This presentation was given at Jornadas de Ciência de Informação 2017.

1. IoT for Smart Cities
Ana Aguiar
ana.aguiar@fe.up.pt
Faculdade de Engenharia UP
Instituto de Telecomunicações

2. Internet of Things

3. IoT for Smart Cities
• Understand and monitor intrinsic processes
– Improved spatio-temporal granularity
– Wider availability of data/ information
– More informed decision making
– Monitor impact of measures
• Improve relationship with citizens
– More comfortable/ easier communication
• Real-time management of urban area

4. BusNet
Susana Sargento, André Cardote, João Barros et al, Veniam

5. BusNet

6. Congestion Red Spots

7. Bus Passenger Flow

8. UrbanSense
Tânia Calçada, Carlos Penichet, Yunior Luis, Bruno Fernandes, Tiago
Lourenço, Diogo Guimarães, Daniel Moura, Sérgio Crisóstomo,
Cecília Rocha, Sofia Sousa, João Barros, Ana Aguiar

9. UrbanSense
6/30/2017 9

10. 6/30/2017 10

11. Road
Side
Unit
Fiber
WiFi
WiFi
WAVE
Data
WAVE
Information
Data
Micro-services

12. (Some) Validation
Temperature Correlations
> 90%
> 80%
> 70%
> 60%
< 60%

13. (Some) Validation
Luminosity Correlations
> 90%
> 80%
> 70%
> 60%
< 60%

14. (Some) Validation
Noise Correlations
> 90%
> 80%
> 70%
> 60%
< 60%

15. (Some) Validation
Ozone Correlations
> 90%
> 80%
> 70%
> 60%
< 60%

16. Average Temperature

17. Air Quality and Luminosity Before and During Forest Fires August 2016

18. DCUs Locations
2016 November 23
Rua das Flores Bolhão Trindade Casa da Música
UrbanSense Platform
Urban noise: are the cities really ‘smart’?, Cecília Rocha, FEUP

