IoT Based Fruit Quality Inspection and Lifespan Detection System

Fruits are an essential source of nutrients, but their quality depends heavily on their freshness and shelf life, which can be impacted by various external factors. This paper presents a comprehensive study on the decay of fruits and the development of a lifespan detection system that integrates a Raspberry Pi Pico, a DHT-11 sensor for capturing real-time temperature and humidity of fruits, and an MQ-4 methane gas detector sensor to estimate methane gas emissions from spoiled fruits. Then data storage and Machine Learning (ML) algorithms are used to accurately predict the expiration date of fruits. The proposed system focuses on measuring some crucial elements that essentially identify the spoilage state of fruit and are transmitted to a local database using a NodeMCU ESP8266. The collected data is then used to predict the expiration date of the fruit using a suggested equation with high accuracy and reliability. By accumulating necessary information about the temperature, humidity, and methane emission of fruit, this paper illustrates a graphical representation of real-time data with an approximate lifespan of the fruit. The system is cost- effective, user-friendly, and useful in warehouses, cold storage, and food quality inspection sectors. With further research and development, the proposed system can be extended to detect the lifespan and expiration of other perishable items, thus providing a comprehensive solution for food preservation and safety.