Smart sensor integration for real-time quality monitoring in processed frozen foods

Abstract

The demand for processed frozen food has increased due to its rich flavors, long shelf life, and convenience. This trend was noticeable during the COVID-19 pandemic as it reduced the need for frequent grocery shopping and minimized virus exposure. However, processed frozen food is still prone to spoilage over time. This study aims to monitor the quality of processed frozen food, including beef, chicken, and fish, over 24 hours using three primary sensors known as MQ4, MQ136, and MQ137. These sensors detect the main gases produced during food spoilage, which are methane (CH4), hydrogen sulphide (H2S), and ammonia (NH3), respectively, and are integrated with the ESP32 microcontroller. Each sample was analyzed using 100 g of meat placed in a sealed container, with ambient temperature and humidity levels being monitored. The pattern of gas production can be viewed on ThingSpeak, and a notification is sent via Telegram when the threshold value is reached. This study is conveniently used to identify the typical conditions under which processed frozen food is most likely to be spoiled. The result shows that the MQ137 sensor is the most sensitive in detecting early spoilage stages, which indicates the ammonia gas in high temperature and humidity levels.