19. Preliminary Results
(annual daily average)
Rua das Flores Bolhão Trindade Casa da Música
Hour Global Average Sunday Monday Tuesday Wednesday Thursday Friday Saturday
0 62.3 65.3 61.6 61.1 60.6 61.5 61.3 64.7
1 58.8 63.5 58.9 57.9 55.8 57.1 57.4 61.3
2 56.9 60.4 57.3 57.0 54.5 55.0 55.1 59.1
3 54.9 53.2 54.6 55.9 53.5 53.7 54.8 58.6
4 57.0 58.7 55.0 57.3 55.9 56.6 56.0 59.3
5 61.6 60.3 65.0 61.8 60.1 60.6 61.7 61.8
6 66.6 62.0 70.0 67.9 66.7 66.4 68.0 65.2
7 69.8 64.0 73.5 72.1 71.3 70.6 70.7 66.5
8 71.1 66.0 73.8 72.9 72.5 72.3 71.3 68.7
9 71.7 68.8 73.7 72.7 72.2 71.9 72.0 70.4
10 71.6 69.3 73.4 72.4 71.8 71.6 72.0 70.8
11 71.3 69.9 73.3 70.8 71.6 71.5 71.4 70.8
12 71.2 69.4 72.4 71.9 71.4 71.4 71.6 70.8
13 71.3 68.3 72.9 71.6 71.8 71.6 72.0 70.8
14 71.6 69.2 72.9 71.7 72.7 72.1 71.7 71.1
15 72.0 69.9 72.8 72.4 72.9 72.5 72.0 71.3
16 72.1 70.0 72.7 72.3 73.2 72.7 72.3 71.4
17 71.8 70.1 72.8 72.0 72.1 72.3 72.1 71.1
18 71.2 69.3 71.8 71.7 71.9 71.6 71.6 70.7
19 70.6 69.7 71.0 70.5 71.1 70.8 70.8 70.0
20 69.3 68.1 69.2 69.0 69.7 69.3 70.7 69.3
21 68.2 67.8 67.6 67.8 67.5 68.7 69.2 68.7
22 66.9 66.4 65.9 67.5 65.8 66.1 68.2 68.1
23 65.0 63.6 64.0 64.1 64.4 64.6 66.6 67.6
Hour Global Average Sunday Monday Tuesday Wednesday Thursday Friday Saturday
0 63.6 65.9 66.3 61.0 60.6 62.5 63.9 65.0
1 61.1 64.2 64.6 59.1 57.5 59.4 60.2 62.8
2 59.3 63.0 62.6 57.8 55.9 57.1 58.2 60.4
3 58.4 62.6 62.0 56.4 55.0 55.9 56.8 60.0
4 58.0 60.8 61.6 56.1 56.4 55.3 56.4 59.6
5 61.0 63.0 62.3 60.3 59.6 60.0 60.5 61.5
6 65.1 64.1 63.9 64.6 66.3 65.5 66.2 64.8
7 67.6 65.2 64.5 69.1 69.3 69.5 69.2 66.6
8 68.4 66.6 65.1 69.6 70.0 69.8 69.5 68.1
9 68.8 67.8 66.5 69.7 70.2 69.9 69.2 68.5
10 68.6 67.6 67.2 69.3 69.3 69.3 69.1 68.5
11 68.4 67.9 67.9 68.9 68.8 68.7 69.0 67.9
12 68.0 67.4 67.1 67.9 68.8 68.4 68.4 68.1
13 68.0 67.2 68.6 68.6 68.4 67.8 68.5 66.8
14 68.6 67.5 68.4 68.4 69.0 69.3 68.9 68.6
15 68.5 67.9 68.5 69.2 68.9 67.6 69.0 68.5
16 69.1 68.2 68.6 69.0 69.0 68.7 69.6 70.5
17 69.3 67.9 69.0 69.9 69.8 70.0 70.1 68.1
18 69.1 68.7 68.6 69.2 69.1 69.6 69.4 68.8
19 68.4 68.3 67.9 67.9 68.0 68.9 69.1 68.5
20 67.5 67.2 67.0 67.2 67.1 68.0 68.2 68.2
21 66.7 66.4 65.8 66.2 66.5 66.9 67.3 67.8
22 66.3 65.5 64.9 65.2 66.4 66.9 67.1 68.3
23 65.5 64.9 62.9 64.2 65.3 66.2 67.0 67.9
Hour Global Average Sunday Monday Tuesday Wednesday Thursday Friday Saturday
0 61.6 65.9 59.6 60.1 58.9 62.2 60.6 64.1
1 59.0 63.9 56.3 56.4 56.7 59.0 58.2 62.2
2 57.1 62.2 54.2 56.0 54.0 56.7 55.8 61.0
3 56.6 60.9 54.0 55.3 53.8 56.7 55.3 60.1
4 57.3 60.8 55.8 55.8 54.9 57.6 56.6 59.7
5 61.2 61.9 60.5 60.8 60.7 61.1 61.6 62.1
6 65.0 61.8 65.1 66.1 66.1 65.5 66.1 64.3
7 67.7 63.0 68.5 69.2 69.3 68.9 68.9 66.1
8 69.1 65.4 69.7 70.4 70.3 69.9 69.8 68.2
9 70.4 66.6 71.3 71.7 71.6 71.1 71.1 69.3
10 70.7 67.2 71.4 71.7 72.0 71.1 71.4 70.1
11 70.2 67.3 70.7 71.4 70.2 70.8 70.9 70.1
12 69.5 67.1 70.0 69.9 69.9 69.9 70.3 69.7
13 69.7 66.9 69.8 70.3 70.5 70.4 70.3 69.8
14 69.9 67.7 70.0 70.5 70.9 70.2 70.4 69.6
15 70.0 68.6 70.2 70.2 70.6 70.5 70.4 69.6
16 70.0 68.3 70.0 70.3 70.9 70.6 70.4 69.3
17 69.7 68.1 70.3 69.9 70.2 69.9 70.2 69.3
18 69.3 67.8 69.3 69.5 69.7 69.7 69.8 69.1
19 68.0 67.1 67.6 67.8 68.1 68.1 69.0 68.4
20 67.2 66.3 66.7 66.5 67.2 67.5 68.4 67.9
21 66.2 65.0 65.7 65.9 66.3 66.2 67.4 67.0
22 65.7 64.5 64.8 64.7 65.5 66.0 67.1 67.1
23 64.2 61.8 62.8 62.3 64.5 64.4 65.9 67.3
Hour Global Average Sunday Monday Tuesday Wednesday Thursday Friday Saturday
0 65.8 62.9 59.7 58.7 62.9 64.3 75.5 76.6
1 64.2 62.0 57.1 62.1 60.3 58.4 73.7 75.4
2 62.6 58.8 56.3 60.8 57.4 57.1 73.5 74.3
3 62.7 57.6 58.9 59.0 57.1 59.0 73.5 74.1
4 68.7 65.1 64.1 60.3 72.3 74.9 73.5 71.0
5 63.8 59.8 61.4 62.8 59.8 61.9 74.5 66.7
6 66.5 59.7 63.9 65.6 74.2 64.0 75.8 62.0
7 69.3 60.6 66.2 68.5 65.8 75.9 79.1 69.1
8 71.0 62.4 66.7 71.0 68.6 77.6 79.6 70.7
9 72.0 68.0 69.7 71.5 69.8 78.1 79.3 67.8
10 73.5 69.0 70.6 76.6 69.6 77.6 78.9 71.8
11 73.1 69.8 78.2 72.3 66.8 76.0 77.0 71.8
12 72.7 69.3 71.1 71.6 71.3 75.4 78.8 71.4
13 71.9 69.0 72.6 71.6 71.5 73.0 74.9 70.9
14 71.5 70.9 72.2 66.8 71.4 71.6 75.0 72.5
15 72.8 70.1 72.3 72.4 71.3 75.2 74.4 74.2
16 72.9 70.3 72.1 73.5 72.2 75.0 73.6 73.8
17 73.0 71.4 73.4 71.4 72.6 74.7 73.8 73.8
18 73.5 70.7 71.9 74.4 74.0 75.4 73.7 74.4
19 72.0 67.6 69.4 72.7 74.0 75.5 72.7 71.9
20 70.3 66.1 65.8 70.8 68.1 76.5 72.2 72.4
21 71.7 74.0 65.2 70.1 68.8 76.3 77.0 70.8
22 68.7 62.9 66.6 69.2 67.1 69.7 76.6 68.6
23 67.7 61.8 65.0 68.6 65.1 68.5 77.0 68.1
2016 November 23
UrbanSense Platform
Urban noise: are the cities really ‘smart’?, Cecília Rocha, FEUP

