SmartBike: an IoT Crowd Sensing Platform for Monitoring City Air Pollution

In recent years, the Smart City concept is emerging as a way to increase efficiency, reduce costs, and improve the overall quality of citizen life. The rise of Smart City solutions is encouraged by the increasing availability of Internet of Things (IoT) devices and crowd sensing technologies. This paper presents an IoT Crowd Sensing platform that offers a set of services to citizens by exploiting a network of bicycles as IoT probes. Based on a survey conducted to identify the most interesting bike-enabled services, the SmartBike platform provides: real time remote geo-location of users’ bikes, anti-theft service, information about traveled route, and air pollution monitoring. The proposed SmartBike platform is composed of three main components: the SmartBike mobile sensors for data collection installed on the bicycle; the end-user devices implementing the user interface for geo-location and anti-theft; and the SmartBike central servers for storing and processing detected data and providing a web interface for data visualization. The suitability of the platform was evaluated through the implementation of an initial prototype. Results demonstrate that the proposed SmartBike platform is able to provide the stated services, and, in addition, that the accuracy of the acquired air quality measurements is compatible with the one provided by the official environmental monitoring system of the city of Turin. The described platform will be adopted within a project promoted by the city of Turin, that aims at helping people making their mobility behavior more sustainable

Development of Instrumented Bikes: Toward Smart Cycling Infrastructure and Maintenance

USDOT Grant 69A3551747109This project is to develop an instrumented bike with a sensor logger, a video device (e.g., GoPro), a mobile app, and a cloud server/website to detect real-time quality of cycling infrastructure systems (bike trails, sidewalks, pedestrian pathways, etc), and immediately share the information with cyclists (road users) and governments/authorities (road managers) such that (1) cyclists (road users) will be aware of upcoming potential hazards prior to cycling and be able to adjust their cycling route accordingly, and (2) governments (road managers) will be able to effectively prioritize their maintenance needs. A computing algorithm using the sliding window method was developed in support of the development of instrumented bike. Based on field cycling test, the sliding window computing algorithm is capable of analyzing vibration patterns and identifying potential hazards (potholes, bumps, uneven surface, cracks, etc.) through multiple cyclists. The purpose of the project is to introduce an instrumented bike to the cycling community and agencies with a goal to provide \u201csmart wheels\u201d for day-to-day cycling operations, improve bike efficiency, safety, and mobility, promote cycling activities, and reduce emissions