AIoT Empowered Smart Traffic Systems
Project Description
The Internet of Things (IoT) is transforming industries by enabling seamless communication between devices and their environments. This project introduces an AIoT-based framework to simulate real-world traffic systems. The system includes connected traffic lights and autonomous model cars that interact within a controlled environment, providing a tangible way to explore IoT networking, sensor integration, and real-time data processing. By leveraging cloud connectivity (Firebase), this setup demonstrates how IoT devices communicate, make decisions, and respond to dynamic conditions—mirroring real-world scenarios like traffic management and vehicle coordination.
Supervisor
SONG Shenghui
Quota
3
Course type
UROP1100
UROP2100
UROP3100
Applicant's Roles
Develop the Firebase cloud backend for real-time data synchronization.
Implement MQTT/Wi-Fi communication between traffic lights, cars, and the cloud.
Design a dashboard for remote monitoring and control.
Implement pathfinding algorithms for autonomous navigation.
Design and prototype a model car with IoT connectivity.
Implement MQTT/Wi-Fi communication between traffic lights, cars, and the cloud.
Design a dashboard for remote monitoring and control.
Implement pathfinding algorithms for autonomous navigation.
Design and prototype a model car with IoT connectivity.
Applicant's Learning Objectives
Gain hands-on experience with IoT cloud platforms (Firebase Realtime Database, Firestore).
Learn about wireless protocols (MQTT, HTTP) for device-to-cloud communication.
Develop skills in real-time data visualization and IoT system architecture.
Learn about feedback control systems for autonomous movement.
Understand edge computing for low-latency IoT responses.
Learn about wireless protocols (MQTT, HTTP) for device-to-cloud communication.
Develop skills in real-time data visualization and IoT system architecture.
Learn about feedback control systems for autonomous movement.
Understand edge computing for low-latency IoT responses.
Complexity of the project
Challenging