TOOLS AND METHODS FOR FOOD FRESHNESS DETECTION USING GAS SENSORS AND MACHINE LEARNING

Abstract

This invention concerns food products such as meat and seafood, which are highly perishable due to their high water content and unsaturated fatty acid content, leading to a rapid decline in quality. The manual process of determining food freshness, which relies on human senses such as smell and sight, is limited by subjectivity, expert fatigue, and significant inaccuracy. To assist distributors, manufacturers, and consumers in ensuring product quality, this invention presents a food freshness detection device that utilizes a combination of gas sensor technology and machine learning algorithms. This device is capable of detecting volatile gases such as ammonia, methane, carbon monoxide, and hydrogen sulfide released during the spoilage process.Data from the gas sensor is processed using an ESP32 microcontroller with a machine learning algorithm to classify freshness levels in real-time. The classification results are displayed on an OLED display with the status "Fresh" or "Not Fresh." The device's portable, simple, and easy-to-use design allows for operation in various locations, both on an industrial and individual scale. With these advantages, this invention is expected to improve efficiency, accuracy, and quality in the food distribution chain, as well as support industrial sustainability.

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