IoT-Based System for Logistics Monitoring and Analysis in Delivery Trucks

Abstract

This paper presents the design, implementation and testing of an Internet of Things (IoT)-based system for monitoring and analyzing logistics in delivery trucks, with case studies conducted in Santa Ana, El Salvador. The proposed system collects real-time data on geographical position, travel time and vehicle performance, thereby providing a baseline dataset for logistical optimization. The IoT system comprises a multi-layer architectural structure, which includes physical, communication, processing, and presentation layers. The system incorporates several key components, including the ESP32 microcontroller, the SIM7000G module for GSM and GPS connectivity and a solar-powered energy management system. The data collected by the IoT nodes are transmitted via a mobile network to an IoT cloud platform, enabling real-time visualization and historical data analysis through an intuitive web interface. The results demonstrate the system's reliability and efficiency, achieving precise geolocation with minimal latency and uninterrupted operation due to effective energy management. Analyzing the collected data can identify patterns in delivery routes, travel times, and bottlenecks, facilitating actionable insights to optimize logistics operations.