Abstract
Aiming to increase the shelf life of food, researchers are moving toward new methodologies to maintain the quality of food as food grains are susceptible to spoilage due to precipitation, humidity, temperature, and a variety of other influences. As a result, efficient food spoilage tracking schemes are required to sustain food quality levels. We have designed a prototype to track food quality and to manage storage systems at home. Initially, we have employed a Convolutional Neural Network (CNN) model to detect the type of fruit and veggies. Then the proposed system monitors the gas emission level, humidity level, and temperature of fruits and veggies by using sensors and actuators to check the food spoilage level. This would additionally control the environment and avoid food spoilage wherever possible. Additionally, the food spoilage level is informed to the customer by an alert message sent to their registered mobile numbers based on the freshness and condition of the food. The model employed proved to have an accuracy rate of 95%. Finally, the experiment is successful in increasing the shelf life of some categories of food by 2 days.
Highlights
Food wastage has been a topic of concern in recent years, and studies are being conducted to identify innovative ways to reduce it
While reviewing the articles on food wastage, we have found that there are a few contributions to increasing the shelf life of food
This study presents a novel technique for Monitoring and analysis of food spoilage using a sensor bases system
Summary
Food wastage has been a topic of concern in recent years, and studies are being conducted to identify innovative ways to reduce it. It has been described as a major concern in the long-term sustainability of food production, demand, and food supply chains. Wastage can be reduced by installing quality control systems in grocery stores. It will further help in controlling diseases [7]. These types of quality control systems keep an eye on the environmental conditions that may maintain the food quality.
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