applied
sciences
A icle
Real-Time Ex ensi e Li es ock Moni o ing Using LPWAN
Sma Wea able and In as uc u e
Robe o Casas 1,* , A u o He mosa 1,Ál a o Ma co 1,2 , Te esa Blanco 1,2 and
F ancisco Ja ie Za azaga-So ia 1


Ci a ion: Casas, R.; He mosa, A.;
Ma co, Á.; Blanco, T.; Za azaga-So ia,
F.J. Real-Time Ex ensi e Li es ock
Moni o ing Using LPWAN Sma
Wea able and In as uc u e. Appl.
Sci. 2021,11, 1240. h ps://doi.o g/
10.3390/app11031240
Academic Edi o : Ak am Alomainy
Recei ed: 31 Decembe 2020
Accep ed: 25 Janua y 2021
Published: 29 Janua y 2021
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Copy igh : © 2021 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
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A ibu ion (CC BY) license (h ps://
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4.0/).
1A agon Ins i u e o Enginee ing Resea ch, Uni e si y o Za agoza, 50018 Za agoza, Spain;
a u ohache@uniza .es (A.H.); ama [email p o ec ed] (Á.M.); [email p o ec ed] (T.B.); ja y@uniza .es (F.J.Z.-S.)
2GeoSpa ium Lab S.L., Ca los Ma x 6, 50015 Za agoza, Spain
*Co espondence: casas@uniza .es; Tel.: +34-976-762-856
Fea u ed Applica ion: The wea able and in as uc u e p esen ed in his wo k has p o en o be
a aluable and lexible ool o eal- ime ex ensi e li es ock acking and moni o ing wi h egu-
la o y compliance. Main ea u es a e online and o line moni o ing and da a logging; adap a i e
dual adio (FSK and LoRaWAN) o bes ene gy/bandwid h/ ange balance; adap a i e mo emen
da a s eaming modes wi h ec o quan iza ion comp ession me hod; and yea s o ba e y li e.
Abs ac :
Ex ensi e unsupe ised li es ock a ming is a habi ual echnique in many places a ound
he globe. Animal elease can be done o mon hs, in la ge a eas and wi h di e en species packing
and beha ing e y di e en ly. Ne e heless, he a me ’s needs a e simila : whe e li es ock is (and
whe e has been) and how heal hy hey a e. The geog aphical a eas in ol ed usually ha e di icul
access wi h ha sh o og aphy and lack o communica ions in as uc u e. This pape p esen s he
design o a solu ion o ex ensi e li es ock moni o ing in hese a eas. Ou p oposal is based in a
wea able equipped wi h ine ial senso s, global posi ioning sys em and wi eless communica ions; and
a Low-Powe Wide A ea Ne wo k in as uc u e ha can un wi h and wi hou in e ne connec ion.
Using adap i e analysis and da a comp ession, we p o ide eal- ime moni o ing and logging o
ca le’s posi ion and ac i i ies. Ha dwa e and i mwa e design achie e e y low ene gy consump ion
allowing mon hs o ba e y li e. We ha e ho oughly es ed he de ices in di e en labo a o y se ups
and e alua ed he sys em pe o mance in eal scena ios in he moun ains and in he o es .
Keywo ds:
animal moni o ing; low-powe wide a ea ne wo ks; LoRaWAN; wea able de ices design
1. In oduc ion
Ex ensi e li es ock a ming is a ypical echnique in many places a ound he wo ld. I
occu s on 25% o global land su ace and suppo s a ound 200 million subsis ence pas o al
households [1]. In A ica, 40% o he land is dedica ed o ex ensi e pas o alism [2]. Many
habi a s impo an o biodi e si y conse a ion ha e been c ea ed by and a e s ill inhe -
en ly linked o ex ensi e li es ock p oduc ion, in pa icula g azing. Fo ins ance, ex ensi e
g azing is conside ed i al o main aining many biodi e si y- ich habi a s in Eu ope. I is
sugges ed as op imum managemen o de-in ensi ied g assland o enhance biodi e si y [
3
].
Ex ensi e g azing was epo ed o posi i ely in luence swa d species composi ion and
s uc u e which, in u n, p o ided a ou able condi ions o colonizing auna.
Fu he mo e, ex ensi e li es ock and he ela ed g azing is also c i ical o main aining
many o Eu ope’s cul u al landscapes and sus aining u al communi ies. O e he cen u ies,
pas o alism, and anshumance (seasonal mo emen o li es ock be ween g azing a eas)
c ea ed a wide a ie y o speci ic cul u al landscapes. The la ges emaining ex ensi e
pas o al sys ems on pe manen wood pas u es in Eu ope a e Dehesa in Spain and Mon ado
in Po ugal [
4
]. G azing and anshumance a e o pa icula impo ance o he p ese a ion
o open landscapes in he Eu opean moun ains. In addi ion, socie al conce n o e he
Appl. Sci. 2021,11, 1240. h ps://doi.o g/10.3390/app11031240 h ps://www.mdpi.com/jou nal/applsci
Appl. Sci. 2021,11, 1240 2 o 18
wel a e o a m animals has ecen ly inc eased and a g owing numbe o ci izens in many
coun ies hink ha i is impo an o p o ec he wel a e o a m animals [
5
]; ex ensi e
li es ock is belie ed o be ad an ageous in e ms o animal wel a e.
