The freshness of food detection using the internet of things.

Electronics and Telecommunication Engineering

Around one-third of the food produced globally ends up as waste, totaling a staggering 1.3 billion tons annually. This waste is particularly prevalent at venues like hotels, family gatherings, and parties. The magnitude of this issue becomes apparent when considering its substantial environmental ramifications. Freshness plays a pivotal role in determining the quality of seafood and other perishable goods. The efficiency of food processing, storage, and marketing hinges on the ability to swiftly ascertain freshness. To address the limitations of existing freshness detection methods, this study introduces a rapid and non-invasive approach. The proposed method leverages IoT technology, employing an array of sensors and sophisticated algorithms to evaluate food quality and freshness. Initially, volatile organic compound (VOC) gases emitted by the food are collected and analyzed for distinctive features. Subsequently, a machine learning algorithm is employed for freshness assessment. To facilitate user interaction and interpretation of results, an application is designed to showcase the outcomes of food inspections conducted by the device. This innovative system aims to mitigate food waste by enhancing our ability to monitor and manage freshness levels effectively.

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