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Road
Monitoring
De Luca - Fioraldi - Spadaccino
Problem
In 2018, bad road
conditions caused
over 14k injuries in
Rome
https://www.ilmessaggero.it/roma/cronaca/roma_buche_e_strade_a_rischio_record_infortuni_nel_2018_10mila_al_pronto_soccorso-4032952.html
What we need
A smart way to monitor the presence of road
anomalies in order to take action surgically.
Our solution
An IoT system of sensors
that can be inserted in
any car with the aim of
reporting road anomalies
to the cloud
On board
● LoRa enabled STM32 X-
Nucleo board
● GNSS expansion board
for GPS tracking
● Accelerometer
On the cloud
Real time data streaming from
the car into the cloud with
Amazon Kinesis
Visualization
Real time highlighting of
detected anomalies in an
interactive map
https://developers.google.com/maps/documentation/javascript/custom-markers
Pipeline
1. Record anomalies as they are found
2. Send them using LoRa to TheThingsNetwork
3. Process data with Kinesis
4. Visualize data in the browser
Team
Giovanni De Luca
Volunteer contributor
Mozilla Common voice project
Andrea Fioraldi
CTF player
mHACKeroni & TRX
Pietro Spadaccino
Machine learning enthusiast
We need you!

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Road monitoring IoT 2019 - Sapienza

  • 1. Road Monitoring De Luca - Fioraldi - Spadaccino
  • 2. Problem In 2018, bad road conditions caused over 14k injuries in Rome https://www.ilmessaggero.it/roma/cronaca/roma_buche_e_strade_a_rischio_record_infortuni_nel_2018_10mila_al_pronto_soccorso-4032952.html
  • 3. What we need A smart way to monitor the presence of road anomalies in order to take action surgically.
  • 4. Our solution An IoT system of sensors that can be inserted in any car with the aim of reporting road anomalies to the cloud
  • 5. On board ● LoRa enabled STM32 X- Nucleo board ● GNSS expansion board for GPS tracking ● Accelerometer
  • 6. On the cloud Real time data streaming from the car into the cloud with Amazon Kinesis
  • 7. Visualization Real time highlighting of detected anomalies in an interactive map https://developers.google.com/maps/documentation/javascript/custom-markers
  • 8. Pipeline 1. Record anomalies as they are found 2. Send them using LoRa to TheThingsNetwork 3. Process data with Kinesis 4. Visualize data in the browser
  • 9. Team Giovanni De Luca Volunteer contributor Mozilla Common voice project Andrea Fioraldi CTF player mHACKeroni & TRX Pietro Spadaccino Machine learning enthusiast