AI-Based Temperature Automation and Location Tracking for Maritime and Food Container

Abstract

This study presents a comprehensive system for automated temperature control and position tracking, designed for application in food and maritime containers. The system utilises photos and a YOLO (You Only Look Once) algorithm to identify and categorise various types of food. GPS technology enables customers to track the container's location in real-time, providing visibility at all times. The deep learning aspect, based on YOLO, is highly critical for enabling the automatic detection and categorisation of food in the container. YOLO is very adept at identifying things, so it can quickly and reliably categorise them, ensuring that different kinds of food are placed in the correct group. A PID controller is a typical feedback device for control loops that does an excellent job of maintaining things at the appropriate temperature. The PID controller continuously adjusts the Peltier device's operation to maintain the container's internal temperature within the predetermined range. This keeps the food fresh and prevents it from spoiling and being thrown away during transportation. When you add GPS technology to the system, it gains new functionality, including the ability to see your location in real-time. Users can see exactly where the container is at all times, which makes it easier to plan logistics and keeps things safer. This feature is highly beneficial in the shipping industry, where container ships travel vast distances, and in the food industry, where delivering food to its destination on time is crucial.