Ethylene gas-based fruit expiry predictor: a sustainable solution to fruit wastage

Abstract

Globally, environmental and economic issues are very apparent regarding food wastage. Fruits play a significant role since they can be damaged easily. Ethylene gas is one of the significant gases produced by fruits when they begin to ripen; it tests whether the fruit is ripe or else spoilable. This work presents a sustainable solution for fruit wastage: an ethylene gas-based fruit expiry predictor (FEP). The system is designed and developed around advanced sensing and artificial intelligence (AI) models for real-time monitoring of ethylene levels and temperature in forecasting the spoilage of fruits. The system consists of non-invasive sensors for detecting ethylene and temperature, a data processing microcontroller, and an AI model trained on a large dataset to make accurate predictions regarding the expiry of fruit. The AI model processes the information collected by the sensors and then displays the grade (level of ripeness of the fruit) on a liquid crystal display (LCD) screen. This solution improves fruit management with reduced wastage in line with international sustainability targets. These would enable real-time and highly accurate predictions of fruit spoilage, allowing end-users informed choices that will eventually lead to reducing the carbon footprint from food waste and increasing food security.