Leveraging Raspberry Pi and Sensor Technology to Assess Sidewalk Accessibility: Enhancing Travel Experiences for Handicapped Individuals

This study was motivated by personal experience during a summer program in Cambridge, Massachusetts, where suboptimal road conditions in the Allston area posed notable challenges for cycling. This experience highlighted broader accessibility concerns, particularly for individuals with mobility impairments who often lack reliable data on surface-level sidewalk conditions. A review of existing accessibility mapping tools, such as Wheelmap, OpenSidewalks, and AccessMap, revealed ongoing efforts to document infrastructure features relevant to wheelchair users. However, a critical gap remains in capturing fine-grained surface condition data. To address this need, this paper proposes a data collection system utilizing a Raspberry Pi integrated with GPS and gyroscopic sensors to assess sidewalk surface quality. The system is designed for use during cycling to generate spatially resolved condition metrics. The collected data can inform accessibility planning, enrich existing mapping platforms, and ultimately support more inclusive urban navigation for individuals with disabilities.