mine he mo emen , loca-
ion and ime o occu ence o pe sons o he pu pose o indi ec ly de e mining he
space occupancy o in elligen buildings IB (adminis a i e buildings, schools, hospi-
als, homes o he elde ly, households), and o op imize he managemen o ope a-
ional and echnical unc ions in IB (ligh ing, blinds, HVAC). To de ec he mo emen
o people o o moni o ing ADL wi hin he building, he PIR mo ion senso s, p es-
ence senso , GPS senso o Sma Phones is possible using (Table1) [40]. Fo bed id-
den pa ien s in hospi als, i is possible o use RFID senso s [41] o ba code labels. To
ob ain addi ional in o ma ion on he occupancy o he indi idual ooms o an IB, he
alues om he ope a ional senso s measu ing he CO2 concen a ion (ppm) can be
measu ed, which a e used o con ol o ced en ila ion in he building. Building hea -
ing, en ila ion, and ai condi ioning (HVAC) sys ems a e conside ed o be a p ime
Fig. 6 Measu ed wa e o m o CO2 (ppm) in R104 o SHC (1.2.2014–27.2.2014). (dd.mm.yyyy hh:mm:ss):
1 a i al (6.2.2017 9:14:00), 2 depa u e (6.2.2017 9:24:00), 3 a i al (6.2.2017 9:34:00), 4 depa u e (6.2.2017
10:45:00), 5 a i al (6.2.2017 11:15:00), 6 depa u e (6.2.2017 12:05:00), 1—open doo s (6.2.2017 13:16:00–
14:07:00), 2 (6.2.2017 14:07:00–8.2. 2017 11:06:00) closed windows and doo s, o ced en ila ion o —na u al
dispe sion o CO2 concen a ion in he space o oom R104
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
ool o ene gy conse a ion due o hei signi ican con ibu ion o comme cial build-
ings’ ene gy consump ion. Fo example, Yang e alua es occupancy modeling using
wel e ambien senso a iables wi h esul s which demons a e ha 20% o gas and
18% o elec ici y could be sa ed e ec i ely i occupancy-based demand- esponse
HVAC con ol is implemen ed in IB [42]. In ene gy e iciency analysis, use beha io
de ec ion ela ed o he dynamic demands o ene gy is a c i ical aspec o suppo -
ing he in elligen con ol scheme o a Building Managemen Sys em. Acco ding o
Zhao, occupancy o anomalous use beha io ends o be igu ed ou om mul iple
ime-se ies eco ds o occupancy [43]. Fo p edic ion and subsequen classi ica ion o
au oma ic human ac i i y ecogni ion (AR), he eg ession me hod o A i ical Neu al
Ne wo ks (ANN), Hidden Ma ko models [43–45] decision ees me hod [46], me h-
ods using Bayesian ne wo ks [47], Condi ional Random Fields (CRF) o a sequen ial
Ma ko Logic Ne wo k (MLN) [48] can be used.
Biswas desc ibed, ha he a i icial neu al ne wo k has eme ged as a key me hod
o add ess he issue o nonlinea i y o building ene gy da a and he obus calcula-
ion o la ge and dynamic da a [49]. Pan aza as used inco po a ing CO2 concen a-
ion as a ac o in p edic i e models may unlock u he op imiza ion oppo uni ies
in con olle applica ions, especially in buildings wi h highly a ied occupancy, such
as ins i u ional buildings wi h he esul s, which sugges ha he e is indeed po en ial
o a leas sho - e m p edic ion using a e y simple iden i ica ion p ocedu e [50].
