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AN INTERENET-OF-THINGS APPROACH UTILIZING ULTRASONIC SENSING
TO REAL-TIME SOLID WASTE LEVEL DETECTION
Jenni e O. Ha apan
S uden s, No hwes e n Mindanao S a e College o Science and Technology
Labuyo Tangub Ci y, Philippines
Hidea Tali ongan
ORCID: 0000-0002-9143-4458
P o esso , No hwes e n Mindanao S a e College o Science and Technology
Labuyo Tangub Ci y, Philippines
ABSTRACT
The s udy aims o add ess he de iciencies in he Tangub Ci y manual collec ion, which su e om luck o
schedule moni o ing, uel was age, and addi ional ime consump ion in p o iding se ices. In o de o add ess
hese ine iciencies, an IoT-based was e-le el sensing sys em was p epa ed using an ul asonic module wi h
LoRaWAN, o he ansmission o ill-le el da a om BMRFs. An online pla o m was c ea ed o isualize he
da a in eal ime and au oma ically no i y he sys em use s acco dingly, as well as o guide hem in adjus ing
hei collec ion ou es based on da a. The e alua ion o he sys em was ca ied ou based on he quali y model
ISO/IEC 25010. The esul s o he measu emen s indica ed he ul asonic senso was g ea e han 95% accu a e
and he LoRaWAN module indica ed a 98% success a e in ansmission which would sugges ha he use
es ing would be s able and eliable. The use s' e alua ion a ed he sys em an accep ance scale alue o 93% o
usabili y, unc ionali y, and eliabili y. To sum up, he e idence p o ides ha he ci y's IoT-based moni o ing
sys em no only makes he p ocess o esou ce collec ion mo e e icien bu also is an eco- iendly me hod o
collec ion ha educes unnecessa y collec ion ips and suppo s he o ganiza ion o a mo e esponsi e and da a-
d i en was e-managemen p ocess o he ci y.
Keywo ds:
T uck Rou e, Sma Was e Managemen , LoRaWAN, Da a Moni o ing Au oma ion, Senso
INTRODUCTION
The p oblem o moun ing solid was e s ands ou in many pa s o he wo ld, abo e all in ci ies ha expand as .
Was e ou pu ises when neighbo hoods become dense and esiden s pu chase mo e goods. The ou come is
o en pollu ion, bins ha spill o e plus collec ion se ices ha lag behind. The Wo ld Bank [1] o ecas s ha , i
he end holds, 3.40 billion onnes o global was e will be gene a ed in 2050; such a olume places hea y
p essu e on managemen , sani a ion and public heal h. Many collec ion se ices s ill depend on hand checks bu
also ixed ime ables ye hose ools no longe i ci ies ha keep g owing. Towns he e o e s uggle o handle
ga bage in a way ha is bo h sus ainable and e icien , because he old me hods lose eliabili y.
Recen p og ess in he In e ne o Things has led o au oma ed ools ha y o ackle hose p oblems. A ypical
IoT se up joins a mic ocon olle , an ul asonic senso as well as a low powe wide-a ea ne wo k like
LoRaWAN - he senso measu es how ull he bin is and he ne wo k sends he igu e ac oss long dis ances
while i d aws li le powe [2],[3]. The da a each a cloud dashboa d in eal ime - was e c ews know he exac
s a us o each con aine . Resea ch also shows ha analy ics based on IoT da a help planne s sho en ou es, ake
be e decisions and aise o e all e iciency [4].
Ac oss Eu ope besides Asia, ci ies ha e ins alled ne wo ks o small In e ne -connec ed de ices on was e bins.
Those ne wo ks epo how ull each bin is and le dispa che s send ucks only o bins ha need emp ying. Field
es s show ha he me hod cu s diesel use, educes he o al numbe o uck uns plus keeps bins om
o e lowing [5], [6]. In Sou heas Asia, local go e nmen s apply he same p inciple - senso s on communal bins
ansmi ill le el da a o a cen al dashboa d - c ews isi bins ha ac ually need se ice [7]. In he Philippines,
mos ba angays s ill ollow a p in ed schedule - d i e s check bins by hand and ollow he same ou e e e y day.
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The ixed schedule causes missed pickups when bins ill ea ly bu also was es uel when bins a e nea ly emp y
[8]. A lexible echnology d i en eplacemen is equi ed.
