A presentation about a project that we developed to create generate a colormap of urban traffic condition and vehicle diagnostic

1. Car Monitoring Project
Leonardo Sarra - Gabriele Cervelli - Giorgio De Magistris

2. Previously on…
- Obtain data from multiple cars
- Process locally the data and send
them to a remote server
- Provide meaningful infographics
thanks to the aggregation of the
data received
The idea: Technologies & services:
- OBD connector
- Android SDK
- Apache Edgent
- IBM Watson IOT
Platform
- Kibana

3. OBD connector
- Provide a bluetooth interface to the
car’s on-board computer
- Wide range of information: fuel, oil,
distance, throttle, brake and error
codes…
- Available information may change
depending on the car, the OEM and
the revision of the OBD module.

4. The Android Application
- Written in Kotlin using AndroidX support
libraries
- Modular design
- Supports smartphones with Android 8+
- Painful spartan UI
- Handle Bluetooth connection (and setup).
- Join together OBD’s info and the GPS
location
- Send a stream data to IBM Watson IOT
Role:

5. App’s modules
- OBD Java API, a community-developed
set of APIs to write queries for the
OBD2/ELM327 module
- Car-Monitoring-Edgent, our library to
pack data and create a stream to a
remote service

6. Code snippet - Setup OBD connection
Before killing the connection remember it is important to remember to reset the
OBD state using the “Close” command, otherwise you may fail connecting later
on.

7. Code snippet - Get data from OBD

8. - Written in Java with Android in mind
- Uses Apache Edgent to create a stream of
data and send it over IBM Watson IOT
- Uses a lightweight connectivity protocol
(MQTT)
- Provides a set of interfaces to read from the
car’s sensors
- Takes care of joining the data into a single
JSON Object
Car Monitoring Edgent library

9. Code snippet - Creating data stream

10. Code snippet - Sensors as objects (Edgent-side)
We expect object that sensors that implement those interfaces in order to get
the data with a fixed-interval schedule

11. Code snippet - Sensors as objects (Android side)
On the Android side I will
override interfaces’
methods

12. Technical difficulties:
- No reliable a priori knowledge of
the available sensors
- Bluetooth interface may fail from
time to time
- Writing and testing code in the car
is not a pleasant experience
- I don’t have a driving license… yet
Solution: OBDSim

13. IBM Bluemix Cloud
Services
IBM Cloudant
Database
Managing devices and storing data

14. IBM Bluemix Dashboard

15. Cloudant Database
- NoSQL structure
- 1 GB free data storage
- JSON documents
- Monthly bucket
- Binding with Watson IOT
Platform requires very few steps
- Create an alias of your Cloudant
instance into your Cloud
Foundry project space through
IBM CLI.
- Then bind that through Watson
dashboard.

16. - Message Hub Server
- 200 MB IN/OUT traffic per month (free plan)
- Role: Receives payloads from Apache Edgent
devices and automatically stores data in
Cloudant DB

17. Code snippet - Mirroring data to Elastic DB
- DB feed fires the
trigger.
- Trigger is mapped to
a chain (sequence) of
actions through a
rule.
- Our first actionis to
read last insertion
and to pass it to a
custom Python
function.
- The function will
actually send a PUT
request to Elastic DB.

18. Our IBM Cloud Function to mirror insertions

19. - Hard to find what you are looking for in IBM and Apache Edgent
documentation (e.g. broken links, discrepancies, outdated docs)
- IBM Documentation assumes you know things you couldn’t know
about their services. (It gave to me headaches because i had no idea
of what was missing)
Technical difficulties:

20. - Powerful and open source search engine
- Allows plain-text or structured queries
over collections of JSON documents
- Built on top of Elastic
- Console to interact with Elastic
- Wide choice of tools for visualizing data
Managing data

21. Elastic Indices
- Documents are organized in
Indices
- The definition includes the name
of each field and its type
- Allows complex type and nested
fields
- JSON format

22. Visualizing with Kibana- Visualizations in
Kibana can shows
either the result of a
query or the entire
database
- Allow filtering
- Aggregators group
documents by a given
attribute applying an
aggregation function
(Count, AVG . . . )

23. Infographics
- Colormap to show real time
traffic
- Refresh rate each 5 seconds
- Time range of 15 minutes
- Speed ranges adapting to
the current viewing area

24. Infographics II
- Bar chart showing how many
vehicles have engine
temperature in a given range
- This kind of diagnostic
information could be used by
car producer to improve their
products

25. Contacts
- Leonardo Sarra - LinkedIn, GitHub
- Gabriele Cervelli - LinkedIn, GitHub
- Giorgio De Magistris - LinkedIn, GitHub
Source-code
github.com/car-monitoring-sapienza-iot-2019

26. Thank You!