Leung p esen s an in es iga ion in o he use o occupancy space elec ical powe
demand o mimic occupan s’ ac i i ies in building cooling load p edic ion by in el-
ligen app oach, whe e he e ec o indi idual beha iou on cooling load demand is
less signi ican a building le el han a o ice le el and he p oposed cooling demand
p edic ion app oach is able o p edic daily peak loads sa is ac o y which would be
use ul o sys em dimensioning. [51]. Moon was de eloped empe a u e con ol algo-
i hm o apply a se back empe a u e p edic i ely o he cooling sys em o a esi-
den ial building du ing occupied pe iods by esiden s, whe e Le enbe g-Ma qua
aining me hod was employed o model aining [52]. The pu pose o Mba wo k was
o apply he a i icial neu al ne wo k (ANNs) wi h Le enbe g–Ma qua d algo i hm
o an hou ly p edic ion, 24-672h in ad ance o (IT) and (IH) in buildings ound in
ho humid egion wi h esul s, which es i ied ha ANN can be used o hou ly IT
and IH p edic ion [53]. Using he neu al ne wo k o p edic he ene gy consump ion
o he building esul ed in some sho comings, which we e sol ed o Dinghao’s p o-
posed model (a new algo i hm which combined gene ic algo i hm wi h he Le en-
be g–Ma qua d algo i hm) o quali ied o p edic sho - e m ene gy consump ion
in buildings accu a ely and e icien ly [54], [55]. Yuce p esen s an ANN app oach o
p edic ene gy consump ion and he mal com o le el o an indoo swimming pool
wi h ANN (Le enbe g–Ma qua d algo i hm) based p edic ion app oach o a spe-
ci ic HVAC sys em [56].
Based on he abo e-desc ibed scien i ic wo ks, i was selec ed ANN wi h he Le en-
be g–Ma qua d algo i hm o p edic ion o measu ed wa e o m CO2 om measu ed
empe a u e and ela i e humidi y wa e o ms.
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Table 1 Senso s in he sma home: summa y o main cha ac e is ics ele an oac i i y de ec ion [40]
Senso Measu emen Da a o ma Ad an age Disad an age
Video came as Human ac ions/en i onmen al s a e Image, ideo P ecise in o ma ion P i acy issues, compu a ional expense,
accep abili y issues
Mic ophones Voice de ec ion, o he sounds Audio Ce ain and ich in o ma ion abou sound Implemen a ion di icul y and high compu a-
ion cos , po en ial accep abili y issues
Simple bina y senso s Use –objec in e ac ion de ec ion mo e-
men s and loca ion iden i ica ion Ca ego ical Low-cos , low main enance, easy o ins all
and eplace, inexpensi e, less p i acy-
sensi i i y, minimal compu a ion equi e-
men s
P o ide simple and limi ed in o ma ion o
composi e and mul i-use ac i i y moni o -
ing
RFID Objec and use iden i ica ion Ca ego ical Small size and low cos Reade collision and ag collision, ange
limi ed
Tempe a u e senso , ligh senso , humidi y
senso En i onmen al pa ame e s Time se ies In ui i e moni o ing o en i onmen and
objec s Limi ed in o ma ion o ac i i y moni o ing
Wea able ine ial senso s Accele a ion o ien a ion Time se ies Compac size, low cos , non-in usi eness,
high accu acy, unique iden i ica ion o
use s, use ’s loca ion easily acked.
Cumbe some and uncom o able eeling,
canno p o ide su icien con ex in o ma-
ion
Wea able i al signs senso s Vi al signs Analog signal Sensi i e o sligh change in i al signs
moni o ing mo e accu a e in eme gency
si ua ion de ec ing
Reliabili y cons ain s, secu i y issues and
uncom o able eeling o long- ime skin
a aching
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closed windows and doo s du ing 1 ime pe iod, swi ched o ai -condi ioning and hea -
ing, p ecisely de ined coming and p esence in he oom 1(s) and lea ing 3(s) o subjec s,
e c. (Fig.11).
In o de o compa e he di e ences be ween he e e ence and p edic ed signal, he
Bland–Al man plo was u ilized [63]. The di e ences be ween he p edic ed signal and
he e e ence aces, x1–x2, a e plo ed agains he a e age, (x1+x2)/2. The ep oduci-
bili y is conside ed o be good i 95% o he esul s lie wi hin a±1.96 SD (s anda d de ia-
ion) ange.
Figu e12 shows he Bland–Al man g aph o he e i ica ion o p edic ion quali y
ANN LMA (600) neu ons in he long- e m expe imen (Fig.10), (4 June 2015–18 June
2015). Fo he en i e da a se , 98.06% o he alues lie wi hin he ±1.96 SD ange o he
de e mina ion o human de ec ion.
