Abstract
School zones are areas near schools that have lower speed limits and where illegally parked vehicles pose a threat to school children by obstructing them from the view of drivers. However, these laws are regularly flouted. Thus, we propose a novel wireless sensor network application called School zone Safety System (S3) to help regulate the speed limit and to prevent illegal parking in school zones. S3 detects illegally parked vehicles, and warns the driver and records the license plate number. To reduce the traveling speed of vehicles in a school zone, S3 measures the speed of vehicles and displays the speed to the driver via an LED display, and also captures the image of the speeding vehicle with a speed camera. We developed a state machine based vehicle detection algorithm for S3. From extensive experiments in our testbeds and data from a real school zone, it is shown that the system can detect all kinds of vehicles, and has an accuracy of over 95% for speed measurement. We modeled the battery life time of a sensor node and validated the model with a downscaled measurement; we estimate the battery life time to be over 2 years. We have deployed S3 in 15 school zones in 2007, and we have demonstrated the robustness of S3 by operating them for over 1 year.
Highlights
With the research and development advancements in technology relevant to WSNs such as MEMS (Micro-Electro-Mechanical Systems), low power communication protocols, and low power embedded software, there has been an increase in trials deploying WSN applications including consumer electronics, PC peripherals, home automation, home security, personal healthcare, toys and games, industrial control and monitoring, asset management [1], and intelligent agriculture [2]
We propose a novel WSN application called School zone Safety System or S3, and report real world experiences from its development and deployment
We proposed a novel WSN application called School zone Safety System (S3)
Summary
With the research and development advancements in technology relevant to WSNs (wireless sensor networks) such as MEMS (Micro-Electro-Mechanical Systems), low power communication protocols, and low power embedded software, there has been an increase in trials deploying WSN applications including consumer electronics, PC peripherals, home automation, home security, personal healthcare, toys and games, industrial control and monitoring, asset management [1], and intelligent agriculture [2]. Published papers on traffic measurement and classification with magneto-resistive sensors [5,6] They proposed a hill-pattern based vehicle detection and classification algorithm and number of experimental results. We include a control loop based on WSNs to capture speeding vehicles with a speed camera and propose the whole system architecture and application scenarios for a school zone safety system. With extensive experiments we demonstrate the performance of S3 through detection ratio, speed measurement accuracy, battery life time, and robustness with real deployments. We evaluated the detection performance and speed measurement accuracy of S3 in the real school zone, and confirmed the results from the experiments in our in-campus and old highway testbeds.
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