Compu a ional In elligence Applied o Moni o Bi d Beha iou
D. F. La ios1, C. Rod íguez², J. Ba bancho1, M. Baena3, F. Simón¹,
J. Ma ín2, C. León1 and J. Bus aman e2
1Depa men o Elec onic Technology, Uni e si y o Se ille, Se ille, Spain
2Depa men o We land Ecology, Doñana Biological S a ion (EDB-CSIC), Se ille, Spain
3ICTS, Singula Scien i ic and Technological In as uc u e, Doñana Biological S a ion, Se ille, Spain
Keywo ds: Neu onal Ne wo k, Compu a ional In elligence, Da a Fusion, En i onmen al Moni o ing, Senso Ne wo ks.
Abs ac : The bes way o ob ain ele an in o ma ion abou he beha iou o animals is di ec obse a ion (o
indi iduals). Howe e , adi ional close-up obse a ions can in e e e on he beha iou , and aking
biome ic measu emen s equi es he cap u e o indi iduals, which also causes s ess. This pape desc ibes
an au oma ic mo o ing sys em o bi ds b eeding in nes boxes. The main goal is o signi ican ly inc ease he
amoun and quali y o da a acqui ed on bi d beha iou wi hou s essing he indi iduals o in e e ing. This
sys em is based in an in e connec ed embedded senso ne wo k, which pe mi s sha ing his aluable
in o ma ion wi h esea che s all o e he wo ld h ough he in e ne . Each de ice o he ne wo k is a sma
nes -box ha allows a c oss- alida ion o senso in o ma ion and da a quali y. This sys em has been
e alua ed o he speci ic case o a lesse kes el b eeding colony in Sou he n Spain. The lesse kes el is an
insec i o ous mig a o y alcon ha eadily accep s nes -boxes. The sys em has been named HORUS and he
esul s ob ained om a yea expe imen demons a e he e iciency o his app oach.
1 INTRODUCTION
Fo zoologis s, one o he mos impo an pe iods o
a bi d is he b eeding pe iod, being his pe iod one o
he mos equen ly s udied. Ma e acquisi ion, nes
de ence, ma e eeding, incuba ion, and chick ea ing
(including p o isioning ligh s) a e s udied in he
su oundings o he nes . Many o hese aspec s help
us unde s and key opics in ecology, such as wha
ac o s in luencing li e ime ep oduc i e success
(LRS: New on, 1992), he pa en -o sp ing con lic
(T i e s, 1974; Schlome e al., 2010), o e olu i e
s able s a egies (ESS: Mayna d-Smi h and P ice,
1973) ega ding sex oles in ep oduc ion (Kokko
and Wong, 2007).
Classic moni o ing me hods ha equi e he
cap u ing o indi iduals o close-up obse a ions
limi he amoun and quali y o da a ha can be
ob ained. The e o e, in his pape a emo e
moni o ing sys em based on sma nes -boxes is
p oposed. These sma nes -boxes allow acqui ing
high amoun o da a wi hou s essing he animals,
ga he ing long- e m and highly eliable in o ma ion
on he species.
The p oposed sys em, called HORUS, pe mi s
ga he ing basic in o ma ion on he iden i y o
indi iduals, s udying i s beha iou and he empo al
changes in indi idual body mass. All his
in o ma ion can be made accessible h ough he
in e ne o scien is all o e he wo ld.
Some o he in o ma ion eco ded by he sys em
can be used o s udy, wi hou in e e ence, he
beha iou o species du ing he b eeding pe iod.
One o he mos impo an biome ic pa ame e s in
bi ds is body mass. I allows us o measu e he
impac o pa en al ca e on b eeding indi iduals.
Manually, i is impossible o de elop a con inuous
moni o ing o his pa ame e . Cap u ing causes oo
much s ess on he indi idual in i s mos sensi i e
pe iod. Ano he impo an pa ame e is he
measu emen o he amoun o ood b ough o he
nes by indi iduals o eed hei o sp ing.
