-
Final Prototype in 3D-Printed Enclosure
-
Final Prototype Closed
-
Functional Principle
-
PCB for Mass Production
-
Initial Desk Prototype
The Problem
How many cars are driving on a given street each day? How do temporary or permanent measures affect the traffic flow? Which street in a city is the most used? Which one is the bottleneck?
What it does
The device detects vehicles using an ultrasonic sensor. It measures the length of the passing vehicle and classifies it into a vehicle category. The detected counts are routinly sent via LoRaWAN. Our backend retrieves that data, saves it in a database and allows to view traffic information in real time on a web map. The colours are basically as one would expect it on Google Maps. Google Maps displays the road utilization by the number of devices and their speed in the choosen road section.
How We built it
- Hardware
- ESP32 LoRaWAN Devboard
- MaxSonar Ultrasonic Sensor
- 3D Printed Enclosure
- Software
- C++ + Arduino (Embedded)
- Python + Django (Backend)
- Javascript + Leaflet (Frontend)
- Documentation
Challenges we ran into
- Measuring a cars length requires its speed
- Measuring a cars speed requires its length
What's next
- Production of a custom PCB
- Installation in a first city
- Compatibility to existing Smart City Solutions
Bonus Content
Built With
- arduino
- c++
- esp32
- javascript
- lorawan
- python
- thethingsnetwork
Log in or sign up for Devpost to join the conversation.