Ultra-Low Power IoT Traffic Monitoring System

Given the sizable anticipated proliferation of Internet of Things (IoT) devices, Forrester Research forecasts that the fleet management and transportation industry sectors will enjoy more growth than others. This may come as no surprise, since infrastructure (e.g., roadways, bridges, airports) is a prime candidate for sensor integration to provide real-time measurements and to support intelligent decisions. The predicted increase of deployed devices makes it difficult to calculate the amount of energy required for these functions. Current estimates suggest that 2 to 4% of worldwide carbon emissions can be attributed to the information and communication industry. This paper presents novel algorithms designed to optimize power consumption of an intelligent vehicle counter and classifier sensors. Each was based on an event-driven methodology wherein a control block orchestrates the work of different components and subsystems. System duty-cycle is reduced through several techniques, and a reinforcement learning algorithm is introduced to control the system power policy, according to the traffic environment. Battery life for a sensor supported by a 2300 mAh battery was extended from 48-hour, adopted all-on policy to more than 400 days when leveraging the algorithms and techniques presented in this work.