Fig. 10 Long- e m expe imen . A The measu emen o CO2 concen a ion in a oom o SHC—ZOOM (1
coming, 2 lea ing, 3 coming, 4 lea ing, 5 coming, 6 lea ing, 7 coming, 8 lea ing), B p edic ion e o du ing
ansien phase—coming o a subjec in o SHC, C coming o a subjec in o he oom o SHC, D p edic ion
e o du ing he ansien phase—coming o a subjec in o SHC, E lea ing o a subjec om a oom o SHC,
F coming o a subjec in o a oom o SHC, G lea ing o subjec s om a oom o SHC, H coming, I lea ing).
Figu e 12 shows he p edic ion and measu ed concen a ion o CO2 (ppm) wi hin he sho - e m expe imen
(16 June 2015)
Fig. 11 Sho - e m expe imen . 1(s)— ime o subjec s’ s ay in a pa icula oom o SHC, 2(s)— ime o he
measu emen o CO2 concen a ion in a pa icula oom o SHC, 3(s)— ime wi hou a p esence o subjec s
in a oom—dispe sion o CO2 concen a ion in a oom o SHC wi h a closed window and swi ched o o ced
en ila ion, A he ansien phase o a p edic ion a he momen o subjec ´s coming in o a oom o SHC, B
he ansien phase o a p edic ion a he momen o subjec s´ lea ing om a oom o SHC, C dispe sion o
CO2 when a oom is emp y. Table 2 shows calcula ed alues o RMSE pa ame e s and R T aining and meas-
u ed ime o lea ning ANN o a con igu ed numbe o neu ons ANN LMA o he ime pe iod 1 June o 30
June 2015

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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
The esul o he Bland–Al man g aph in Fig.13 shows a highe numbe o ou lying
measu emen s in in e als om 600 o 800 (ppm) and pa ially in he in e al om 1300
o 1400 (ppm), which is caused by changes ( ansien phases) wi hin p edic ions in con-
nec ion wi h he coming and lea ing o a subjec in o a oom o SHC. The majo i y o
alues a e shown in he in e al om 500 o 600 (ppm), which demons a es he absence
o subjec s in a moni o ed space. Figu e13 shows he Bland–Al man g aph o he e i-
ica ion o p edic ion quali y o ANN LMA (600) neu ons in he sho - e m expe imen
(Fig.11), (16 June 2015). Fo he en i e da a se , 96.00% o he alues lie wi hin he±1.96
SD ange o he de e mina ion o human de ec ion.
Resul s wi hANN (1.2.2014–27.2. 2014)
Table3 shows he calcula ed alues o MAPE, RMSE and R o p edic ed cou ses o
CO2 on ained ANN LMA (1.6.2015–30.6.2015) o neu on coun s in ange 10–700.
Compa ison wi h Table2 con i ms ha he bes calcula ed pa ame e s MAPE (81.52%),
RMSE (0.0165), R coe icien (0.96), (Table3) o p edic ed cou ses o CO2 a e o
ained ANN LMA wi h 600 neu ons.
Table4 shows he measu ed and calcula ed alues o MSE, co ela ion coe icien R,
ime (s) o lea ning p ocess o ANN LMA ( o neu on coun s in he ange 10–700)
o measu ed alues Ti, T0, H and CO2 in oom R104 o he SHC in he pe iod
1.2.2014–27.2.2014. ANN LMA exhibi ed he bes lea ning pa ame e s o 500 neu ons
(MSE=6.188.10–4, R=0.950).
Table5 shows he calcula ed alues o MAPE, RMSE and R o p edic ed cou ses o
CO2 on ained ANN LMA (1.6.2015–30.6.2015) o neu on coun s in ange 10–700.
Fig. 12 The Bland–Al man g aph— he long- e m expe imen
Fig. 13 The Bland–Al man g aph— he sho - e m expe imen
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
Compa ison wi h Table 4 con i med ha he bes calcula ed pa ame e s o MAPE
(70.89%), RMSE (0.025), R coe icien (0.95), (Table5) o p edic ed cou ses o CO2 a e
o ained ANN LMA wi h 500 neu ons.