E en whe e ucks ca y adios o GPS, ew c ews ecei e li e da a on bin olume. D i e s disco e ull bins
only when hey a i e - ex a ips, ou e changes and o e low occu . S udies wi hou li e senso s eco d
duplica ed jou neys, highe uel bills as well as o e ime wages [9]. To emo e he guesswo k, his wo k
p esen s an In e ne -connec ed Ga bage Volume Senso (GVS) ha measu es ill le el e e y ew minu es and
elays he eading o a cloud dashboa d. The dashboa d lags bins ha ha e eached he collec ion h eshold o
expo he lis o he dispa ch o ice allowing planne s o build uck ou es om ac ual demand a he han om
a calenda . This esea ch p esen s a low-powe LoRaWAN GVS ha uses ul asonic measu emen o olume
de ec ion. The sys em is accompanied by a web dashboa d and a ou ing engine o acili a e eal- ime bin ill
moni o ing and collec ion ou ing on demand.
As ecen s udies concluded, was e-moni o ing sys ems ha ocus on he in eg a ion o IoT wi h ul asonic le el
sensing wi h low-powe long- ange ne wo ks (e.g., LoRaWAN) can achie e ob ious ope a ional bene i s such as:
24/7 bin- ill measu emen s o con inuous da a collec ion, cen alized dashboa ds ha allow “li e” moni o ing,
and demand-d i en scheduling o a oid unnecessa y uck ips [5], [10], [2]. Fu he mo e, ull-scale ield es s
p o ed he signi ican bene i o sa ing uel and educing o e low e en s when such sys ems we e ins alled a
scale, hus demons a ing g ea p omise in ealising cos and esea ch also shows ha LoRaWAN ansmi s da a
o e long dis ances and uses li le powe , which sui s ci y wide ne wo ks whe e bins s and a apa . Ul asonic
senso s measu e he ill le el accu a ely in mos bin shapes - he wo echnologies oge he le ba e ies las longe
plus cu he need o equen se ice isi s [3],[11].
Howe e , Recen wo k ne e heless shows he same p ac ical aul s ha keep he sys ems om wo king well
ou side he labo a o y. Ul asonic senso s, o ins ance, gi e co ec eadings only while he ai s ays d y and he
was e su ace s ays la - d ops o wa e o an une en pile o e use e u n alse echoes. To keep he ou pu
eliable, he senso mus be ecalib a ed o shielded [12], [13] Many ins alla ions s op a epo ing how ull he
bin is - hey do no o ecas when i will o e low, do no p opose he sho es collec ion pa h and do no check
whe he he assigned uck has enough ee olume. Because o hose omissions, he dashboa d gi es he
ope a o only pa o he in o ma ion needed o a decision [4], [14]. Radio links also ail - in mul iple a eas he
LoRaWAN signal a i es only now and hen - he se e loses chunks o da a and s a mus d i e ou o
con i m he bin s a us by eye - he ex a ips e ode us in he digi al eading [15],[8]. P o o ypes seldom
include clea plans o la ge scale oll-ou , hacke p o ec ion o ou ine spa e pa eplacemen - long e m
ope a ion he e o e hinges on he du abili y o he i s ha dwa e ba ch, on he skills o he local adminis a ion
and on he quali y o he da a handling ules - opics ha emain une enly co e ed [16],[17].
The e iewed pape s ag ee ha IoT plus ul asonic plus LoRaWAN sys ems cu si e isi s and show da a in eal
ime - ye hey only wo k i h ee condi ions a e me : (1) he senso case wi hs ands ain, dus plus ib a ion and
he so wa e emo es empe a u e d i and echo noise; (2) he back end uses li e da a o e- ou e ehicles and o
schedule collec ions only when bins a e ull enough; (3) he ne wo k has spa e ga eways and s o es messages
locally when he signal d ops - no hing is los [5],[4],[7],[15]. Field es s in Eu ope, besides Sou heas Asia,
show ha p ojec s ha sealed he elec onics, il e ed da a on he se e , bu also added op imisa ion modules
kep use s sa is ied and educed mileage [6], [18], [19]. The gap is ha mos p o o ypes s op a e hey de ec a
ull bin - hey do no co ec eadings o wea he , do no choose he bes ou e as well, and do no check
whe he he assigned uck has space [4], [14]. To close his gap, he p esen wo k adds: (a) a wa e igh
ul asonic housing and a il e ha emo es empe a u e o echo e o s; (b) a LoRaWAN plan wi h wo ga eways
pe subu b, acknowledged uplinks and a local SD-ca d log i he link ails; (c) a web dashboa d ha eeds li e
ill le els and uck capaci ies o a ou ing engine. The whole sys em is es ed on eal collec ion ounds and
sco ed agains he ISO/IEC 25010 quali y model.
