Continuous Athlete Monitoring in Challenging Cycling Environments Using IoT Technologies

• Published in: IEEE internet of things journal Vol. 6; no. 6; pp. 10875 - 10887
• Main Authors: Municio, Esteban, Daneels, Glenn, De Brouwer, Mathias, Ongenae, Femke, De Turck, Filip, Braem, Bart, Famaey, Jeroen, Latre, Steven
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.12.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 6TiSCH; Bicycles; Bicycling; Body area networks; Car following; Cognition; CONAMO; cycling; Heart rate; Industrial Internet of Things (IoT); Internet of Things; Mathematical analysis; Monitoring; Mountains; Performance enhancement; Protocols; Racing; Real time; real-time feedback; Real-time systems; Reliability; Remote sensors; Sensors; Sports; stream reasoning; Wireless sensor networks
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2019.2942761

Internet of Things (IoT)-based solutions for sport analytics aim to improve performance, coaching, and strategic insights. These factors are especially relevant in cycling, where real-time data should be available anytime, anywhere, even in remote areas where there are no infrastructure-based communication technologies (e.g., LTE and Wi-Fi). In this article, we present an experience report on the use of state-of-the-art IoT technologies in cycling, where a group of cyclists can form a reliable and energy efficient mesh network to collect and process sensor data in real-time, such as heart rate, speed, and location. This data is analyzed in real-time to estimate the performance of each rider and derive instantaneous feedback. Our solution is the first to combine a local body area network to gather the sensor data from the cyclist and a 6TiSCH network to form a multihop long-range wireless sensor network in order to provide each bicycle with connectivity to the sink (e.g., a moving car following the cyclists). In this article, we present a detailed technical description of this solution, describing its requirements, options, and technical challenges. In order to assess such a deployment, we present a large publicly available data-set from different real-world cycling scenarios (mountain road cycle racing and cyclo-cross) which characterizes the performance of the approach, demonstrating its feasibility and evidencing its relevance and promising possibilities in a cycling context for providing low-power communication with reliable performance.