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We present a novel efficient adaptive sensing and monitoring solution for asystem of mobile sensing devices that support traffic monitoring applications.We make a key observation that much of the variance in commute times arises ata few congestion hotspots, and a reliable estimate of congestion can beobtained by selectively monitoring congestion just at these hotspots. We designa smartphone application and a backend system that automatically identifies andmonitors congestion hotspots. The solution has low resource footprint in termsof both battery usage on the sensing devices and the network bytes used foruploading data. When a user is not inside any hotspot zone, adaptive samplingconserves battery power and reduces network usage, while ensuring that any newhotspots can be effectively identified. Our results show that our applicationconsumes 40- 80% less energy than a periodic sampling system for differentroutes in our experiments, with similar accuracy of congestion information. Thesystem can be used for a variety of applications such as automatic congestionalerts to users approaching hotspots, reliable end-to-end commute timeestimates and effective alternate route suggestions.

RTChoke: Efficient Real-Time Traffic Chokepoint Detection and Monitoring