Concept proposal and experimental verification of a sidewalk supporting system utilizing a smartphone

In this report, we propose a system to be used as a basis for the efficient gathering of information on sidewalk usage and services for the purpose of building a system to support social infrastructures through which users can move safely and securely. We assume services for extracting and providing useful information to sidewalk users and local governments. Specifically, we propose a concept for a sidewalk supporting system that accumulates information from strollers, mobility scooters, bicycles, etc., through sidewalk users’ smartphones, sensors, and other such devices to provide valid information. Next, we show a proposed basic system configuration utilizing data collection technologies that have been developed in robots and walking appearance analysis with regard to responses to the diversity of sensors and the characteristics of smartphones. Furthermore, we introduce techniques for estimating sidewalk conditions using the subjectivity of sidewalk passers-by with regard to the acquisition of training data to analyse data effectively. As a specific application case, we evaluated the estimation of the gradient and unevenness of sidewalks by machine learning from the sensor data during the passage of strollers, and verified the effectiveness of this method.