The p oposed sys em allows us o pe o m a
con inuous moni o ing o he ep oduc ion wi hou
s essing he indi iduals, e.g. ob aining eliable body
mass measu emen s e e y ime a bi d en e s o
lea es he nes . The main p oblem ob aining he
measu emen s is he mo emen o he animal, which
p oduces uns able alues. These alues ha e been
calib a ed using a neu onal ne wo k p ocessing,
Figu e 1: Pic u e au oma ically aken by he ou side
came a o he moni o ed colony wi h he HORUS ex e nal
senso s. F om op o down i shows a pigeon, a lesse
kes el male and a emale.
ob aining high accu a e measu emen s.
The es o he pape is o ganized as ollows:
Sec ion 2 ocuses on he lesse kes el beha iou
s udy, especially compa ing a adi ional app oach
e sus au oma ed da a eading. Sec ion 3 b ie ly
desc ibes he HORUS sys em in as uc u e. A
de ailed desc ip ion o he in o ma ion ea men
de eloped in his p ojec can be ound in sec ion 4.
The esul s ob ained wi h ou sys em a e shown in
sec ion 5. Finally, sec ion 6 sum-up conclusions and
p o ides ema ks.
2 LESSER KESTREL BREEDING
BEHAVIOR STUDY
habi a s (Pee and Gallo-O si, 2000). The species is
also sensi i e o clima e wa ming (Rod iguez and
Bus aman e, 2003). So i makes o a good model
species o s udy he impac o global change on an
endange ed species.
2.1 T adi ional Moni o ing
The “Es ación Biológica de Doñana” (EDB-CSIC)
has been moni o ing lesse kes el colonies since
1988. I has been eco ding colony occupancy and
b eeding success in e ms o numbe o ledglings
and p opo ion o success ul nes s. Rega ding
indi idual moni o ing, bi ds ha e been ma ked wi h
me al and PVC ings wi h a unique alphanume ic
code ha allows iden i ying indi iduals by using
elescopes. Biome ic measu es we e aken
spo adically o all ma ked indi iduals when
cap u ed. Due o e hical easons, howe e , he
numbe o cap u es in he nes is limi ed ( he cap u e
al e s b eeding beha iou and may jeopa dize he
su i al o he o sp ing) and he majo i y o
esigh ings we e made wi h elescopes. This causes
high di e ences in he equency o ecap u es
among indi iduals mainly due o di e ences in
de ec abili y. In a classic da a base moni o ing,
2,135 bi ds igu ed as ecap u ed (including
esigh ings wi h elescope). On a e age hey we e
cap u ed 3 imes on he same b eeding season
( ange: 1-70). In app oxima ely 45% o cases, body
mass was measu ed and maximum numbe o
measu emen s pe bi d and yea was 4.
Because o ha , he pa e n o body mass
a ia ion o b eeding adul s om a i al o he
colony in mid-Feb ua y o he end o he nes ling
pe iod in mid-July is no well known. Acco dingly,
we ha e no in o ma ion on he pa e n o in aday
a ia ion in body mass.
The p oposed emo e moni o ing sys em aims o
b idge he abo e de ailed logis ic and e hic gaps,
hus allowing us o ge enough in o ma ion o
documen bo h pa e ns.
2.2 Au oma ed Da a Reading
Habi a moni o ing has e ol ed g ea ly e olu ion
due o he boom o senso ne wo ks echnology.
Se e al consequences ha e been caused due o
he inc ease o senso s: Fi s ly he quali y o
in o ma ion g ows in ime and on he spa ial
domain; secondly he possibili y o ansmi ing he
measu ed da a h ough he ne wo k inc eases he
need o ha ing high bandwid h communica ions;
and hi dly, i o he educ ion o he cos o he da a
The lesse kes el (Falco naumanni, igu e 1) is a
small (body mass a ound 150 g ams) mig a o y
alcon inhabi ing open landscapes (C amp and
Simmons, 1980). I is a colonial species ha b eeds
in old buildings, such as chu ches o cas les wi hin
u ban a eas in Wes e n Eu ope. The species
expe ienced a ma ked decline in i s Wes e n
Palea c ic b eeding ange in he middle o he 20 h
cen u y (C amp and Simmons, 1980; Bibe , 1990).
Conside ed p e iously one o he mos abundan
ap o s in Eu ope (Bijle eld, 1974) he lesse kes el
became ex inc in se e al coun ies (e.g. Aus ia,
Hunga y, Poland) and p ac ically disappea ed in
o he s (e.g. F ance, Po ugal, Bulga ia).
