ARCHIVES
Accident Prediction and Emergency Response System Using Accelerometer Sensor
Published Online: May-August 2024
Pages: 80-87
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20240302010Abstract
Accidents, being unforeseeable events, can result in serious consequences, particularly when immediate medical attention is necessary. To address this issue, we propose the development of an Accident Prediction and Emergency Response System (APERS) that utilizes mobile accelerometer sensors. The APERS comprises two key components: a mobile application installed on users' smartphones and a web-based application for hospitals. The mobile application enables users to input and update their personal information and medical records, which are securely encrypted and stored. Moreover, the application continuously monitors accelerometer sensor data in real-time. Upon detecting a sudden spike in accelerometer readings indicative of an accident, the user's encrypted data and medical records are automatically transmitted to the hospital-side web application. On the hospital side, the web-based application receives and decrypts the user data, granting medical professionals access to vital information even if the user is unconscious. This facilitates timely and well-informed medical interventions, potentially saving lives. The system operates seamlessly, providing a robust solution for accident prediction and emergency response. The APERS offers numerous benefits, including proactive accident prediction, automated data sharing, and swift medical response. By leveraging mobile technology and accelerometer sensors, it addresses the pressing need for efficient emergency services in accident scenarios. Looking ahead, users could potentially share data while crossing the reception, further enhancing the system's effectiveness.
Related Articles
2024
Revolutionizing User Interfaces: Exploring the Latest Trends in Front-End Development
2024
Website Development in Computer Science: Unveiling the Digital World
2024
Review on RSA Cryptography, Steganography and Compression Techniques for Data Security
2024
Stock Price Prediction Using LSTM
2024
Comparative Analysis of Program Execution Time Required by Python, R and Julia Compiler
2024