IoT-Based Real-Time Tracking System Using GPS and ThingSpeak

Abstract

Theft of vehicles, suboptimal fleet operations, and late response to emergencies have resulted in an increasing demand for affordable, reliable and real-time vehicle tracking solutions. The design and development of an IoT implementation for tracking the movement of a vehicle using a NEO-6M GPS receiver, ESP32 microcontroller and ThingSpeak cloud platform is discussed in this paper. The GPS module reads the signals from the satellites to get locations, speed and time information for the vehicle. The ESP32 is used to communicate with the ThingSpeak cloud using Wi-Fi and to process the received NMEA data to extract the various parameters, and GSM communication is treated as a backup. The cloud platform can be used to monitor in real-time, display position maps, graphical representation, and visualise the data in the past, making it easier and quicker to manage vehicles. The suggested architecture is meant to be affordable, simple and scalable using easily accessible hardware components and cloud-based services. The prototype was tested in open sky conditions and was found to successfully acquire a first GPS position fix within 30- 60 seconds of power on and to successfully upload location information every 10-15 seconds. The positional error observed was typically 3-5 m from the reference places, consistent with a performance range typical of similar low cost GPS devices. The performance assessment includes positioning accuracy, acquisition time, transmission reliability and update frequency; however, the number of test runs, mean error, standard deviation and the transmission-reliability percentage need to be reported quantitatively. The technology designed may be utilized for vehicle safety, fleet administration, logistics and personal safety. Offline data logging and geofencing-based warnings are planned features and will further enhance tracking reliability and intelligent monitoring functionality.