Resul s— es ing o ANN LMA
Fo ained ANN LMA in he pe iod 1.6.2015–30.6.2015 (Table2) we used he meas-
u ed da a in he pe iod 16.6.2015 (6:40–23:18), (1000 samples) o es ing wi hin a sho
expe imen . The esul s a e in Table6.
Table 3 Compa ison o p edic ion quali y ANN (LMA) [1.6.2015–30.6.2015 (da a no mal-
ized)], wi h es ed da a omin e al [1.6.2015–30.6.2015 (da a no malized)]
Numbe o neu ons (−) RMSE aining (ppm) R aining (−)
10 0.033 0.8
50 0.028 0.87
100 0.023 0.91
150 0.023 0.91
200 0.02 0.93
250 0.018 0.95
300 0.022 0.92
350 0.019 0.94
400 0.0168 0.96
450 0.017 0.96
500 0.019 0.95
550 0.018 0.95
600 0.0165 0.96
650 0.018 0.95
700 0.017 0.96
Table 4 Compa ison o  lea ning quali y ANN (LMA) [1.2.2014–27.2.2014 (da a no mal-
ized)]
Numbe o neu ons (−) Time (hh:mm:ss) MSE aining (ppm) R aining (−)
10 0:00:46 2.219 × 10−30.79
50 0:06:48 1.183 × 10−30.90
100 0:05:24 1.144 × 10−30.90
150 0:56:29 7.762 × 10−40.93
200 0:24:45 8.406 × 10−40.93
250 0:21:47 8.487 × 10−40.93
300 0:35:36 7.185 × 10−40.94
350 0:45:14 6.739 × 10−40.94
400 1:09:55 6.811 × 10−40.94
450 1:06:52 7.256 × 10−40.94
500 1:32:14 6.188 × 10−40.95
550 0:18:42 9.006 × 10−40.92
600 1:09:26 6.761 × 10−40.94
650 0:31:09 7.525 × 10−40.94
700 0:58:46 7.307 × 10−40.94
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Compa ison wi h Table2 shows ha o calcula ed pa ame e s RMSE (0.02), R coe -
icien (0.93), (Table6) o p edic ed cou ses o CO2 a e he bes o ained ANN LMA
(in he pe iod 1.6.2015–30.6.2015) wi h 500 neu ons.
Fo ained ANN LMA in he pe iod 1.2.2014–27.2.2014 (Table3) we used he meas-
u ed da a in he pe iod 18.2.2014 (7:00–23:40), (1000 samples) o es ing wi hin a sho
expe imen . The esul s a e in Table7.
Compa ison wi h Table4 shows ha o calcula ed pa ame e s RMSE (0.049), R coe -
icien (0.67), (Table7) o p edic ed cou ses o CO2 a e he bes o ained ANN LMA
(in he pe iod 1.2.2014–27.2.2014) wi h 300 neu ons.
Table 5 Compa ison o p edic ion quali y ANN (LMA) [1.2.2014–27.2.2014 (da a no mal-
ized)] wi h es ed da a omin e al [1.2.2014–27.2.2014 (da a no malized)]
Numbe o neu ons (−) RMSE aining (ppm) R aining (−)
10 0.047 0.80
50 0.034 0.90
100 0.033 0.90
150 0.028 0.93
200 0.029 0.93
250 0.029 0.93
300 0.028 0.93
350 0.025 0.95
400 0.026 0.94
450 0.027 0.94
500 0.025 0.95
550 0.030 0.92
600 0.026 0.94
650 0.028 0.94
700 0.027 0.94
Table 6 Compa ison o p edic ion quali y ANN (LMA) [1.6.2015–30.6.2015 (da a no mal-
ized)] wi h es ed da a [16.6.2015 (6:40–23:18)]
Numbe o neu ons (−) RMSE aining (ppm) R aining (−)
10 0.054 0.67
50 0.047 0.59
100 0.027 0.88
150 0.029 0.85
200 0.024 0.90
250 0.022 0.91
300 0.025 0.89
350 0.024 0.90
400 0.021 0.92
450 0.021 0.92
500 0.020 0.93
550 0.023 0.90
600 0.021 0.92
650 0.021 0.92
700 0.022 0.91
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
Discussion
The second pa o he pape desc ibes and expe imen ally documen s he p ocedu e o
he use o a mul ilaye o wa d ANN o p edic he cou se o CO2 concen a ion om he
measu ed Ti (°C), ela i e humidi y H (%) in he in e io o he selec ed oom R104 o
he SHC and om he ou doo empe a u e To (°C), wi h he g adien e o p opaga ion
algo i hm using he Le enbe g–Ma qua d p edic i e me hod (LMA). Fo he classi i-
ca ion o p edic ion quali y, a co ela ion analysis (co ela ion coe icien R), calcula ed
RMSE (Roo Mean Squa e E o ) and MAPE (Mean Absolu e Pe cen E o ) and Black-
Al man me hod we e used. The bes esul s we e achie ed by ANN LMA ained on he
measu ed alues in he pe iod 1.6.2015–30.6.2015. The achie ed esul s app oached R