OBJECTIVES
The main objec i e o he s udy is o iden i y he challenges in Tangub Ci y’s manual was e collec ion p ocess,
and o de elop a p o o ype senso de ice, a collec ion moni o ing sys em ha imp o es he e iciency, accu acy,
and esponsi e o was e-collec ion ope a ions.
1. To build a p o o ype senso de ice ha can be ins alled inside a Ma e ial Reco e y Facili y, using an
ul asonic module o measu e he heigh o accumula ed was e, a mic ocon olle o p ocess he
eadings, and a LoRaWAN adio o ansmi he da a o a emo e ecei e .
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2. To de elop a web-based applica ion ha main ains a li e lis o all senso s, displays a colo -coded
s a us ba o each acili y, and au oma ically sends e-mail o ex -message ale s o d i e s when
con aine s each a de ined ill-le el h eshold.
3. To conduc a s uc u ed es plan o bo h he senso ha dwa e and he web so wa e, e alua ing he
accu acy o ill-le el measu emen s, he eliabili y o adio communica ion, and he esponsi eness o
ale no i ica ions based on he ISO/IEC 25010 quali y model.
4. To eco d he numbe o was e con aine s ha each he “ ull” le el each day and compa e hese
eco ds wi h he a ailable uck capaci y in o de o adjus collec ion ou es so ha ucks isi only he
acili ies lagged as ull by he sys em.
METHODOLOGY
The Solid Was e Managemen (SWM) O ice moni o ed a ew designa ed Ba angay Ma e ial Reco e y
Facili ies (BMRFs) in Tangub Ci y, Misamis Occiden al, Philippines, whe e he s udy ook place. These si es
we e picked because hey do no ha e eal- ime moni o ing sys ems and was e builds up i egula ly. Du ing he
de elopmen s age, he SWM O ice was also he main loca ion o dashboa d es ing, sys em assessmen , and
senso eading alida ion.
The da a used in his esea ch consis ed o ul asonic senso dis ance measu emen s (in cen ime e s), LoRaWAN
ansmission logs, eal- ime bin ill le els (in cubic me e s), and ale imes amps ansmi ed e e y h ee
minu es. Addi ional da a we e collec ed h ough obse a ion o daily BMRF was e accumula ion pa e ns and
in e iews wi h SWM pe sonnel. These da a se s we e used o e alua e accu acy, signal eliabili y, sys em
esponsi eness, and he e ec i eness o dynamic collec ion ou ing.
The Agile me hod will be used in he de elopmen o he p ojec . To conduc his p ojec he de elope s ha e
ollowed an agile model in so wa e de elopmen . This model, which is a c oss be ween p o o yping and
wa e all models, is also e e ed o as he li ecycle model in sys em de elopmen . The p oponen s adop ed his
model o he de elopmen o he p oposed sys em since he phase ha de elope s will execu e a e comple ion
o he sys em is pe inen and p ecise. Agile so wa e de elopmen is a concep ual amewo k o so wa e
enginee ing p ojec s unde which he solu ions e ol e h ough he collabo a i e e o o sel -o ganizing and
c oss- unc ional eams.
Figu e 1 Agile Model
The Agile model consis s o se e al phases:
Requi emen s: Ins all he i s machine o ene gy-sa ing p oduc ion. To se he bucke o he ini ial posi ion
and condi ion.
Design: The clien is in ol ed om he ou se , and eedback is c ucial. A duino and LoRa we e collec i ely
chosen o he echnology.
De elopmen ; Fea u es a e inc emen ally deli e ed in egula sp in s may be modi ied as equi emen s dic a e.
Tes ing: These a e when hese GV se es o p o ide a GV ce i ica e o epo .
Deploymen : Wi h equen eedback, he clien adds o he sys em’s ma u i y.
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Re iew: This also helps o alida e he success ul e iew and acking o key pe o mance indica o s.