Medi e anean Spain cons i u es i s s onghold in
he Wes e n Palea c ic (Bibe , 1990). Howe e , he
Spanish popula ion also su e ed a p ecipi ous
decline, as i d opped om an es ima ed 20,000–
50,000 pai s in he 1970s (Ga zón, 1977) o 4,000–
5,000 b eeding pai s in 1988 (González and Me ino,
1990). This decline has been a ibu ed o he
educ ion in bo h he ex en and quali y o o aging
Figu e 2: HORUS Ne wo k scheme.
s o age makes possible o sa e huge amoun s o
da a.
All hese consequences imply some nega i e
e ec s: an inc ease o da a a ic and inc ease o
powe consump ion.
Some au ho s ha e aken hese e ec s in o
accoun (Cook, 2007; S idha , 2007) and ha e
exp essed he need o employ p ocessing echniques
in o de o educe hese handicaps.
The e a e di e en app oaches o habi a
moni o ing. Some o hem use wi eless senso
ne wo k echnology in o de o acqui e and p ocess
he physical in o ma ion (Ga cía-Sánchez e al,
2010; Handcock e al, 2010; Valen e e al, 2011;
Ca ullo e al, 2009). O he s ocus on he needed
middlewa e ha allows access o he physical
in o ma ion (Hwang e al., 2010; Fa shchi e al.,
2007).
In ou app oach, bo h aspec s a e conside ed.
3 HORUS INFRAESTRUCTURE
The p oposed in as uc u e is a dis ibu ed sys em
as igu e 2 depic s. This igu e shows he mos
impo an de ices o he p oposed a chi ec u e.
These de ices will now beb ie ly desc ibed.
3.1 Ne wo k In as uc u e
The HORUS in as uc u e is made up o di e en
subsys ems in e connec ed h ough a low da a a e
communica ion ne wo k.
This ne wo k has been designed conside ing he
ollowing es ic ions:
The de ices ha p o ided in o ma ion o he
ne wo k a e deployed in a sp ead way wi hou
any p e ious planning.
The da a a e associa ed wi h he da a sou ces is
low (< 250 kbps)
The sys em could be easily scalable.
The ne wo k used in HORUS can be accessible
h ough di e en physical media (wi eless o wi ed
based).
Robus ness o he ne wo k is e y impo an , o
he p oposed applica ion: du ing he b eeding pe iod,
i is no possible o ealize main enance asks,
because i can dis u b and s ess he colony. All
de ec ed ailu es would be epai ed in win e , a e
he bi ds ha e le he colony.
3.2 Base S a ion
The p ocess se e is a sys em ha o e s he
ollowing se ices:
Da abase se e .
Moni o ing and con ol sys em.
Remo e con ol access.
The da abase s o es all he his o ic senso s
in o ma ion ga he ed om he sys em.
The moni o ing con ol sys em is a p og am
esponsible o adding addi ional aluable
in o ma ion o he senso measu emen s, such as
in o ma ion abou he nes sende , a ime s amp
egis e o a con ol sequence, ha pe mi s
Figu e 3: Nes cabine .
de e mining he numbe o loss packe s. This sys em
s o es he in o ma ion in he da abase.
Remo e access con ol o e s he cloud se ices
o emo e use s, such as biologis s. These se ices
pe mi emo e access o he senso s da abase.
3.3 Sma Nes -Boxes
The sma nes -boxes a e he main componen s o
he moni o ing sys ems. I consis s o he nex wo
blocks:
The nes cabine .
The elec onic sys em
The nes cabine (Figu e 3) is di ided in o wo
pa s: a co ido and he incuba ion chambe . This
nes cabine has a sma design o ensu e ha he
bi ds pass he co ido each ime hey en e o lea e
he nes . The ad an age o his is o allow he
dis ibu ion he senso s in a small a ea ( he co ido )
whe e he animal is o ced o pass and, he e o e, i
ensu es ob aining he senso in o ma ion.
The elec onic sys em (Figu e 4) o each sma
nes -box is accomplished wi h he nex subsys ems:
3.3.1 Mic ocon olle Boa d
This boa d is based on he ATmega2560, an
economic, low powe and obus mic ocon olle . I
con ols and p ocesses he nes ’s senso in o ma ion.
