<![CDATA[Traffic accidents are a serious issue, causing an average of three fatalities every hour. Based on available data, approximately 61% of traffic accidents are caused by human factors, 9% by vehicle roadworthiness, and 30% by infrastructure-related factors such as road conditions, traffic signs, weather, and the surrounding environment. In the process of accident investigation, law enforcement officers often face difficulties in obtaining accurate data related to vehicle speed, braking activity, and the use of turn signals by the rider. As a result, the information gathered is often subjective and varies among different witnesses. This study aims to design and implement a motorcycle monitoring system capable of recording vehicle speed, braking actions, and turn signal activation in real-time to support objective traffic accident analysis. The method used in this research involves the development of a microcontroller-based hardware system equipped with a speed sensor, brake sensor, and turn signal sensor. All data is automatically transmitted using Internet of Things (IoT) connectivity to the Google Firebase platform. An Android application developed using MIT App Inventor displays the data in real-time, while storage is handled through integration with Google Spreadsheet. The results of this system are expected to provide accurate and reliable reference data for law enforcement and relevant institutions in analyzing traffic accidents, as well as to serve as a preventive tool for future incidents by enabling digital monitoring of driving behavior. Keywords: IoT, Google Firebase, Google Sheets, Motorcycle Vehicles, MIT APP Inventor]]>
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