| Project ID |
BITS-SRIP/6CF4DC/2026 |
| Project Title |
Multi-Agent Edge AI for Controlled Sensing and Communication: A Practical Testbed |
| Project Description |
This project builds a hands-on multi-agent testbed where multiple sensing nodes and an edge AI controller work together to achieve controlled sensing and efficient communication. Several ESP32-based sensor nodes will act as distributed sensing agents, collecting real-world data such as motion, environmental parameters, vibration, or sound. An edge AI controller running on an NVIDIA Jetson platform will analyze incoming data using lightweight machine learning models and make control decisions.
Expected Outcome:
• Interfacing sensors with ESP32 and collecting real-time data
• Implementing communication between ESP32 nodes and the Jetson edge controller
• Building a small dataset and training basic ML models for classification or anomaly detection
• Implementing controlled sensing strategies using rule-based and simple adaptive methods
• Measuring performance in terms of accuracy, latency, and data reduction
• Demonstration, documentation, and final report preparation |
| Project Discipline |
Open to students from Electrical Engineering, Electronics and Communication Engineering, Computer Science, and related interdisciplinary programs. Students with interest in embedded systems, edge AI, data processing, or system integration are encouraged to apply. |
| Faculty Name |
Syed Mohammad Zafaruddin |
| Department |
Department of Electrical & Electronics Engineering |