This boa d communica es wi h senso s and o he
componen s, and p ocesses he collec ed in o ma ion
ha is sen o he p ocess se e o e he
communica ion in e ace.
The p og am implemen ed in he mic ocon olle
pe o ms he ollowing asks:
Communica es wi h he p ocess se e o e a
communica ion in e ace, and synch onize
clock ime wi h his.
Figu e 4: A chi ec u e o he elec onic sys em.
Checks in a- ed ba ie s. Each nes -box has
wo in a- ed ba ie s a bo h ex emes o he
co ido . The sequence in which hey a e
ac i a ed indica es whe he bi ds en e o
lea e he nes -box.
Checks i he RFID eade has ead a code om
inged kes els.
Ob ains he body mass measu emen om a
digi al balance.
Reads he empe a u e and humidi y o he nes .
Con ols he RFID eade o iden i y
indi iduals.
3.3.2 Senso s Boa d
A senso boa d adap s he logic le els om he nes
senso s o he mic ocon olle boa d’s equi emen s.
All he nes ’s senso s a e sp ead on o he
co ido o he nes . Posi ions o senso s a e
designed o ensu e ha e e y ime he bi ds pass he
co ido he sys em egis e s a leas one eco d pe
senso .
The deployed senso s a e:
A digi al balance. I allows a maximum weigh
o 600 g . and an accu acy o 0.01 g , o e ing
16 measu es pe second. I pe mi s ge ing an
es ima e o he body mass o he indi iduals in
mo emen . Al hough he pan is ound, i has
been modi ied o be ec angula in o de o i
he shape o he co ido .
(a)
(b)
(c)
(d)
Figu e 5: Di e en weigh pa e n Y-axis, weigh in g ams. X-axis, samples.
An in eg a ed empe a u e senso loca ed in he
window. I is calib a ed o ope a e in
en i onmen al empe a u e ange. I is used o
measu e he nes empe a u e.
An in eg a ed humidi y senso . I is used o
measu e he nes humidi y.
Two in a- ed ba ie s, used o ace he
di ec ion o bi ds’ mo emen s.
A RFID eade . I communica es ia RS-232C
and o e s a eading on he unique ID o a
agged bi d, when i is passing h ough he nes
en ance. This sys em has mechanisms o a oid
collisions, pe mi ing ope a ion e en when
he e a e se e al bi ds a ound he en ance.
A Se omechanism. I is used o emo ely
cap u e bi ds when hey en e in he nes -box.
4 TREATMENT OF THE
INFORMATION
As desc ibed be o e, e e y nes -box p o ides he
ollowing in o ma ion:
Measu emen s o body mass: The digi al
balance used o e s 16 measu emen s pe
seconds wi hou calib a ion and classi ies
measu emen s as s able o uns able.
IR in o ma ion: These senso s pe mi
de e mining i he bi ds go in o o go ou o he
nes .
RFID in o ma ion: I pe mi s a ibu ing he
in o ma ion o o he senso s o an indi idual
bi d.
All his in o ma ion is ob ained om he senso s
deployed in e e y nes -box. The senso s o e
ele an in o ma ion on he indi idual b eeding a
he colony o he biologis s ha s udy hem. This
in o ma ion, excep he body mass, canno be added,
as hey in o m abou disc e e e en s. The e o e, his
in o ma ion is sen di ec ly o he da abase wi hou
any local p ocessing o ea men .
On he o he hand, he digi al balance o e s a
high amoun o in o ma ion. I s equency o
measu emen is much highe han he body mass
e olu ion o he animal. i.e., he animal body mass
e olu ion has mo e ine ia han he weigh p o ided
by he balance. Due o his, i is possible o pe o m
a da a p e-p ocessing abou weigh in o ma ion,
educing wi h ha he amoun o in o ma ion send o
he cen al p ocessing.
4.1 Weigh P e-p ocessing
The algo i hm desc ibed in his pape , is ocused on
locally p e-p ocessing he weigh in o ma ion, o
educe he amoun o unnecessa y in o ma ion and
inc ease i s accu acy. I is designed o be execu ed in
each nes -box, in he mic ocon olle boa d. I has
been designed o ul il he nex goals:
To educe he amoun o useless in o ma ion in
he da abase using local p e-p ocessing.
