Building an Intelligent Food Safety Inspection System Based on the Internet of Things

In order to make it more convenient and fast for people to obtain the production information of dairy food and consume dairy food with confidence, a dairy food safety testing system based on the Internet of Things (IoT) is proposed in the study. Firstly, an ISM-AHP-RBF neural network-based risk assessment method for dairy products is proposed, and then the design of an IoT-based dairy milk production method is proposed using the information transmission and data collection functions of the IoT. The performance of the model is validated by comparing it with traditional neural network models. The results show that the ISM-AHP-RBF neural network can quickly iterate to a stable state and converge better than the other two traditional models; the results of risk prediction and assessment of milk components using the model are close to the real values and can accurately predict the riskier components, thus ensuring the food safety of dairy products. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2024 KIPS