Ex ensi e li es ock a ming is, in mos cases in Eu ope, unsupe ised. Ca le, mainly
bo ine, a e ee in la ge enclosed emo e a eas o mos o he yea . Al hough shephe ds
do con ol he ca le pe iodically, whene e he wea he allows i , animals a e collec ed
only o one mon h o ake a e e ina y con ol. This implies mo ing o he a ea whe e he
animals a e li ing and looking o hem. We a e alking abou hund eds o hec a es, in
mos cases wi hou any kind o oad. Consequen ly, i is usual ha shephe ds spend mos
o hei ime walking h ough he ield while hey a e looking o he animals. In o de o
assis hem in his ask, some Global Na iga ion Sa elli e Sys em (GNSS)-based solu ions
ha e been de eloped o con olling he mo emen s o he animals and epo ing hem
o he a me s. Fo ins ance, Pé ez e al. [
6
] use a GPRS-based sys em o moni o ing lidia
ca le, meanwhile La ia e al. [7] use a SigFox-based one.
In Eu ope, his ype o li es ock a ming is usually es ic ed o emo e a eas wi h
low popula ion densi y. This makes hese a eas less in e es ing o elecommunica ion
se ice p o ide (TSP), o o e high wand-wind se ices: high in es men o small e u n
(see Figu es 1and 2). E en o echnologies de eloped o he imp o emen o In e ne o
Things (IoT) canno o e co e age o all hese emo e a eas (see Figu e 2).
Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 o 19
Figu e 1. 3G co e age p o ided by he main elecommunica ion se ice p o ide (TSP) in he Py enees a ea in Spain
(sou ce websi es om Mo is a , O ange, Voda one and MasMo il, Decembe 2020).
Figu e 1.
3G co e age p o ided by he main elecommunica ion se ice p o ide (TSP) in he Py enees a ea in Spain (sou ce
websi es om Mo is a , O ange, Voda one and MasMo il, Decembe 2020).
The e a e se e al o he al e na i es o cellula ne wo ks o IoT moni o ing. These can
be mesh ne wo ks, whe e link quali y indica o s could be used o loca e animals wi hou
GNSS [
8
]. This kind o deploymen is hea ily dependen o he ga eway which usually
becomes he bo leneck and, depending on he o og aphy, equi es a ou e in as uc u e
ha needs conside able amoun o ene gy [
9
]. The e a e imes whe e he link be ween he
wi eless senso ne wo k (WSN) and he in e ne is a Wi-Fi anscei e , which is mean o
inc ease he ange in zones wi hou GPRS co e age [10].
Appl. Sci. 2021,11, 1240 3 o 18
Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 o 19
Figu e 1. 3G co e age p o ided by he main elecommunica ion se ice p o ide (TSP) in he Py enees a ea in Spain
(sou ce websi es om Mo is a , O ange, Voda one and MasMo il, Decembe 2020).
Figu e 2.
Co e age p o ided by SigFox (up) and NB-IoT by Voda one (down, and p obably he
bes one in Spain) in he Py enees a ea in Spain (sou ce websi es om SigFox and Voda one,
Decembe 2020).
Low-Powe Wide A ea Ne wo ks (LPWAN) a e also sui able op ions, b inging o-
ge he he low-powe quali ies o WSN and long- ange capaci ies o cellula ne wo ks.
The e a e no el modula ions such as LoRa ha can be used on mesh opologies o ex end
ange, al hough i is usually used in s a opology. Gi en he bene i s such as long ange,
low-powe and cos sa ings, LoRa is ideal o ca le moni o ing [11–13].
Ano he appealing al e na i e is he use o UAVs, which is an eme ging applica ion in
he ield o p ecision ag icul u e [
14
–
16
]. Speci ic usage o UAVs o ca le moni o ing is
desc ibed in [
17
–
20
] which elay on image p ocessing echniques o iden i y animals and
accoun o hem. Howe e , ha app oach ha e some limi a ions when we a e conce ned
abou acking speci ic indi iduals (a shephe d would be in e es ed in loca ing his animals
only) and does no allow con inuous acking as GNSS solu ions do. Combined usage o
UAVs and GNSS is also p oposed in [
21
], which conside d ones o easing he e ie e
o he acking in o ma ion acqui ed by GPS colla s wo n by he animals. Ne e heless,
a numbe o echnical and adminis a i e issues a ise ha s ill possess some di icul ies
o using UAVs in ex ensi e ca le moni o ing, such as he cos o he need o specialis
ope a o s (i is equi ed mid/high-size UAVs o co e ing big ex ensions), which may also
equi e a lying license and special pe mission in some coun ies [22].
Besides localiza ion acking o he animals using GNSS, egis e ing hei s a us and
ac i i ies can be o in e es o shephe ds [
23
]. Ac i i y de ec ion can be pe o med wi h
di e en s a egies such as adio equency iden i ica ion (RFID) o in e ca le d inking
beha io and wa e in ake by de ec ing p oximi y o speci ic places [
24
]. Using empe -
a u e [
25
] and o he biosenso s [
26
] can help o de ec a e e s a e and o asse animal
well-being. The mos common a e ine ial senso s based on accele ome e s and gy oscopes
ha a e able o iden i y animal ac i i ies such as es ing, walking, ma ing o eeding among
o he s [27,28].