To inc ease he accu acy o he measu emen s,
calib a ing he esul s ob ained.
To inc ease accu acy o he communica ion
ne wo k, educing he amoun o packe loss,
he delays and he collisions.
To inc ease he amoun o use ul in o ma ion in
he da abase, es ima ing a body mass om
each pa e n wi h non-s able measu emen s.
To pe mi i s execu ion on de ices wi h low
esou ces.
To inc ease he accu acy a a e calib a ion is
necessa y. The balance used o e s measu emen s
wi hou a a e calib a ion. This calib a ion would be
ob ained consul ing he body mass measu ed by he
balance, when he e is no animal on he pan i.e.,
when he measu ed weigh is below a ce ain

es ima ed h ough a compu a ional in elligence
algo i hm. In bo h cases, only one selec ed weigh
pe pa e n is sen o he da abase. These selec ed
weigh s a e calib a ed wi h he a e, be o e sending
hem.
The p oposed algo i hm is summed-up in he
nex pseudo-code:
while 1:
wai new(meas_weigh );
i meas_weigh >= h eshold
weigh [i]:=meas_weigh – a e;
inc ease I;
i s able(meas_weigh )==1
s able :=1;
end i
else
i i!=0
i s able==1
es _weigh :=a e age(
s able_weigh );
s able:=0;
else
es _weigh :=model(weig h);
end i
send_se e (es _weigh );
i:=0;
else
new_ a e:=meas_weigh ;
a e:=I e _RMS(p e _ a es,
new_ a e);
end i
end i
end while
4.1.1 Applying Machine Lea ning o
Weigh Recogni ion
Fo his applica ion, an algo i hm has been
e alua ed. Ini ially, an algo i hm wi hou machine
lea ning based on he di e ences be ween
consecu i es measu emen s has been conside ed.
This algo i hm conside s a weigh s able i he e a e
mo e han a ce ain numbe o measu emen s o he
same weigh . This is simila o he in e nal algo i hm
o he balance o agging measu emen s as s able o
uns able, bu i is less es ic i e: he balance
equi es a high numbe o measu emen s wi h he
same alue o conside a measu emen s able. I
pe mi s he e ie al o some weigh s om he
uns able pa e ns, bu i ails wi h complex pa e ns.
Ou p oposal o using compu a ional in elligence
(machine lea ning) inc eases he pe cen age o
success.
Machine lea ning is widely used in pa e n
ecogni ion, bu i s use in animal moni o ing is less
widesp ead. O he supe ised lea ning echniques
apa o he neu onal ne wo k ha e been conside ed.
h eshold. This h eshold can be ob ained as a
unc ion o he body mass o he animals o moni o .
In ou deploymen o he Lesse Kes el (wi h a
body mass ange o 100-190 g) a h eshold o 100
g ams o has been used.
In he eal deploymen we ha e p o en ha he
a e does no change signi ican ly du ing a yea .
The e o e, measu ing he a e only once pe day
o e s enough accu acy o he p oposed sys em.
On he o he hand, as desc ibed be o e, he
balance o e s 16 weigh measu emen s agging
hem e e y second by i sel as s able (i.e.,
measu emen s ha emain a same alue du ing a
long pe iod o ime) o uns able. Bu bi ds usually
do no pass o e he balance slow enough o ob ain
s able measu emen s. This causes he da abase o
ha e a high amoun o he in o ma ion as uns able
measu es. In he eal p o o ype only abou 15.25%
o he measu ed pa e ns had a s able measu emen ,
conside ing a pa e n as he collec ion o
measu emen s ob ained om he ime he bi d ge s
on he balance (i.e., when he balance acqui es a
weigh o e he h eshold) un il he animal ge s ou
o balance (i.e., when he balance acqui es du ing 5
seconds weigh s below he h eshold). Fig. 5 shows
di e en examples o weigh pa e ns ob ained in he
eal deploymen wi h hese condi ions.
This igu e shows di e en eal weigh pa e ns
ob ained om he same animal in di e en days.
Only pa e n (a) has some s able measu emen .
These s able measu emen s ha e been compa ed
wi h measu emen s o he animal done manually
cap u ing he bi d. The s able a e measu emen s a e
co ec , bu no equen enough o ob ain a long
e m sequence o body mass empo al change o he
bi ds a he colony.