20. João Rodrigues, Vítor Ribeiro, João Pedro Pereira, Márcio Coelho,
Pedro D’Orey, João Barros, Cecília Silva, Cristina Queirós, Ana Aguiar

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

22. Data Privacy
• Participants fill out informed consent form
• Participants can access their own data
– OpenID authentication
– We store info that enables access to own data
• Anonymisation via pseudo-id
– We cannot identify participants
• Full access to own data anytime (web)
– Visualise, download, delete (yes, really)

23. On an Urban Scale
Fuel Consumption, by Daniel Moura
Bus driver stress
by João Rodrigues

24. A Research Tool
• What about the citizen’s mood?
– With Cristina Queirós, FPCEUP

25. Mood Map
Mood map,
by João Rodrigues

26. SenseMyFEUP
• Study FEUP’s mobility sustainability
– Joint work with Cecília Silva, CITTA/ DEC, and
Comissariado para a Sustentabilidade
– Traditional questionnaires
– Crowdsensor
• OD matrices: durations, distances, frequencies, mode

27. Origins & Destinations

28. Duration

29. Traffic Flow
Weekdays Midday
Extracted from taxi speeds when busy, courtesy of GeoLink

30. Traffic Flow
Weekdays Midnight
Extracted from taxi speeds when busy, courtesy of GeoLink

31. Traffic Flow
Weekends Midnight
Extracted from taxi speeds when busy, courtesy of GeoLink

32. Emission Map
Ecological Footprint,
by João Rodrigues

33. IoT for Smart Cities
• Understand and monitor intrinsic processes
– Improved spatio-temporal granularity
– Wider availability of data/ information
– More informed decision making
– Monitor impact of measures
• Improve relationship with citizens
– More comfortable/ easier communication
• Real-time management of urban area

34. Closing the loop…
• Mobility plan for ?
– Asprela, UP, Porto?
• Real-time estimated time of arrival for buses
• Route planning for cyclists (with Ubike)
– Using traffic, speed and inclination data
• Public information on temperature and air
quality
• Traffic routing based on air quality

35. Challenges
• Interoperability
• How much data to store? Which data? How long?
• Security
• Interdisciplinarity
– Working at the border of comfort zone
– Time
– Patience
– Tolerance
– Open mindedness
• Cooperation

36. IoT for Smart Cities
Ana Aguiar
ana.aguiar@fe.up.pt
Faculdade de Engenharia UP
Instituto de Telecomunicações

37. Ana Aguiar
ana.aguiar@fe.up.pt