Appl. Sci. 2021,11, 1240 4 o 18
Using ine ial da a o ex ac ac i i ies is a e y powe ul, cheap, ene gy-e icien and,
consequen ly, b oadly adop ed s a egy. Ne e heless, ine ial senso s canno be di ec ly
used, due o he high h oughpu equi ed: a 12-bi 3-axis accele ome e sampling a 10
Hz gene a es mo e han 1.25 Mb o da a e e y hou . Sending his amoun o da a h ough
LPWAN is oo cos ly in bo h economic and ene ge ic e ms, some imes iola es egional
es ic ions (e.g., LoRaWAN) o i is jus echnically impossible (e.g., Sig ox). Thus, aw
da a needs o be p ocessed in o de o ex ac he mos impo an ea u es, which also helps
sa ing and sending way less da a han gene a ed.
The e a e wo main s a egies ha can be applied. Cus om da a p ocessing echniques
o speci ically de ec he equi ed ac i i ies pe o med by animals [
29
] and humans [
30
] is
a ending esea ch opic. I is also possible o use da a comp ession s a egies o educe
he amoun o in o ma ion o be sen and hen decomp ess and p ocess i in he cloud.
Usual echniques o accomplishing da a comp ession a e P incipal Componen Analysis
(PCA) [
31
–
34
], Sequen ial Fo wa d Selec ion (SFS) [
35
], Random Subse Fea u e selec ion
(RSFS) [
35
], Independen Componen Analysis (ICA) [
34
], I-PCA [
34
], Vec o Quan iza ion
(VQ) [36], and F equency Sensi i e Compe i i e Lea ning (FSCL) [37,38].
In his con ex , we aim o moni o animals in ex ensi e a ming in he no h pa o
Spain (in he Py enees a ea, nea he bo de wi h F ance). We ha e wo main objec i es:
Fi s ly, we need o ack he mo emen o he animals o e alua e hei impac on he plan
biodi e si y. This could be done jus by using a de ice i ed wi h a GNSS ecei e ha
would collec he posi ions du ing he ime he animals a e in he moun ain and download
hem when hey a e e u ned o he ba ns. Secondly, we in end o i ually educe he
dis ance be ween he animals and he shephe ds. Fo his eason, i is necessa y o elay he
posi ions and s a uses o he animals in eal ime. As he selec ed a ea has no gua an eed
co e age om any TSP, i has been necessa y o ocus on a di e en app oach.
Ou p oposal is a wea able equipped wi h ine ial senso s, GNSS and wi eless com-
munica ions. Including adap i e analysis and VQ comp ession model in he wea able
achie ing high comp ession a ios wi h good peak signal- o-noise a ios (PSNR) [
39
] allows
o eal- ime moni o ing and logging o ca le’s posi ion and ac i i ies. We ha e chosen a
anscei e wi h bo h FSK and LoRa capabili ies. As i has been men ioned be o e, he e
is no co e age by TSPs and links based on hese modula ions ha e p o en i s u ili y in
open a ming scena ios. We ocused ou elec onic design on achie ing e y low ene gy
consump ion, allowing o se e al mon hs o ba e y un ime. We ha e e alua ed bo h
he wea able and he sys em pe o mance o acking cows in eal scena ios, such as
moun ains and o es .
The es o he pape is s uc u ed as ollows: i s , he cha ac e is ics o he wea able,
i s capabili ies and he ope a ion modes a e de ined; hen, labo a o y expe imen a ion and
ield es s a e p esen ed; and las ly, sys em cha ac e is ics and wo k esul s a e discussed.
2. Ma e ials and Me hods
2.1. Wea able Design
The wea able in eg a es se e al senso s o measu ing empe a u e, accele a ion, and
magne ic ields. I also ea u es a GNSS posi ioning module and a LoRa anscei e able o
ansmi using FSK and LoRa modula ions o communica ion pu poses. In he p ocessing
side he e is a 64 Mbi NOR lash o s o ing acking da a, a 16-bi MCU wi h low-powe
ea u es and a powe managemen ci cui y ha allows being powe ed wi h any ba e y
chemis y and echa ging i om di e en powe sou ces like sola panels, induc ion,
he moelec ic and piezoelec ic (Figu e 3[40]).
Appl. Sci. 2021,11, 1240 5 o 18
Appl. Sci. 2021, 11, x FOR PEER REVIEW 5 o 19
The wea able in eg a es se e al senso s o measu ing empe a u e, accele a ion, and
magne ic ields. I also ea u es a GNSS posi ioning module and a LoRa anscei e able
o ansmi using FSK and LoRa modula ions o communica ion pu poses. In he p o-
cessing side he e is a 64 Mbi NOR lash o s o ing acking da a, a 16-bi MCU wi h low-
powe ea u es and a powe managemen ci cui y ha allows being powe ed wi h any
ba e y chemis y and echa ging i om di e en powe sou ces like sola panels, induc-
ion, he moelec ic and piezoelec ic (Figu e 3 [40]).
Figu e 3. Ha dwa e block diag am.