Design o so wa e, Sys em, P oduc
Figu e 2 Sys em A chi ec u e
When he Ga bage Volume Senso (p o o ype) is moun ed a he Ba angay Ma e ial Reco e y Facili y (BMRF),
i s a s scanning he BMRF was e. Once a de ec ion has aken place, he mic ocon olle (A duino) sends ha
in o ma ion o he LoRaWAN module. On ge ing he GVS (p o o ype) da a, i is sen o he LoRaWAN
ga eway and hen is ed o he SWM (Solid Was e Managemen ) O ice o analysis. The cloud moni o ing
pla o m iden i ies which BMRF sen he da a and hen ansmi s he in o ma ion o he use in e ace. Upon
ecei ing he da a, he SWM s a can iew he ga bage le els o each BMRF in eal ime and de e mine which
loca ions equi e immedia e collec ion.
Con ex Diag am
Figu e 3 Con ex Diag am
The ga bage olume senso sends da a o he ga bage collec o sys em and he o ice in cha ge will iew he
epo o he ga bage olume in cubic me e s pe BMRF.
Da a Flow Diag am
A. DFD o Sa ing and Upda ing BMRF’s ga bage olume
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Figu e 4 Sa ing and Upda ing
B. DFD o Viewing o Ga bage Volume pe BMRF
Figu e 5 View Ga bage pe BMRF
C. DFD o Adminis a o Login
Figu e 6 Adminis a o
D. Fo Adding new and Upda ing Exis ing BMRD Reco d
Figu e 7 Adding and Upda ing
Func ional Decomposi ion Diag am
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Figu e 8 Func ional Decomposi ion Diag am
Cos and Bene i Analysis
Table 1 Cos and Bene i Analysis
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The es ima ed cos s and bene i s o he IoT ga bage-collec ion sys em a e summa ized in he able. Fo new
ins alla ions, he p esen ed sys em will be compe i i e a e a ew yea s o ope a ion due o uel consump ion
and wo k e iciency conside a ions, despi e high ini ial in es men o senso s and added cos s compa ed o a
manual placemen o con aine s.
Figu e 9 Cos and Bene i Analysis Cha
The igu e shows ha , al hough cos o he IoT based ga bage collec ion is la o e hese yea s, cumula i e
bene i keeps g owing. This is indica i e o he cos -e ec i eness, and he long- e m sus ainabili y o he
p ojec in s eamlining was e-managemen se ices.
RESULTS AND DISCUSSION
This sec ion p esen s he esul s o he sys em e alua ion using ables, igu es, and na a i e explana ion. The
indings a e o ganized based on he s udy’s objec i es and a e compa ed wi h es ablished h esholds om
ela ed li e a u e.
ACKNOWLEDGEMENT
The esea che s would like o hank he No hwes e n Mindanao S a e College o Science and Technology and
he Tangub Ci y Solid Was e Managemen O ice o hei echnical suppo and assis ance du ing he sys em
de elopmen and es ing. Ou g a i ude goes o ou amilies o se ing as ou sou ce o inspi a ion, and abo e
all, o God
CONCLUSION
The esea ch has achie ed he o mula ion and assessmen o an IoT-based municipal solid was e moni o ing
sys em and collec ion op imiza ion o Tangub Ci y. The ul asonic senso module ixed a he BMRF o he
ga bage con aine p oduced he mos accu a e ill-le el eadings, and he LoRaWAN communica ion
con igu a ion indeed showed a e y s able 98% ansmission success a e wi hin he es ange. Real- ime web
dashboa d was also accomplished whe e SWM o ice s can emo ely moni o he s a us o bins, ge au oma ed
ale s, and hence make scheduling decisions easily. The ISO/IEC 25010 e alua ion showed a 93% accep ance
sco e, which indica es ha he sys em had good usabili y, unc ionali y, and eliabili y. Regula senso da a
enabled SWM pe sonnel o ecognize hose BMRFs ha had eached he ull h eshold and co espond hese
wi h he a ailable uck capaci y o he bes ou e planning. Ne e heless, quali a i e commen s om he SWM
o ice s showed ha he e we e ewe unnecessa y ips, mo e lexible ou ing, and an o e all imp o emen in
ope a ional e iciency as compa ed o he p e ious manual, schedule-based me hod.
Summing up he indings indica e ha he IoT-based sys em deli e s on ime, accu a e, and ac ionable
in o ma ion ha helps o enhance was e-collec ion ope a ions and also assis s Tangub Ci y in i s ansi ion
owa ds da a-d i en and sma e was e-managemen p ac ices.
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