To sol e his, a compu a ional in elligence
algo i hm o es ima e he body mass o animals om
he pa e ns wi h non-s able weigh s has been
de eloped, inc easing he amoun o use ul
in o ma ion. This neu onal ne wo k algo i hm is
desc ibed below.
Ini ially, he sys em has been designed o s o e,
in he cen al se e , all weigh measu emen s o he
pa e n acqui ed by he balance, s able o uns able,
bu i causes high bandwid h consump ion in he
communica ions in e ace.
To educe he amoun o useless in o ma ion, he
p oposed algo i hm only sends one es ima ed weigh
o he da abase o each measu ed pa e ns. I he
pa e n has some s able measu emen s, he es ima ed
weigh sen o he cen al se e will be he a e age
o he ob ained s able measu emen s. I no
measu emen s o he pa e n a e s able, he weigh is
Non supe ised echniques, such as Sel -O ganized
maps (SOM, Kohonen, 1990) o Suppo Vec o
Machine (SVM, Co es 1995) we e disca ded,
because we ha e some s able measu emen s ha
pe mi pe o ming aining.
One example o he conside ed supe ised
machine lea ning echniques is he use o A i icial
Neu o-Fuzzy In e ence Sys ems (ANFIS; Jang,
1993). ANFIS has many applica ions in he
e alua ion o complex sys ems, bu i equi es a
p e ious knowledge o he sys em o design he ules
and he ini ial sys em. This sys em was disca ded;
due o he complex o ms o he pa e ns ha do no
easily pe mi acqui e his ini ial sys em.
Expe sys ems o case based expe s sys em
we e no conside ed, due o he amoun o p e ious
in o ma ion ga he ed om he sma nes -box was
no su icien o hese kinds o sys ems.
Fo hese easons, a neu onal ne wo k model was
inally chosen. The a iables used as inpu s o he
model a e as ollows:
Max_1: The mos epea ed weigh in a pa e n
( he la ges i mul iple).
N_1: Numbe o epe i ions o he p e ious
a iable in a pa e n.
Max_2: The second mos epea ed weigh in a
pa e n ( he la ges i mul iple).
N_2: Numbe o epe i ions, in a pa e n, o he
p e ious a iable.
Max_C1: The mos consecu i ely epea ed
weigh in a pa e n.
NC_1: Numbe o epe i ions o he p e ious
a iable in a pa e n,
Max_C2: The second mos epea ed weigh ,
consecu i ely, in a pa e n.
NC_2: Numbe o epe i ions, in a pa e n, o
he p e ious a iable.
N_EL: To al numbe o weigh measu es in a
pa e n.
In o de o ob ain hese pa ame e s, a pa e n
wi h a leas 5 weigh measu emen s is needed. As
Table 1: Analysis o he da abase.
Cap ion
Value
Measu emen weigh
2583565
Numbe o pa e n
51517
Pa e ns wi h s able weigh s
7856
A e age pa e n ime
23,18 seconds
Days o es
399 days
an alue ou pu , he neu onal ne wo k model o e s a
alue, called “Ou pu weigh ”. This ou pu e lec s
he es ima ed weigh o he neu on model and i is
he in o ma ion sen h ough he ne wo k o he
se e da abase.
The s eps execu ion o his neu onal ne wo k
model is summed-up in he nex pseudo-code, whe e
he neu onal ne wo k is he execu ion o a h ee
laye ne wo k.
Neu onal ne wo k needs a se o pa ame e s o
i s aining. These se s ha e been ob ained o each
pa e n wi h s able measu es, by execu ing he
ollowing s eps:
S ep 1: A a iable name “Ta ge weigh ” was
de ined o e e y pa e n. This a iable s o es he
a e age alue o all s able weigh s. This is he a ge
esul o he aining o he neu onal ne wo k.
S ep 2: Fo e e y pa e n, a new pa e n has been
c ea ed, elimina ing all s able measu emen s.
S ep 3: The inpu s ha e been ob ained om his
new pa e n wi hou s able alues.
S ep 4: The inpu alues o each pa e n we e
s o ed, oge he wi h hei espec i e Ta ge weigh
in o a able, named “T aining in o ma ion”
Wi h hese ables wo se s o in o ma ion we e
ob ained, one o aining and he o he o
e alua ing he accu acy o he sys em. In o al, he
aining in o ma ion able has 1163 se s o alues.