The design objec i es conside ed se e al pe spec i es, mainly ha o he shephe d
and ha o he animal, as wo ypes o use s wi h di e en needs. Thus, he design speci-
ica ions we e aimed a ensu ing high esis ance o shock and wa e ; compa ibili y wi h
di e en exis ing s ap a achmen me hods; ease o a achmen and emo al; and ac-
cep ance o he de ice by he hos . We designed, es ed and edesigned a ious 3D enclo-
su es o e i y di e en o maliza ions, inishing angles, and manu ac u ing ma e ials.
Finally, we selec ed a clam design wi h an o- ing ha s ays in place wi h ou sc ews. The
enclosu e has wo slo s wi h di e en sizes allowing di e en -sized animals o com o a-
bly wea hem (e.g., sheep and cows). We ha e success ully pe o med wa e p oo IP68
es ing. Final design can be seen in Figu e 4.
Figu e 4. 3D and inal p o o ype.
2.2. Logic and Communica ions
We conside se e al modes each wi h di e en con igu a ion pa ame e s:
● Beacon: GNSS is sampled a TGNSS and once posi ion is acqui ed, i is sa ed in lash
memo y, sen ia LoRaWAN and hen he anscei e wai s o a con igu a ion
Figu e 3. Ha dwa e block diag am.
The design objec i es conside ed se e al pe spec i es, mainly ha o he shephe d
and ha o he animal, as wo ypes o use s wi h di e en needs. Thus, he design
speci ica ions we e aimed a ensu ing high esis ance o shock and wa e ; compa ibili y
wi h di e en exis ing s ap a achmen me hods; ease o a achmen and emo al; and
accep ance o he de ice by he hos . We designed, es ed and edesigned a ious 3D
enclosu es o e i y di e en o maliza ions, inishing angles, and manu ac u ing ma e ials.
Finally, we selec ed a clam design wi h an o- ing ha s ays in place wi h ou sc ews. The
enclosu e has wo slo s wi h di e en sizes allowing di e en -sized animals o com o ably
wea hem (e.g., sheep and cows). We ha e success ully pe o med wa e p oo IP68 es ing.
Final design can be seen in Figu e 4.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 5 o 19
The wea able in eg a es se e al senso s o measu ing empe a u e, accele a ion, and
magne ic ields. I also ea u es a GNSS posi ioning module and a LoRa anscei e able
o ansmi using FSK and LoRa modula ions o communica ion pu poses. In he p o-
cessing side he e is a 64 Mbi NOR lash o s o ing acking da a, a 16-bi MCU wi h low-
powe ea u es and a powe managemen ci cui y ha allows being powe ed wi h any
ba e y chemis y and echa ging i om di e en powe sou ces like sola panels, induc-
ion, he moelec ic and piezoelec ic (Figu e 3 [40]).
Figu e 3. Ha dwa e block diag am.
The design objec i es conside ed se e al pe spec i es, mainly ha o he shephe d
and ha o he animal, as wo ypes o use s wi h di e en needs. Thus, he design speci-
ica ions we e aimed a ensu ing high esis ance o shock and wa e ; compa ibili y wi h
di e en exis ing s ap a achmen me hods; ease o a achmen and emo al; and ac-
cep ance o he de ice by he hos . We designed, es ed and edesigned a ious 3D enclo-
su es o e i y di e en o maliza ions, inishing angles, and manu ac u ing ma e ials.
Finally, we selec ed a clam design wi h an o- ing ha s ays in place wi h ou sc ews. The
enclosu e has wo slo s wi h di e en sizes allowing di e en -sized animals o com o a-
bly wea hem (e.g., sheep and cows). We ha e success ully pe o med wa e p oo IP68
es ing. Final design can be seen in Figu e 4.
Figu e 4. 3D and inal p o o ype.
2.2. Logic and Communica ions
We conside se e al modes each wi h di e en con igu a ion pa ame e s:
● Beacon: GNSS is sampled a TGNSS and once posi ion is acqui ed, i is sa ed in lash
memo y, sen ia LoRaWAN and hen he anscei e wai s o a con igu a ion
Figu e 4. 3D and inal p o o ype.
2.2. Logic and Communica ions
We conside se e al modes each wi h di e en con igu a ion pa ame e s:
•
Beacon: GNSS is sampled a T
GNSS
and once posi ion is acqui ed, i is sa ed in
lash memo y, sen ia LoRaWAN and hen he anscei e wai s o a con igu a ion
message om he se e be o e going o sleep. I no GNSS signal is de ec ed o
T
TIMEOUT
, las known coo dina es a e sen . I can ollow a sma beha io i desi ed.
Then, GNSS is acqui ed only i mo emen has been de ec ed be ween wo T
GNSS
pe iods. Mo emen condi ion is asse ed by he ine ial measu emen uni (IMU) i sel ,
as i ac i a es an in e up when an A
TRHESOHLD
is exceeded. I no sma beha io is
se , he de ice sends GNSS ega dless o he mo emen condi ion.

