This document discusses infrastructure for urban-scale Internet of Things (IoT) sensing. It describes an interdisciplinary team that develops IoT sensors, cloud infrastructure for data storage and analysis, and applications like traffic monitoring and citizen well-being tracking. The team operates large vehicular networks of over 600 vehicles for sensing. They have also developed low-cost environmental and health sensors, and platforms for crowdsourced data collection from citizens on topics like mood, transportation habits and bus driver stress. The goal is to use IoT technologies to collect a wide range of urban data at scale for research purposes.

1. IoT
for
Smart
Ci-es:
Infrastructure
for
Urban
Scale
Sensing
Ana
Aguiar,
ana.aguiar@fe.up.pt
FEUP,
Ins-tuto
de
Telecomunicações
Centro
de
Competências
para
Cidades
do
Futuro

2. CC
Future
Ci-es
>
Inter-­‐disciplinary
team

3. Cloud

4. Urban
IoT
Sensing
Storage
Management
SenseMyCity
UrbanSense
BusNet
Heterogeneous Connectivity
Informa-on
Data
Micro-servicesTraffic
Flow
Calibra-on
…
Stress
InteroperabilityREST
FI-­‐WARE
ETSI
M2M

5. BusNet
and
HarborNet
Vehicular
Ad-­‐Hoc
Network
• Largest
vehicle-­‐to-­‐vehicle
(V2V)
testbed
in
the
world
– 600
vehicles
• Two
independent
testbeds
– BusNet:
garbage
trucks,
city
sweepers
– HarborNet:
trucks
and
boats
• Joint
work
– Universidade
do
Porto
– Universidade
de
Aveiro
– VeniamWorks
– InsLtuto
de
Telecomunicações
20/09/16
5

6. 40-­‐70%
Wi-­‐Fi
offloading
>150,000
Unique
users
1.3
million
Internet
sessions
2.3
TB
Monthly
Internet
traffic
>260k
hours
Surfing
Lme
16
minutes
Average
session
VANET
>
STCP
free
WiFi
September
2014
–
September
2015
Source:
Veniam

7. Bus
Mobility

8. WiFi
ConnecLons

9. UrbanSense
• Data
CollecLon
Units
• Developed
within
the
project
jointly
with
industrial
partner
• Low
cost
sensors
• Processing
board:
Raspberry
Pi
• Local
processing
and
storage
– Intermident
communicaLons
– Capability
for
local
data
analysis
• CondiLoning
circuit
electronics
– Control
Board
• Custom
made
expansion
board
for
RPi
– Sensor
board
• Exposed
to
elements
• Enclosure
and
shield
20/09/16
9
Noise
Air
quality
,
RH,
temperature
Processing,
storage
and
control
Solar
RadiaLon
sensor
WiFi
interfaces
Weather
StaLon

10. Architecture
and
Ecosystem
Sensor
1
Sensor
1
Sensor
1
Control
Board
RPi
Data
CollecLon
Unit
Fixed
WiFi
BusNet
Cellular
Backhaul
API
Storage
Backoffice

11. Sensors
in
a
Flowerpot

12. Data
Quality
via
CalibraLon
In
the
lab
On
the
street

13. Deployment
Status
Jan
2016

14. What
is
a
crowdsensor?
Internet
of
Things
Crowdsensor
Leverage
the
power
of
the
crowd
to
sense
large-­‐scale
human
processes

15. Data
Privacy
• ParLcipants
fill
out
informed
consent
form
• ParLcipants
can
access
their
own
data
– Pseudo-­‐anonymisaLon
to
enable
access
to
own
data
– We
cannot
idenLfy
the
parLcipant
(hashed
email)
• OpenID
authenLcaLon
• Data
removed
aker
3
years
• We
only
allow
anonymised
datasets
– K-­‐anonymity
– Avoid
simultaneous
Lme
and
locaLon
– Coarse
Lme
or
locaLon

16. Data
Ownership
• Full
access
to
own
data
– Visualise
– Download
– Delete…
Yes,
really
• AnyLme,
over
web
interface

17. On
an
Urban
Scale
Origin-­‐DesLnaLon,
by
Daniel
Moura

18. On
an
Urban
Scale
Ecological
Footprint,
by
João
Rodrigues

19. A
Research
Tool
• Procedure
and
plaporm
result
from
long
iteraLve
design
involving
engineers,
psychologists
and
parLcipants
Demographic
quesLonnaires
• Age
• Weight
• Experience
Vital
Jacket
• Real-­‐Lme,
medical
grade
electrocardiogram
(ECG)
• 500Hz
sampling
rate
• 8
bits/sample
• 3-­‐axis
accelerometer
• Event
push
budon
Recall
Joint
work
with
João
Paulo
Cunha
(INESC
TEC)
and
Mariana
Kaiseler
(leeds
Becked
University,
UK)

20. On
an
Urban
Scale
Fuel
ConsumpLon,
by
Daniel
Moura
Bus
driver
stress
by
João
Rodrigues

21. jcunha@ieee.org
21
Vital
CrowdSensing
>
SenseMyCity
+
SenseMyHeart

22. A
Research
Tool
• Awareness
of
ciLzen’s
mood
– With
CrisLna
Queirós,
FPCEUP

23. On
an
Urban
Scale
Mood
map,
by
João
Rodrigues

24. SenseMyFEUP:
Origin
of
Trips
To
FEUP
Joint
work
with
Cecília
Silva,
CITTA
(FEUP)
and
Comissariado
para
a
Sustentabilidade

25. SenseMyCity
Datasets
SenseMyCity
SenseMyMood
SenseMyFEUP
Trips
8929
10500
28763
Unique
users
182
211
239
GPS
points
15656043
2979585
13786878

26. A
Lookout…

27. Thank
You!
Ana
Aguiar
ana.aguiar@fe.up.pt