50% o hese alues ( andomly selec ed) we e used
o aining, and he o he 50 % we e used o
alida ion.
5 SIMULATION, TESTS AND
RESULTS
The esul s ob ained wi h his sys em can be
classi ied in wo ypes: analysis o he ne wo k
pe o mance and weigh es ima ion accu acy
ob ained wi h he eal deploymen .
This sec ion summa izes hese wo ypes o
esul s.
5.1 Ne wo k Pe o mance
Du ing he i s yea o he deploymen (2010), he
p o o ype was sending in o ma ion om all senso s,
e en he 16 eco ds pe second o he balance, o he
da abase o he cen al se e . The main
cha ac e is ic o he ga he ed in o ma ion in he
da abase is summa ized in able 1.
A e a yea o deploymen , he analysis o da a
allowed us o de ec some ne wo k con lic s. Fo
example, i di e en nes -boxes a e acqui ing
weigh s om indi iduals a he same ime, hey a e
compe ing o con ol o he bus, causing da a
collisions and delays in ansmi ing in o ma ion.
Table 2: Cos pe message wi h CC2420 Radio
anscei e .
Cap ion
Ene gy (J)
Wi hou da a usion
255.3
Wi h da a usion
0.608
The p oposed sys em allows a oiding hese
con lic s, using he p oposed da a usion.
In his sec ion we a e going o quan i y he
ad an age o da a usion agains he classical
cen alized sys ems. Due o ha , in his kind o
applica ions i is impo an o educe he use o
bandwid h as much as possible.
The analysis o da abase in o ma ion has been
summed-up in he able 1. I shows ha only a
15.25% o he acqui ed pa e ns ha e any s able
measu emen .
Knowing ha he balance o e s 16 Samples Pe
Second (SPS), he a e age payload o he
applica ion laye pe pa e n o he sys em wi hou
da a usion can be ob ained wi h he equa ion 1.
,16 · · ·
T aw SPS T By es msg
N P N N
(1)
Whe e
,T aw
N
is he numbe o by es o send
pe day a applica ion laye ;
T
P
is he leng h o he
pa e n in seconds;
By es
N
is he numbe o by es o
send. 16 by es in his case and
msg
N
is he numbe
o messages pe day.
On he o he hand, wi h he p oposed algo i hm,
only one message pe pa e n is sen . In his case, he
payload pe pa e n can be ob ained acco ding o
equa ion 2.
,·
T aw By es msg
N N N
(2)
This shows ha he amoun o in o ma ion sen
o he da abase a ies in unc ion o he numbe o
pa e ns and he leng h (in ime) o he pa e n.
Figu e 6 depic s hese esul s.
Concluding, he local p ocessing pe mi s one o
d as ically educe he used h oughpu o he
ne wo k, especially in days wi h a high numbe o
pa e ns.
This da a usion and agg ega ion scheme is
especially impo an o i s use in low bandwid h
sys ems, due o i pe mi ing one o sa e ene gy.
Wi h he p oposed sys em, only one message pe
pa e n is sen , ins ead o 16 measu emen s pe
second du ing he cap u e o he pa e n. These
esul s a e summed-up in able 2. They conside he
a e age pa e n leng h o 23.18 seconds, i.e. he
a e age ime while he bi d is on he balance.
Wi h hese condi ions and wi h he CC2420
adio anscei e , widely used in wi eless senso
ne wo k, pe mi sa ing 99.76 % o he ene gy used
in da a ansmissions, conside ing a powe
consump ion o 38mW in ansmission mode
(Polas e e al, 2005.
Using all weigh pa e ns ob ained in he yea
2010, he p oposed body mass es ima ion algo i hm
pe mi s he e ie al o a ound 56.21% o he
pa e ns wi hou s able measu emen s.
This is a good esul ha pe mi s us o ob ain an
a e age o 4 body mass es ima ions pe day and
nes , which is 4 imes highe han using only
pa e ns wi h s able measu emen s. I pe mi s o
ha e a con inuous acing o body mass in
indi iduals.