Appl. Sci. 2021,11, 1240 6 o 18
•
Mo emen : on op o he beacon sma mode, he wea able s eams IMU da a a
T
SENSOR
pe iod. As IMU aw da a s eam would lead o a du y cycle policy iola ion,
we ha e implemen ed ou di e en beha io s o p e en exceeding i :
#
Con inuous: The easies way o ge maximum bi a e is o use FSK modula ion
o achie e 50 Kbps. Conside ing ha he accele ome e has 14 bi p ecision
measu emen s, a EU868 (869.525 MHz) equency, he one wi h he bes du y
cycle (10%), we can s eam a :
FSAMPLE =ACCPRECISION ×NAXIS
DATARATE ×DUTY CYCLE ×PRATIO =14 b ×3
50 kb/s ×10% ×64 B +8 B
64 B =105.82 Hz, (1)
Un o una ely, his is no LoRaWAN complian as du y cycle and bi a e a e abo e lim-
i s. Thus, assuming du y cycle policies om EU868 egion (1%), usual DR5 LoRaWAN
modula ion, acco ding o Equa ion (2), we can s eam a ound one sample pe second.
FSAMPLE =14 b ×3
5.47 kb/s ×1% ×358 B
242 B =1.14 Hz, (2)
I we jus send one piece o axis da a, he
FSAMPLE
can each 3.4 Hz, which could lead
o sending mo e meaning ul da a.
#
Coded: his mode beha es simila ly o he p e ious, bu i includes an addi-
ional s ep whe e he da a is comp essed p io o be sen [
30
]. VQ comp ession
de ines a NxM look-up able (codebook), being N he numbe o cen oids,
i.e., he numbe o di e en comp essed samples ha can be chosen o being
ansmi ed, and M he size o he signal ha each cen oid ep esen s. The
comp ession algo i hm accumula es a window o M samples o he signal and
picks he cen oid ha be e i s he o iginal signal (minimizing mean squa ed
e o ). Then, jus he index o he cen oid is ansmi ed, and he signal can
be econs uc ed a he ecep ion by accessing he codebook wi h he index.
The numbe o cen oids N and he size o he window M allows es ablishing
in ad ance he comp ession a e o be achie ed (and hus inc easing e ec i e
FSAMPLE):
comp ession_ a e =M×sample_size
log2(N)/8 , (3)
The codebook has o be gene a ed p e iously wi h a machine lea ning algo-
i hm ha is ained wi h samples o he da a o iden i y he cen oids ha
will lead o be e PSNR igu es wi h he desi ed comp ession a e, Ou majo
limi a ion is he memo y a ailable in he de ice. Using his mode, we can go
up o 20 Hz sampling a DR5 o e LoRaWAN p o ocol wi h good pe o mance.
#
Bu s : his mode de ec s mo emen and hen accumula es se e al seconds
o da a. Then, in o de o comply wi h LoRaWAN egula ion, we spli he
packe be ween he a ailable channels using a schedule ha moni o s channel
usage and p e en s messages o be sen when he du y cycle is abou o be
exceeded. When his happens, new da a is disca ded un il we a e eady o
send again. Using his mode, we can send 3-s bu s s a 10 Hz sampling a DR5
o e LoRaWAN p o ocol.
#
Sma : The sma s a egy is like bu s mode bu be o e sending da a, i ana-
lyzes i o check i no mo emen is de ec ed; in ha case, mo emen da a is
disca ded, and no sen . This condi ion is de e mined when he maximum peak
o peak alue o he las i e seconds o da a is below a h eshold A
NO-MOVE
.
This h eshold is con igu able o adjus sensi i i y o he de ice.
•
Con ig: his mode sends LoRaWAN beacons e e y 10 s, allowing downlink messages
ha con igu e he wea able. Con ig mode is au oma ically en e ed a e a ha d ese
Appl. Sci. 2021,11, 1240 7 o 18
and las s T
CONFIG
. In his mode we can e ie e he GNSS samples s o ed in lash
memo y and send hem h ough FSK packe s.
•
S andby: his is he lowes ene gy consump ion mode whe e he wea able jus sleeps.
The only way o exi his s a e is ia ha d ese .
Figu e 5illus a es i mwa e’s low diag am in eg a ing all modes.
To cus omize he se ings o his de ice, we de ine a con igu a ion message ia Lo-
RaWAN, al hough i is also possible o do so ia USB. Acco ding o LoRaWAN speci ica ion,
as a class A de ice, each ime an uplink message is sen , he e a e wo ecei ing windows
when he de ice can ecei e downlink messages. This is he eason why in con ig mode
he de ices send beacon messages each 10 s du ing 1 min.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 7 o 19
alue o he las i e seconds o da a is below a h eshold ANO-MOVE. This
h eshold is con igu able o adjus sensi i i y o he de ice.
● Con ig: his mode sends LoRaWAN beacons e e y 10 s, allowing downlink messages
ha con igu e he wea able. Con ig mode is au oma ically en e ed a e a ha d ese
and las s TCONFIG. In his mode we can e ie e he GNSS samples s o ed in lash
memo y and send hem h ough FSK packe s.
● S andby: his is he lowes ene gy consump ion mode whe e he wea able jus sleeps.
The only way o exi his s a e is ia ha d ese .
Figu e 5 illus a es i mwa e’s low diag am in eg a ing all modes.
To cus omize he se ings o his de ice, we de ine a con igu a ion message ia Lo-
RaWAN, al hough i is also possible o do so ia USB. Acco ding o LoRaWAN speci ica-
ion, as a class A de ice, each ime an uplink message is sen , he e a e wo ecei ing win-
dows when he de ice can ecei e downlink messages. This is he eason why in con ig
mode he de ices send beacon messages each 10 s du ing 1 min.
Figu e 5. Fi mwa e’s low diag am.
