Abstract

The development and implementation of vehicle tracking systems based on Internet of Things (IoT) technology have attracted considerable interest due to the rising demand for effective and secure monitoring solutions. This study investigates the investigation and development of a vehicle monitoring system that utilizes Internet of Things (IoT) capabilities to provide real-time tracking, data collection, and analysis. By combining existing literature, IoT principles, and modern technologies, this study seeks to present a comprehensive and practical method for implementing an effective vehicle tracking system that satisfies the requirements of contemporary fleet management. This document provides a thorough investigation and practical application of a vehicle tracking system utilizing Internet of Things (IoT) technology. The research covers a comprehensive examination of relevant articles and resources regarding vehicle tracking systems and Internet of Things (IoT) applications. It explores into the fundamental principles of IoT and its significance in the context of vehicle tracking. The implementation phase encompasses the creation of a bespoke vehicle tracking system that integrates GPS modules, microcontrollers, wireless communication, and cloud-based data storage to enable real-time tracking and monitoring. The integration of advanced data analytics and machine learning techniques enhances the capabilities of the system, resulting in valuable insights, optimized routing, and predictive maintenance. This integration contributes to improved fleet management. The ethical implications pertaining to the protection of data privacy, security, and compliance to regulatory requirements are carefully taken into account. The results of this study make a valuable contribution to the field of Internet of Things (IoT)-based vehicle tracking systems. Additionally, it provide a practical framework that can be utilized by organizations in search of effective and scalable solutions.

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