As a conclusion, he local p ocessing pe mi s us
o d as ically educe he used h oughpu o he
ne wo k, especially in he days wi h a high numbe
o pa e ns.
5.2 Body Mass Es ima ion Accu acy
Based on he aining and e i ica ion se desc ibed
in sec ion 4.1.1, some analysis has been done o he
p oposed algo i hm o body mass es ima ion.
Wi h he e alua ion se , he sys em o e s an
accu acy o 98.7%, i.e., an e o in he o de o 2
(a)
(b)
Figu e 6: By es pe day send, a applica ion laye , o he cen al se e . (a) Wi hou da a usion. B) Wi h da a usion.
Figu e 7: Neu al ne wo k model: impo ance o he
a iables in he calcula ion o he es ima ed weigh s.
Figu e 8: G ain ele a o used o he p o o ype
ins alla ion.
g ams, which is qui e small conside ing he ypical
body mass o hese animals (150 g ams).
This accu acy pe mi s analysis o a long se ies
o he e alua ion o empo al changes in body mass,
and some imes o de e mine he body mass o p ey,
when bi ds b ing medium-sized animals o he nes
o eed he nes lings.
F om he aining p ocedu e, an analysis o he
impo ance o he inpu pa ame e s in ela ionship
wi h he a ge body mass can be ob ained. Figu e 7
shows hese esul s. This analysis concludes ha he
selec ed pa ame e s a e alid o e ec i ely es ima e
he body mass o animals.
5.3 Real Deploymen
A p o o ype, o a eal alida ion o he p oposed
sys em, has been deployed in he g ain ele a o o
“La Palma del Condado (Huel a P o ince, SW
Spain” ( igu e 8). A his si e, esea che s o he
Es ación Biológica de Doñana ha e been s udying
he lesse kes el colony since 1994. A his colony,
kes els nes ed on he windowsills o he g ain
ele a o ha a e shel e ed and su icien ly enclosed
o make a sui able nes ing si e.
Fo he p o o ype ins alla ion we selec he
windows on he 6 h loo o he building whe e
sma nes -boxes we e ins alled, and eadily
accep ed, by kes els du ing p elimina y checking (3
and 4 nes -boxes du ing 2008 and 2009,
espec i ely) and also when he de ini i e p o o ype
ins alla ion was made in 2010.
Nes -boxes a e placed in all he windows along
he six h loo . They a e named “6XY”, whe e X
e e s o he ca dinal poin and Y is an o dinal
numbe . Each box has wo sepa a e en ances and
wo incuba ion chambe s (I. le and D: igh ) in a
symme ical dis ibu ion. En ances a e placed a he
ex emes o he box o a oid po en ial agg essions
be ween neighbou s, hus maximizing he numbe o
po en ial b eeding pai s. None heless, he igh pa
has no been opened ye .
The esul s p o ided by he sys em a e s ill being
analysed by biologis s. Howe e , in i s cu en s a e,
i is possible o ob ain some conclusions:
18 o he 20 ins alled nes s-boxes we e used by
b eeding kes els. This leads o he conclusion
ha he p oposed sys em e ec i ely allows one
o ga he a high amoun o in o ma ion abou
he beha iou o b eeding indi iduals wi hou
s essing hem. I he nes and i s senso s we e
hos ile, i would no ha e been chosen by lesse
kes els b eeding pai s.
A p elimina y esul o he con inuous
weigh ing o indi iduals will allow he
esea che s o es ima e he cos o b eeding in
e ms o body mass. This cos is di ec ly
associa ed wi h he o aging ips o eed he
nes lings.
The lesse kes el mainly eeds on insec s, bu
some imes can ca ch sligh ly bigge p ey, such
as small oden s, bi ds o liza ds (wi h a ound a
dozen o g ams). The p oposed sys em would
pe mi an analysis o he equency o big p ey
cap u es.
6 CONCLUSIONS
The main goal o he p oposed sys em is o use
cu en echnological ad ances in a eal-wo ld
applica ion in he a ea o Biodi e si y Conse a ion
o s udy how global clima e change could a ec a
colonial and endange ed bi d species.
The esul s ob ained conclude ha he p oposed
sys em would pe mi i s use in a sys em wi h low
esou ces and wi h a low bandwid h usage.
The p o o ype deployed in Spain o e alua ion