MobIntel: Sensing and Analytics Infrastructure for Urban Mobility Intelligence

Abstract

Mobility monitoring in urban environments can provide valuable insights into pedestrian and vehicle movement. Understanding the causes and effects of changing mobility patterns can help city officials and businesses optimize operations and support economic development. In this paper, we present MobIntel, an alternative to visual surveillance technologies for mobility monitoring. We deployed multiple radio frequency sensors in downtown West Palm Beach and enabled a system for providing valuable metrics concerning pedestrian activity patterns. We discuss several obstacles to accurate trajectory monitoring, such as MAC address randomization and sensor range issues.