Video Analytics and IoT People/Asset Sensing for Smart City Applications
Project Description
To research and develop advanced video analytics and IoT (Wi-Fi, LoRa and ibeacon) sensing technologies for smart city applications. Students involved will actively work with my R&D team and industry to conduct trials and deploy the technology. Machine learning/AI techniques will be involved to enable new retail, smart city and new applications.
CHAN Gary Shueng Han
Course type
Applicant's Roles
Students will research and develop various advanced video analytics and IoT (Wi-Fi, LoRa and ibeacon) technologies, their algorithms and protocols, to support user/asset tracking, people sensing, crowd counting, etc. This includes IoT design, sensing, camera innovations, edge AI, and data/video analytics for large-scale deployment. They will help on research, prototyping, simulation, and experimental trials. Students in the project will actively involved in industrial deployment based on our research results to enable new retail, promote smart city and create new market opportunities. Documentations in the form of patent, papers, and presentations will also be involved.
Applicant's Learning Objectives
Ability to understand how IoT works and are designed, what smart camera and edge AI are, how video and IoT play a role to sense users, asset tracking, data mining and user analytics, etc. Ability to conduct video analytics, network programming, machine learning and protocol design.
Complexity of the project