Electric Vehicle Accident Alert System is a Machine Learning Integrated, IoT based real-time alerting system, operating on ESP8266 microcontroller. Our designed system acts as an alerting system in its truest sense. It uses KNN classification algorithm to analyse the GPS location of the vehicle and generate a prediction indicating whether the vehicle is in an accident-prone area or not. And, if the accident occurs, the Electric Vehicle Accident Alert System sends a SOS alert message with a link to google maps (for directions), to the emergency contact saved in the system. The whole system is based on a plug n play concept, i.e., the system would be ready to use once powered up. To provide this agility and flexibility, we have designed a registration web portal for the device which registers the user and their device with a unique UID on the Cloud. After successful registration, the system becomes ready and can be simply fitted inside a vehicle to be used. Moreover,the ML algorithm saves those GPS coordinates in its dataset to further improve the accuracy of the prediction. The whole IoT stack integrated with ML algorithm, Web Portal and a Cloud server (implemented on Google Firebase), makes our project a self-improving, agile and a user-friendly system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.