Demo Abstract: EVAPS: Edge Video Analysis for Public Safety
Qingyang Zhang, Zhifeng Yu, Weisong Shi, Hong Zhong · 2016
Real-time video analysis at the edge of the network is very promising to significantly improve public safety, e.g., dangerous accidents detection and find a missing person. Simply uploading the video stream to the cloud for analysis costs too much energy and network bandwidth to an energy-limited camera. Hence we propose EVAPS (Edge Video Analysis for Public Safety), which distributes the computing workload in both the edge nodes and the cloud in an optimized way. EVPAS is able to eliminate unnecessary data transmission over and save energy for edge devices, i.e., cameras. Three demos are used to illustrate the energy efficiency and optimized solution for public safety using the proposed EVAPS framework.