Edge-based anomaly detection for campus air quality/occupancy
Supervisor Name
Alhareth Zyoud
Supervisor Email
azyoud@birzeit.edu
University
Birzeit University
Research field
Electrical Engineering
Bio
Alhareth Mohammed Zyoud received his bachelor degree in electrical engineering from Palestine Polytechnic University in 2006, his master and Ph.D. degrees in communication engineering from International Islamic University Malaysia in 2011 and 2017, respectively. He has authored or co-authored many research papers in international journals and conferences. His current research interests include RF modeling and simulation, 5G radio resource management, Internet of Things, and rain attenuation analysis.
Description
Anomaly detection is consistently reported as the weakest-performing analytics function in cloud-reliant smart-campus systems. This project directly addresses that gap by implementing a localized, edge-based anomaly detection system for campus air quality and occupancy. This is particularly relevant for Palestinian university campuses, where reliable cloud connectivity and infrastructure budgets are often constrained. By deploying low-cost ESP32 nodes equipped with specific environmental and occupancy sensors (e.g., CO2, temperature, humidity, and infrared beam sensors), the system will transmit encrypted data directly to a local Raspberry Pi. A lightweight machine learning model (such as an Isolation Forest or Autoencoder) will run directly on the edge.