>95% o 600 neu ons (Tables2, 3), o du ing he ac ual es R=0.93 o 500 neu ons
(Table6). ANN LMA, ained o measu ed alues in he pe iod (1.2.2015–27.2.2015),
achie ed compa able esul s (R=0.95) o he numbe o neu ons 500 (Tables4, 5). The
esul s o p edic ion es ing o ANN LMA (1.2.2015–27.2.2015) howe e , we e no as
success ul (R=0.67) o 300 neu ons (Table7).
Thi d pa —implemen a ion oice communica ion inSHC wi hKNX echnology
Fo oice communica ion wi h he con ol sys em aimed a con ol o ope a ing echni-
cal unc ions and elec ic appliances [64, 65, 66, 67–69] in SHC and in in elligen build-
ings, i is necessa y o p o ide o an applica ion wi h a isualiza ion pla o m employing
he exis ing high-quali y speech command ecognize wi h high e iciency o ecogni-
ion in he eal SHC en i onmen wi h addi i e noise, which can be used o suppo
he independen li ing o senio s in hei home en i onmen . B ooks con i med ha
use —cen e ed design and he use o echnology—Sma u ni u e wi h oice in e ac-
ion, which can be used o enhance daily li ing [70]. Hamill desc ibes he de elopmen
and es ing o an au oma ed, hands- ee, dialogue-based speech ecogni ion in e ace o
pe sonal eme gency esponse sys ems—PERS p o o ype wi h he moun ed mic ophone
Table 7 Compa ison o p edic ion quali y ANN (LMA) [1.2.2014–27.2.2014 (da a no mal-
ized)] wi h es ed da a [18.2.2014 (7:00–23:40)]
Numbe o neu ons (−) RMSE aining (ppm) R aining (−)
10 0.076 0.10
50 0.064 0.39
100 0.061 0.40
150 0.051 0.61
200 0.050 0.63
250 0.053 0.59
300 0.049 0.67
350 0.047 0.65
400 0.047 0.66
450 0.050 0.61
500 0.047 0.65
550 0.053 0.59
600 0.047 0.66
650 0.050 0.63
700 0.049 0.65
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
a ay, an open-sou ce au oma ic speech ecogni ion engine, and a ‘yes’ and ‘no’ esponse
dialog modeled a e an exis ing call cen e p o ocol [71]. Hossain p oposes sma home
heal h ca e sys em o he ealiza ion o sma ci ies o ull ill he needs o elde ly peo-
ple, whe e a pa ien ’s condi ion is moni o ed by using mul imodal inpu s, speci ically,
speech and ideo. Video came as and mic ophones a e ins alled in he SHC; hese sen-
so s cons an ly cap u e ideo and speech o he pa ien and ansmi hem o a dedi-
ca ed cloud [72]. Johnson in he s udy, whe e was desc ibed olde adul s’ pe cep ions
and eac ions o SHC echnologies/applica ions a he Ga o -Tech SHC has ollowed
esul s: O e all, mos pa icipan s esponded a o ably owa d he sma doo and oice
ac i a ion han any o he sma echnology/applica ion [73]. Po e was aiming a es -
ing he ou impo an aspec s in SHC: oice con ol, communica ion wi h he ou side
wo ld, domo ics sys em in e up ion human ac i i y and elec onic agenda. Po e said
ha oice in e ace seemed o ha e g ea po en ial o ease he daily li e o he elde ly and
weak people and would be be e ecei ed han he mo e in usi e solu ion [74]. Tang
was desc ibing how hey implemen ed augmen ed eali y o oice con ol & web se e
o con ol SHC and elec ical appliances o elde lies and disabled [75]. Vanus designed
[76] and es ed [77] he oice communica ion wi h he con ol sys em in SHC. Zhuang
e al. [78] desc ibed a all de ec ion sys em o dis inguish noise coming om alls om
o he noise in he sma home en i onmen . In hei sys em, hey only use a a - ield
mic ophone o iden i y a ious sounds. Then a Gaussian Mix u e Models (GMM) Supe
ec o is used o model each all o noise segmen by applying Euclidean dis ance o
measu e he pai wise di e ence be ween audio segmen s. A Suppo Vec o Machine
buil on a GMM Supe ec o ke nel is used o classi y audio segmen s in o alls and
a ious ypes o noise [79].
