Analyzing Riding Activities on the World's Longest Continuous Cycling Path Using Non-Intrusive IoT Sensors

Abstract

On February 2020, Qatar entered the Guinness World Record by opening the world's longest continuous cycling track developed by the Public Works Authority - Ashghal. Gaining insights of the usage of the so called Olympic Cycling Track (OCT) such as biker count, travel time, speed, riding periodicity, and location origin, allows for the development of better cycling user experience, operational planning and maintenance. This paper attempts to conduct this analysis based on data collected from WaveTraf a sensing system that anonymously detects and tracks the movement of Bluetooth and WiFi-enabled devices. Data from four WaveTraf IoT sensors, deployed along the track, is cleaned, prepossessed and analysed to reveal riding patterns in the OCT track. An effective data cleaning technique was applied to detect and clean the noise in the data caused by detected devices from roads close of the OCT track. Analysis results demonstrate clear seasonality and trend in the riding pattern which was proven to be associated to the weather conditions as well as the normal work schedules.