2017/11/9 PNC meeting With emerging concerns of air pollution and recent advances in Internet of Things (IoT) technology, air quality monitoring has become one of the most important IoT applications in many countries and major cities. One of the most successful systems of this kind is the AirBox project, which is based in Taiwan and operated in a grassroot fashion, and it has deployment more than 2,500 nodes in 30 countries in just one year. The system is also notable for its extremely high deployment density and data frequency, as most of the participating nodes are located in Taiwan and with a high sample rate. In this talk, we present the development of this AirBox project in detail, and we demonstrate several data analysis work that we have carried out for data visualization, anomaly detection, data forecast, and other advanced data services. We also discuss challenges and opportunities for making sense of Internet of Things data based on the lessons learned from the AirBox project.

1. Making Sense of Internet of Things:
using AirBox as an example
Ling-Jyh (L.J.) Chen, Academia Sinica
cclljj@sinica.edu.tw

2. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Internet of Things (IoT)
2
LAN
40%
LPWAN
45%
Cellular M2M
15%
LAN
40%
LPWAN
45%
Cellular M2M
15%
40%
LPWAN
45%
Cellular M2M
15%
• 經由感應器轉換環境中可偵
測的物理量可獲得外在環境
跟生理訊號等資訊。
• 外在環境感測，例如：溫濕
度、氣壓、亮度、聲音等。
• 生理訊號感測，例如：心跳、
血糖、血壓、心電圖等。
(Sensor)
• 經由感應器轉換環境中可偵
測的物理量可獲得外在環境
跟生理訊號等資訊。
• 外在環境感測，例如：溫濕
度、氣壓、亮度、聲音等。
• 生理訊號感測，例如：心跳、
血糖、血壓、心電圖等。
(Sensor)

3. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Internet of Things (IoT)
3
LAN
40%
LPWAN
45%
Cellular M2M
15%
LAN
40%
LPWAN
45%
Cellular M2M
15%
40%
LPWAN
45%
Cellular M2M
15%
• 經由感應器轉換環境中可偵
測的物理量可獲得外在環境
跟生理訊號等資訊。
• 外在環境感測，例如：溫濕
度、氣壓、亮度、聲音等。
• 生理訊號感測，例如：心跳、
血糖、血壓、心電圖等。
(Sensor)
• 經由感應器轉換環境中可偵
測的物理量可獲得外在環境
跟生理訊號等資訊。
• 外在環境感測，例如：溫濕
度、氣壓、亮度、聲音等。
• 生理訊號感測，例如：心跳、
血糖、血壓、心電圖等。
(Sensor)
IoT

4. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 4
AirBox: a participatory sensing
IoT system for PM2.5 sensing

5. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
What’s PM2.5?
5
1. Par'culate ma.er enters our lung
system through the nose and throat.
2|3. The larger par'cula
(PM10) is eliminated throug
coughing sneezing and swall
4. PM2.5 can penetrate deep into the
lungs. It can travel all the way to the
alveoli, causing lung and heart
problems, and delivering harmful
chemicals to the blood system.

6. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 6
The Professional Solution
• 76 multi-function stations (TW)
• huge and extremely expensive
• 10+ meters above the ground
• well-mixed atmosphere

7. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 7
What’s the air quality
here and now?
We ask a very simple question…

8. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Our strategy to make it happen…
8
Enable
Empower
Engage

9. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Enable: identify feasible sensors
9
Accuracy
vs
Precision

10. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Empower: open HW/SW
10

11. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Engage: a healthy ecosystem
11

12. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
And it is still ongoing …
12
• 4,000+
devices
• 30 countries

13. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Before (2015) Now (2017)
13
76 2,000

14. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Finer-grained ever
14
Smog from China on 2017/01/30
http://gph.is/2jKCLuM

15. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
The spirit of AirBox system
15
Grassroots

16. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Open Data
16
• The real time raw data and analytics results
are freely available
https://sites.google.com/site/pm25opendata/open-data

17. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Visualization Tools
https://pm25.lass-net.org/GIS/voronoi/ https://pm25.lass-net.org/GIS/IDW/

18. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Animation Example
18
2017/02/04 21:00 - 2017/02/05 04:00 God birthday ritual
http://gph.is/2lUD4SU

19. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Maker Education
19

20. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Environment Education
20

21. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Open Community
21

22. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Open Discussion
22
Citizen
Science

23. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Data Analytics
23

24. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Making Sense of Things
24
https://airmap.g0v.asper.tw
indoor

25. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Making Sense of Things
25
https://airmap.g0v.asper.tw
indoor
emission ongoing

26. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Making Sense of Things
26
https://airmap.g0v.asper.tw
indoor
emission ongoing
close to fixed
emission source

27. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 27
https://pm25.lass-net.org/

28. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Making more sense of IoT?
28
http://www.rosebt.com/uploads/8/1/8/1/8181762/6779091_orig.jpg

29. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Making more sense of IoT?
29
http://www.rosebt.com/uploads/8/1/8/1/8181762/6779091_orig.jpg

30. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 30
Data Forecast
Accuracy
Scalability
NNAR Hybrid (NNAR + ARIMA)

31. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 31
Data Forecast
Accuracy
Scalability
NNAR Hybrid (NNAR + ARIMA)
Matrix Optimization

32. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 32
Data Forecast
Accuracy
Scalability
NNAR Hybrid (NNAR + ARIMA)
Matrix Optimization
Cluster-based Hybrid

33. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 33
Data Forecast
Accuracy
Scalability
NNAR Hybrid (NNAR + ARIMA)
Matrix Optimization
Cluster-based Hybrid

34. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Personalized Service
34

35. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Next step
• More deployment (10K nodes by 2020)
• Portable/wearable devices
• Considering other gas sensors
• Chatbot to interact with end users
• A.I. for finer-grained data forecast
• Moving from “sensing” to “action”
• And more
35

36. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Interdisciplinary Collaboration
36

37. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 37
Making sense
of IoT data
Data informed
decision making

38. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Take home messages
38
• The power of Internet of Things is not just
collecting data, but making sense of data.
• Lessons learned from the AirBox project:
• “open” is the way to make systems scalable
• visualization is helpful for data analytics
• think about must-have or nice-to-have
• Making sensing of IoT is the way to go for smart
environment and data informed decision making.

39. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw)
Acknowledgement
39
• Government: TW EPA, TW MOST, …
• Academia: AS-IIS, AS-RCEC, SUTD,
NCHC, NCTU, NCKU, …
• Industry: Edimax, Realtek, …
• Community: LASS, G0V, CENTRA,
PRAGMA, CECEA, ASEAN IVO, …
• Hard-working bees: my research teams,
students, interns, and many friends

40. Dr. Ling-Jyh Chen (cclljj@iis.sinica.edu.tw) 40
PM2.5 Open Data Portal
https://pm25.lass-net.org/