Thus, he e is one downlink message used o wea able con igu a ion and wo pos-
sible payloads o upload: one wi h GNSS da a and he o he is he IMU da a a ays. Bo h
GNSS da a and con igu a ion messages use LoRaWAN in as uc u e because hey a e
sho messages ha a e no sen e y o en and occu a de e minis ic imes. This allows
us o mee ai use policies [41] needed o use a ailable LoRaWAN in as uc u e in he
ield, being he bes -e o app oach, as he e a e many a ailable ga eways ha can ou e
he packe s o he cloud. Besides ea u es such as secu i y, enc yp ion, e y coun e o
moni o o un eachable nodes, LoRaWAN allows us o send con igu a ion packe s when-
e e a de ice becomes a ailable and he ne wo k laye allows o acknowledged packe s.
Meanwhile, IMU da a is hea y, occu s non-de e minis ically and needs o be ime
s amped and managed as i occu s. We ha e conside ed using wo di e en modula ions
as we ha e wo use cases: bu s and con inuous ansmission. The i s one is used when
we migh be in e es ed in spo adic da a sampled and low equencies (less han 5 Hz),
and i is possible o ge bene i om he ex a ange LoRa p o ides on noisy en i onmen s.
This kind o beha iou is accep able o he deploymen in open ield a eas whe e he e
a e animals ee o mo e long dis ances. Fi mwa e needs o check whe he he payloads
Figu e 5. Fi mwa e’s low diag am.
Thus, he e is one downlink message used o wea able con igu a ion and wo possible
payloads o upload: one wi h GNSS da a and he o he is he IMU da a a ays. Bo h GNSS
da a and con igu a ion messages use LoRaWAN in as uc u e because hey a e sho
messages ha a e no sen e y o en and occu a de e minis ic imes. This allows us o
mee ai use policies [
41
] needed o use a ailable LoRaWAN in as uc u e in he ield,
being he bes -e o app oach, as he e a e many a ailable ga eways ha can ou e he
packe s o he cloud. Besides ea u es such as secu i y, enc yp ion, e y coun e o moni o
o un eachable nodes, LoRaWAN allows us o send con igu a ion packe s whene e a
de ice becomes a ailable and he ne wo k laye allows o acknowledged packe s.
Meanwhile, IMU da a is hea y, occu s non-de e minis ically and needs o be ime
s amped and managed as i occu s. We ha e conside ed using wo di e en modula ions
as we ha e wo use cases: bu s and con inuous ansmission. The i s one is used when
we migh be in e es ed in spo adic da a sampled and low equencies (less han 5 Hz), and
i is possible o ge bene i om he ex a ange LoRa p o ides on noisy en i onmen s. This
kind o beha iou is accep able o he deploymen in open ield a eas whe e he e a e
animals ee o mo e long dis ances. Fi mwa e needs o check whe he he payloads mee
he egula ion du y cycle; in case we gene a e mo e da a han he numbe o by es we can
send, he de ice will send da a un il i eaches he maximum ai ime allowed and hen i
will disable he anscei e un il i could send da a again.
In case ha con inuous animal moni o ing is needed, he as es bi a e is a ailable
h ough FSK modula ion. The only downsides a e he sho ange and he compa ibili y
Appl. Sci. 2021,11, 1240 8 o 18
wi h comme cial LoRaWAN ga eways. Addi ionally, no ne wo k laye is p o ided so
ou ing is up o he so wa e implemen a ion.
2.3. In as uc u e and Backend
Wea able de ices should wo k ega dless o he in as uc u e a ailable and use i s
ene gy wisely in any condi ion. We conside wo di e en scena ios: a comple ely online
in as uc u e when bo h beacon and s eaming messages can be ecei ed by s a iona y
IP-connec ed ga eways and a po able o line in as uc u e when he e a e no s a iona y
ga eways in ange and jus a shephe d wi h a ga eway ha can ecei e beacons. The sys em
in as uc u e and communica ions low a e shown in Figu e 6.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 8 o 19
mee he egula ion du y cycle; in case we gene a e mo e da a han he numbe o by es
we can send, he de ice will send da a un il i eaches he maximum ai ime allowed and
hen i will disable he anscei e un il i could send da a again.
In case ha con inuous animal moni o ing is needed, he as es bi a e is a ailable
h ough FSK modula ion. The only downsides a e he sho ange and he compa ibili y
wi h comme cial LoRaWAN ga eways. Addi ionally, no ne wo k laye is p o ided so
ou ing is up o he so wa e implemen a ion.
2.3. In as uc u e and Backend
Wea able de ices should wo k ega dless o he in as uc u e a ailable and use i s
ene gy wisely in any condi ion. We conside wo di e en scena ios: a comple ely online
in as uc u e when bo h beacon and s eaming messages can be ecei ed by s a iona y
IP-connec ed ga eways and a po able o line in as uc u e when he e a e no s a iona y
ga eways in ange and jus a shephe d wi h a ga eway ha can ecei e beacons. The sys-
em in as uc u e and communica ions low a e shown in Figu e 6.
Figu e 6. Sys em in as uc u e and communica ion low.
In he i s case scena io, we use a comme cial ga eway ha connec s o a TSP and
send messages o a LoRaWAN Se e . Then, we use MQTT in eg a ions o deli e he da a
o a sel -hos ed da abase, and we p o ide a use dashboa d whe e da a can be isualized.
