Building an Intelligent Food Safety Inspection System Based on the Internet of Things
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In order to make it more convenient and fast for people to obtain the production information of dairy food andconsume dairy food with confidence, a dairy food safety testing system based on the Internet of Things (IoT)is proposed in the study. Firstly, an ISMAHPRBF neural networkbased risk assessment method for dairyproducts is proposed, and then the design of an IoTbased dairy milk production method is proposed using theinformation transmission and data collection functions of the IoT. The performance of the model is validatedby comparing it with traditional neural network models. The results show that the ISMAHPRBF neuralnetwork can quickly iterate to a stable state and converge better than the other two traditional models; the resultsof risk prediction and assessment of milk components using the model are close to the real values and canaccurately predict the riskier components, thus ensuring the food safety of dairy products.
Abstract
In order to make it more convenient and fast for people to obtain the production information of dairy food andconsume dairy food with confidence, a dairy food safety testing system based on the Internet of Things (IoT)is proposed in the study. Firstly, an ISMAHPRBF neural networkbased risk assessment method for dairyproducts is proposed, and then the design of an IoTbased dairy milk production method is proposed using theinformation transmission and data collection functions of the IoT. The performance of the model is validatedby comparing it with traditional neural network models. The results show that the ISMAHPRBF neuralnetwork can quickly iterate to a stable state and converge better than the other two traditional models; the resultsof risk prediction and assessment of milk components using the model are close to the real values and canaccurately predict the riskier components, thus ensuring the food safety of dairy products.
참고문헌 (15)
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