Co-Sense: Internet of Things Multi-Sensor Vehicle Trip Data Recorder

Accident identification requires a detailed account of an accident and its cause. These accounts are typically based on unreliable eyewitness testimony. The Co-Sense system, designed to improve analysis of accidents, records vehicle data including tilt, location, speed, and distance information to an object using GPS, gyroscope, and ultrasonic sensors. With an ESP32 microcontroller and a Raspberry Pi 4, Co-Sense is an Internet of Things system that expands on earlier research by adopting an alternative connectivity method, enhancing scalability, using an alternative data acquisition procedure, integrating with external platforms, and enhancing system usability. The results of a field test indicate that Co-Sense efficiently records information, stores it, and transmits it to a mobile phone. The gyroscope, ultrasonic sensor, and GPS module exhibit error rates of 0.85%, 1.82%, and 10.12%, respectively, when detecting vehicle speed.

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Published
2024-10-24
DOI
https://doi.org/10.1109/icic64337.2024.10957169
Primary Topic
Traffic Prediction and Management Techniques
Type
article
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article

Co-Sense: Internet of Things Multi-Sensor Vehicle Trip Data Recorder

Maya Fitria, Rahmad Dawood, Humaira, Tubagus Maulana et al.
Traffic Prediction and Management Techniques
article

Co-Sense: Internet of Things Multi-Sensor Vehicle Trip Data Recorder

Maya Fitria, Rahmad Dawood, Humaira, Tubagus Maulana, Ahmad Mufadhdhal Alkifani, Muhammad Daffa Adrian Sitorus
article en

Abstract

Accident identification requires a detailed account of an accident and its cause. These accounts are typically based on unreliable eyewitness testimony. The Co-Sense system, designed to improve analysis of accidents, records vehicle data including tilt, location, speed, and distance information to an object using GPS, gyroscope, and ultrasonic sensors. With an ESP32 microcontroller and a Raspberry Pi 4, Co-Sense is an Internet of Things system that expands on earlier research by adopting an alternative connectivity method, enhancing scalability, using an alternative data acquisition procedure, integrating with external platforms, and enhancing system usability. The results of a field test indicate that Co-Sense efficiently records information, stores it, and transmits it to a mobile phone. The gyroscope, ultrasonic sensor, and GPS module exhibit error rates of 0.85%, 1.82%, and 10.12%, respectively, when detecting vehicle speed.

Universitas Syiah Kuala (ID)
Openalex Percentile: Top 69%
Traffic Prediction and Management Techniques
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Co-Sense: Internet of Things Multi-Sensor Vehicle Trip Data Recorder — Maya Fitria, Rahmad Dawood, et al. · (2024) | TGRS Research Map | TGRS