I is he mos s aigh o wa d way o deploy a LoRaWAN ne wo k. We use an addi ional
LoRa ga eway o ou e he FSK a ic ha canno be decoded by comme cial ga eways
di ec ly o ou da abase.
Fo he second scena io, we de eloped a ga eway using an embedded sys em (Rasp-
be y Pi) wi h headless Linux, whe e we ins all a cus om LoRaWAN se e ha allows
o o line logging and s o age o payloads. GNSS payloads a e decoded and sen o a web
applica ion ha uns an o line maps iewe . I consis s o a Lea le map wi h OSM iles
and Flask se e . Use s can check he las epo s ecei ed on in e ac i e b owse window
in hei mobile o able de ices. A WiFi AP is deployed by he ga eway o p o ide TCP/IP
connec ion wi h he use mobile de ice.
Bo h ga eways use an 8-channel concen a o ca d ha demodula es all channels a
he same ime and p o ides he enc yp ed payload o he hos sys em. LoRaWAN payload
is end- o-end enc yp ed wi h AES c yp og aphic algo i hms [42], based on he AppKey
Figu e 6. Sys em in as uc u e and communica ion low.
In he i s case scena io, we use a comme cial ga eway ha connec s o a TSP and
send messages o a LoRaWAN Se e . Then, we use MQTT in eg a ions o deli e he da a
o a sel -hos ed da abase, and we p o ide a use dashboa d whe e da a can be isualized.
I is he mos s aigh o wa d way o deploy a LoRaWAN ne wo k. We use an addi ional
LoRa ga eway o ou e he FSK a ic ha canno be decoded by comme cial ga eways
di ec ly o ou da abase.
Fo he second scena io, we de eloped a ga eway using an embedded sys em (Rasp-
be y Pi) wi h headless Linux, whe e we ins all a cus om LoRaWAN se e ha allows o
o line logging and s o age o payloads. GNSS payloads a e decoded and sen o a web
applica ion ha uns an o line maps iewe . I consis s o a Lea le map wi h OSM iles
and Flask se e . Use s can check he las epo s ecei ed on in e ac i e b owse window
in hei mobile o able de ices. A WiFi AP is deployed by he ga eway o p o ide TCP/IP
connec ion wi h he use mobile de ice.
Bo h ga eways use an 8-channel concen a o ca d ha demodula es all channels
a he same ime and p o ides he enc yp ed payload o he hos sys em. LoRaWAN
payload is end- o-end enc yp ed wi h AES c yp og aphic algo i hms [
42
], based on he
AppKey pa ame e , known o node and se e . In he online scena io he payload is sen
o he se e o decode i , bu in he o line scena io he hos sys em mus use he key o
dec yp he payload on he ly. The ga eway also un a ull ea u ed LoRaWAN se e o
managemen o de ices, da abase in eg a ion and inpu /ou pu pipelines.
Appl. Sci. 2021,11, 1240 9 o 18
3. Resul s
We chose o spli es in o wo di e en s ages. The i s one will include all es
o cha ac e ize he elec onics, such as powe consump ion, RF pe o mance and digi al
modula ion. A e e i ying ha all hypo heses a e co ec , we ake he senso s o he ields
so we can pe o m eal wo ld measu emen s.
3.1. Labo a o y Tes s
3.1.1. Ene gy and Timing Analysis
The idea behind he p og amming done in his de ice is o ine une pa ame e s o
achie e he be e ange o each use case while main aining he lowes powe igu e.
P e iously we s a ed ha we we e using bo h LoRa and FSK modula ions. Addi ionally,
LoRa packe s a e coded in o LoRaWAN ames, ha allows an easy deploymen in mos
cases. In hese es s we will e i y he comp omise be ween speed and powe consump ion
in wo di e en da a a es (DR1 and DR5) and FSK modula ion. La e , we will check wha
in luences does i ha e in ange i any. Labo a o y es se up comp ise se e al senso nodes
all p og ammed o do he ollowing Sma IMU asks:
-
Fi s (Figu e 7), he senso samples da a om IMU a 12.5 Hz when an e en is
de ec ed, un il desi ed payload leng h is achie ed. Da a a e sen h ough LoRaWAN
a DR5, he as es a ailable a any channel. Then, GNSS ecei e is u ned on un il
ix is achie ed, and i is sen h ough LoRaWAN a DR1, he second slowes . We
chose DR1 o loca ion da a because i le us send da a each minu e i IMU s eaming
is u ned o , o comply wi h he du y cycle shows he cu en while doing a basic
Sma IMU ask.
-
Second (Figu e 8), we s eam accele ome e da a a he highes possible esolu ion
wi h FSK modula ion. This mode is used o de ine ac i a ion h esholds and deciding
on he il e cons an s o he embedded IMU uni egis e s.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 o 19
Figu e 7. Cu en consump ion while sampling IMU a 12.5 Hz and ac i a ing GNSS ecei e .
Figu e 8. Cu en consump ion while s eaming IMU da a sampled a 100 Hz.
The de ice mus be usable on animals ha usually spend a whole yea g azing on
he ield. Acco ding o he p e ious powe consump ion equi emen s we calcula ed he
ba e y li e o each mode as shown in Table 2.