In his pa o he pape is desc ibed he p ac ical implemen a ion o he newly de el-
oped isualiza ion desk op applica ion HESTIA, ype Uni e sal Windows Pla o m
(UWP), o Windows 10 implemen ed on he wooden house (SHC) a VŠB-TU Os a a
o oice con ol o ope a ing echnical unc ions by means o he KNX echnology wi h
de ec ion o occupancy o he oom R104 using CO2 senso .
Implemen a ion o  he c ea ed HESTIA isualiza ion applica ion
The p ac ical implemen a ion is dedica ed o he implemen a ion o own c ea ed appli-
ca ion Hes ia 10 which allows he oice con ol o ope a ing and echnical unc ions in
he SHC i ed wi h KNX bus sys em. The applica ion suppo s oice con ol and a ew
se ings o he use en i onmen . Uni e sal Windows Pla o m echnology and C# p o-
g amming language we e selec ed o de elop he applica ion. The implemen a ion was
based on he MVVM (Model, View a ViewModel) a chi ec u al pa e n which is b ie ly
desc ibed below.
HESTIA applica ion desc ip ion
Applica ion Hes ia consis s o se e al sc eens. Fo use s, he mos impo an sc een
is ha wi h con ols; his sc een con ains a lis o ooms and isualizes indi idual p e-
con igu ed de ices/appliances. The con ols a e depic ed based on he con igu a ion
sc een. In he case o ligh ing, he ligh s can be swi ched on and o . I is also possible
o change hei b igh ness using bu ons o dimming. As o u nishings o sunblind

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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
ype, he sc een depic s a con ol which may include se e al unc ions. Ano he impo -
an sc een se es o se ing he applica ion. He e, he use s can adjus some applica ion
pa ame e s in o de o adap i o hei indi idual needs. I is possible o se he language
(Czech o English). Fu he mo e, he use s can choose om wo colo schemes, ligh
and da k. The las se ing allows hem o change he on size; his acili a es he wo k
wi h he applica ion mos ly o senio s. The e a e h ee on sizes o choose om—small,
medium and la ge. A p e equisi e o he p ope unc ioning o he applica ion is con ig-
u a ion. I uns on a sepa a e sc een which can be accessed om he applica ion se ings.
Fo he pu pose o be e cla i y, a lis o ooms in he building is c ea ed in he i s
ins ance. A lis o de ices o each oom is c ea ed a e wa ds. When c ea ing de ices,
i is necessa y o selec he de ice ype and en e a leas one g oup add ess o some o
he possible unc ions. Con igu a ion should be pe o med by a pe son amilia wi h he
KNX bus sys em and speci ic bus p og amming. I is necessa y o know g oup add esses
and de ice ypes occu ing in he opology (Fig.14).
Wi hou his knowledge, i is no possible o p o ide con ol unc ionali y. The appli-
ca ion consis s o se e al componen s (Fig.15); he basic componen s a e Hes ia.View,
Hes ia.Model and Hes ia.ViewModel, o ming he ame o he MVVM a chi ec u al
pa e n.
