SPATH: Finding the Safest Walking Path in Smart Cities

Abstract

Given the fact that more than 1 million crimes happened in U.S. every year, public safety becomes one of the most important concerns. Although many public safety related applications have been commercialized, how to guarantee safely walking to a destination, especially in an unfamiliar city is still challenging. To provide a safe walking navigation in smart cities, we design a novel application, SPATH (the Safest PATH). To support this service, wireless cameras, existing cellular infrastructure, and vehicles with underutilized computing resources are utilized to process and transmit surveillance videos, which can be viewed by users to check the current safety status of different walking paths. Noting the long-distance transmission of a large volume of videos may cause network congestion, video summarizing technology, which is realized by utilizing the underutilized computing capability in vehicles, is applied to extract valuable information from a video file while effectively compressing its data size. Since the quality of service for this application is strongly correlated with the latency of delivering videos, we formulate a latency minimization problem by jointly considering the computing resource allocation and computing task assignment. A Fast Iterative Matching (FIM) is proposed with low complexity to effectively solve the optimization problem. Simulation results demonstrated the effectiveness and efficiency of our solution.