Table 1. Communica ion modes pe o mance analysis.
Modula ion
Payload
Time
Th oughpu
Ene gy pe By e
Link Budge
LoRa (DR1)
8 by es
495 ms
129.3 b/s
712 uJ
148 dB
LoRa (DR5)
228 by es
358 ms
5.1 kb/s
18.1 uJ
138 dB
FSK
61 by es
11 ms
44.4 kb/s
2.1 uJ
123 dB
Table 2. De ice mode ene ge ical analysis.
Mode
TGNSS-
SAMPLE
FSENSOR-
SAMPLE
TREPORT
Ene gy pe
Day 1
Li-SOCl2
Li e ime 2
Alkaline
Li e ime 3
Li-Ion Li e ime 4
Beacon
1 h
-
1 h
31.2 J
9.0 yea s
2.8 yea s
4.2 yea s
Beacon
1 h
-
10′
37.9 J
7.4 yea s
2.3 yea s
3.4 yea s
Figu e 7. Cu en consump ion while sampling IMU a 12.5 Hz and ac i a ing GNSS ecei e .
Ou communica ion model consis o he modes p e iously explained and which
pe o mance is summa ized in Table 1. We can obse e ha each mode is ma ched o he
bes modula ion o he use case. The bes link budge is allowed in GNSS epo s, which
equi es he bes sensi i i y. In mo ion epo s we alue speed o e ecep ion, so we chose
a as e da a a e. Fo moni o ing pu poses when we a e close o he animal, we can use
FSK o he as es a ailable da a a e.
Appl. Sci. 2021,11, 1240 16 o 18
5. Conclusions
In o ma ion and Communica ion Technologies (ICT-based) solu ions a e imp o ing
he p oduc i i y o all indus ial sec o s, e en ag icul u e and li es ock. They should also
imp o e he well-li ing o he people ac oss he Wo ld. Ne e heless, in many cases, he
success o one o hese solu ions is linked o he a ailabili y o communica ion in as uc-
u es ha could p o ide suppo o he “C” o ICT. In de eloped coun ies, whe e we could
assume ha communica ion in as uc u es should ha e a high deg ee o deploymen , ag i-
cul u e and li es ock a e usually ela ed wi h u al a eas whe e hese in as uc u es begin
o loss hei capaci ies. Un o una ely, in he es o he Wo ld, his lack o communica ions
capaci ies begins e en in he big ci ies.
I we pu he ocus on ex ensi e li es ock, we can ind ha , in Eu ope, i is usually
es ic ed o emo e a eas, whe e he communica ions in as uc u es a e no capable o
p o ide any kind o se ices o deploying ICT solu ions. In o he coun ies, we can ind
ex ensi e li es ock also nea he big ci ies, bu his does no gua an ee he a ailabili y o
communica ions se ices (o hey a e bu a high p ice).
This pape has p esen ed a solu ion o dealing wi h his p oblem o lack o s ablished
communica ion in as uc u es o con olling he mo emen s o animals om ex ensi e
li es ock a ms. I is based on he de elopmen o an animal wea able ha is equipped wi h
ine ial senso s, GNSS and wi eless communica ions. I also includes enough compu a ion
capaci y o making adap i e analysis and VQ comp ession ha p o ides high comp ession
a ios wi h good peak signal- o-noise a ios, and allows o eal- ime moni o ing and
logging o ca le’s posi ion and ac i i ies. This wea able has been e alua ed in eal scena ios,
such as moun ains and o es , in he con ex o a p ojec ha aims o moni o animals in
ex ensi e a ming in he no h pa o Spain (in he Py enees a ea, nea he bo de wi h
F ance). This p ojec includes he necessi y o ack he mo emen o he animals o
e alua e hei impac on he plan biodi e si y, as well as he in en ion o i ually educe
he dis ance be ween he animals and he shephe ds.
Au ho Con ibu ions:
Concep ualiza ion, R.C. and F.J.Z.-S.; me hodology, F.J.Z.-S. and T.B.; ha d-
wa e and so wa e, R.C., A.H. and Á.M.; design, T.B.; alida ion, R.C., A.H. and T.B.; w i ing, e iew
and edi ing, All; p ojec adminis a ion and unding acquisi ion, R.C. and F.J.Z.-S. All au ho s ha e
ead and ag eed o he published e sion o he manusc ip .
Funding:
This wo k has been pa ially suppo ed by he A agon egional Go e nmen hough
he p og am o R&D g oups (T27_20R and T59_20R) and by he Ru al De elopmen P og am in
conjunc ion wi h FEADER om EC (GCP2019004100). The wo k o Al a o Ma co and Te esa Blanco
has been pa ially suppo ed by he Spanish Go e nmen , p og am To es Que edo (PTQ2017-09481
and PTQ2018-010045, espec i ely).
Ins i u ional Re iew Boa d S a emen :
E hical e iew and app o al we e wai ed o his s udy, due
o i was accomplished wi hin he con ex o he wo ks ela ed o he Ru al De elopmen P og am,
whe e shephe ds ag eed wi h hese ials. Only a limi ed numbe o animals we e in ol ed in he
s udy, and hey we e no exposed o ha m ul le els o adia ion, as discussed in he ex .
In o med Consen S a emen : No applicable.
Con lic s o In e es : The au ho s decla e no con lic o in e es .
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