This is desc ibed he eina e . Ano he componen is KNXLib.Po able. I is a eely
a ailable lib a y o communica ion wi h he KNX bus. Hes ia.Speech p o ides oice
ecogni ion logic and passes he in o ma ion u he in he applica ion. Hes ia. Common
Fig. 14 G oup add esses c ea ed in he ETS 5 SW ool o pa ame e iza ion o he indi idual KNX modules
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
is a sha ed componen ha con ains global a iables and me hods used ac oss he
applica ion.
Voice con ol
Fo speech ecogni ion, he SW ool o Mic oso Speech Pla o m SDK 11 is employed.
The oice ecogni ion unc ion consis s in he con e sion o he inpu sound ack o a
ex by he Speech Recogni ion Engine. The sound inpu is di ided in o segmen s p o-
cessed as a speech signal and subsequen ly con e ed o digi al o m. The inpu da a
adap ed in his manne is u he e alua ed by means o h ee da abases—(a) Acous-
ic model, (b) Lexicon, and (c) Language model. The acous ic model, ep esen ing he
acous ic language exp ession, can be adap ed o ecognize speci ic speech ai s o he
indi idual use s. The lexicon con ains a la ge numbe o wo ds in he gi en language,
p o iding in o ma ion on hei p onuncia ion. The language model p o ides in o ma ion
on he ways in which wo ds can be combined. The sequence diag am in Fig.16 desc ibes
a si ua ion whe e he use ocally en e s a g oup add ess in he con igu a ion ool.
Desc ip ion o  oice con ol implemen a ion inSHC
Fo he implemen a ion o oice con ol in SHC a VŠB–Technical Uni e si y o Os a a,
whe e KNX and BACne echnologies a e used o con ol he ope a ing and echnical
unc ions, while in e ope abili y be ween echnologies is ensu ed. To con ol ligh ing,
blinds, and socke s, KNX modules a e used (Fig.17).
Fo communica ion wi h he KNX bus, i is necessa y o connec KNXne /IP ou e o
he bus; he ou e allows sending in o ma ion be ween he de ice and he bus using he
IP p o ocol. In he case o wi eless communica ion, he KNXne /IP ou e mus be con-
nec ed o a wi eless ou e and he de ice (compu e , mobile phone) used o eques -
ing he communica ion wi h he bus mus be connec ed o he same ne wo k as he
KNXne /IP ou e (Fig.18).
Fig. 15 Diag am o componen s
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
Adap a ion osma phone
The HESTIA isualiza ion applica ion c ea ed o Windows 10 sha es a common code.
The applica ion wi h a PC-connec ed mic ophone is no sui able o he speake ’s mobil-
i y wi hin SHC. The e o e, he use in e ace mus be adap ed o be displayed on a ious
de ices (mobile appliances). This can be achie ed by using he VisualS a eManage class.
The sc een o he mobile de ice used o con ol he building is composed on he le pa
wi h a lis o ooms and he igh pa wi h de ails o he indi idual ooms including he
de ice lis . I he wid h o a window wi h he unning applica ion is educed o unde
Fig. 16 Sequence diag am desc ibing p ocessing o a oice command
Fig. 17 Swi chboa d wi h he KNX echnology componen s connec ed o he HESTIA applica ion c ea ed o
oice con ol o ope a ing- echnical unc ions in SHC
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Vanus e al. Hum. Cen . Compu . In . Sci. (2017) 7:30
720 pixels, only a oom lis is displayed; a e clicking on a speci ic oom, he use is edi-
ec ed o a new sc een wi h he oom de ails. This unc ionali y is implemen ed by he
VisualS a eManage elemen de ined in Con olView.xaml. Two s a es a e c ea ed in i by
means o he VisualS a e elemen — he de aul and educed s a es. By means o he Adap-
i eT igge elemen , condi ions o using he indi idual s a es can be de ined; by means
o he Se e elemen , i is possible o change he alues o exis ing elemen s and hei
a ibu es in he XAML ile. VisualS a eManage (Lis ing 1) can espond o a change bo h
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VisualS a eManage de ini ions.
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Wid h o MinWindowHeigh elemen . Fo a window wid h o e 720 pixels, he sc een
appea ance changes acco ding o he a ibu es se in he VisualS a e elemen called
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Fig. 18 P inciple block diag am o in e connec ion o he indi idual KNX bus modules eady o oice con ol
by means o he HESTIA SW applica ion c ea ed
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