Mobile crowdsensing applications for intelligent parking and mobility - Cherian, Jim (2019)
Due to the worldwide rapid urbanization and rising private vehicular mobility, most cities face problems such as traffic congestion, parking deficit, and cruising for parking, leading to resource wastage and environmental costs. This includes the first/last-furlong problem for personal vehicular mobility in public places i.e. the challenge to find/locate a parking space near the destination. Intelligent mobile sensing, which fuses the computing/sensing capabilities of mobile devices with machine learning, holds a great potential towards solving such urban mobility challenges. Opportunistic Mobile Crowdsensing (MCS) has also emerged as a new paradigm that enables intelligent mobility applications and services. Mobile computing research has addressed the on-street/outdoor traffic and parking problems to a great extent. However, the occupancy estimation of indoor parking garages remains mostly unsolved - especially in garages that lack vehicle-tracking sensor infrastructure and/or real-time information delivery.