主讲人：高泽宇教授、朱盾鸣教授
主讲时间：2024-01-12 10:00
主讲人简介：Jerry Gao, Ph.D. Professor, and Research Center Director, San Jose State University The Organization Chair for IEEE Future Technology Summit The Steering Board Chair of IEEE International Congress on Intelligent Service-Oriented Systems Engineering (IEEECISOSE)
主讲内容：In this talk, Dr. Gao will first provide an overview of smart city drone applications and its machine learning intelligence. Then, he will present diverse intelligence requirements and needs in smart city traffic monitor, flow detection and analysis, and traffic compression classification, and alter generation. Later, three different types of smart city traffic big data (such as IOT, camera, and drone data) are presented using the Silicon-Valley case study. In California, USA. Based on these big data, Dr. Gao discusses their approach how to use machine learning models to support smart city traffic flow analysis and prediction for each deployed traffic camera (CCTV), traffic lane opponency analysis and speed analysis & prediction for each IOT station, and traffic congestion detection, analysis, and classification, as well as traffic alerts. Some case study results are reported, and selected demos are presented. Finally, Dr. Gao will discuss the future smart city traffic issues, challenges, and needs for future research work.
讲座地点：国际交流学院206会议室
主办部门：智能制造与智慧交通学院
主讲时间：2024-01-12 10:00
主讲人简介：Jerry Gao, Ph.D. Professor, and Research Center Director, San Jose State University The Organization Chair for IEEE Future Technology Summit The Steering Board Chair of IEEE International Congress on Intelligent Service-Oriented Systems Engineering (IEEECISOSE)
主讲内容：In this talk, Dr. Gao will first provide an overview of smart city drone applications and its machine learning intelligence. Then, he will present diverse intelligence requirements and needs in smart city traffic monitor, flow detection and analysis, and traffic compression classification, and alter generation. Later, three different types of smart city traffic big data (such as IOT, camera, and drone data) are presented using the Silicon-Valley case study. In California, USA. Based on these big data, Dr. Gao discusses their approach how to use machine learning models to support smart city traffic flow analysis and prediction for each deployed traffic camera (CCTV), traffic lane opponency analysis and speed analysis & prediction for each IOT station, and traffic congestion detection, analysis, and classification, as well as traffic alerts. Some case study results are reported, and selected demos are presented. Finally, Dr. Gao will discuss the future smart city traffic issues, challenges, and needs for future research work.
讲座地点：国际交流学院206会议室
主办部门：智能制造与智慧交通学院
