GFG-Assisted Human Tracking Using Smart Phones

Mobile phones are increasingly being equipped with hardware and software services that allow them to determine their locations; however, support for building location-based applications remains a challenging problem. The most widely used localization technology in smart phones is GPS, but it rarely works indoors and provides low energy efficiency. Cell towerbased localization is widely available, but can provide very poor accuracy without a fingerprint profile. WiFi localization, when available, provides reasonable accuracy, but is also much less effective in other areas. Constandache et al. proposed an Escort system to assist in localizing and tracking others in a public place without requiring either GPS, WiFi, war-driving, maps, or floor plans. However, the Escort system may route one person on a long path even though the person being tracked may be close by. In this paper, we will investigate the problem of finding better tracking paths in the Escort system. We propose a GFG routing assisted human tracking algorithm to reduce the length of the tracking path for every pair of users using smart phones in mobile social networks. Through adding one seeker in the Escort system, whose main function is to find better paths between any pair of two intersections by applying the GFG routing algorithm, the localization and tracking algorithm in the Escort system is more effective than the original algorithm. Finally, we conduct simulations of our proposed algorithm at the main campus of Temple University with different numbers of mobile users and different duration times. The simulation results show that the human tracking performance has been greatly enhanced.