Freshness prediction method of large yellow croaker based on Internet of Things and neural network

Xu E; Jianglong Cao; Zhenpeng Dai; Song Wang

doi:10.1117/12.3031223

19 July 2024 Freshness prediction method of large yellow croaker based on Internet of Things and neural network

Xu E, Jianglong Cao, Zhenpeng Dai, Song Wang

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131818W (2024) https://doi.org/10.1117/12.3031223
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

Total Volatile Basic Nitrogen (TVB-N) was an important index for evaluating the freshness of aquatic products. However, the traditional detection technology for TVB-N was complex and caused irreversible damage to fish. Therefore, this study proposes a new method to predict the freshness of large yellow croaker using the combination of Internet of Things technology and Neural Network Model. By monitoring the levels of CO2, H2S, NH3 and trimethylamine (TMA) in fish stored at 4℃, TVB-N was used as a chemical indicator to assess freshness. Polynomial regression analysis and partial least squares are used to explore the correlation between TMA and TVB-N. Using these results, a CNN-LSTM model based on polynomial regression is developed to predict TVB-N values for large yellow croaker. Regarding evaluation indices, the CNN-LSTM model, rooted in polynomial regression, demonstrated an approximately 88.6% enhancement in the RMSE index compared to the traditional PLS model. The results suggest that the integration of IoT technology and neural networks can function as an objective, non-destructive tool for evaluating the freshness of large yellow croaker.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xu E, Jianglong Cao, Zhenpeng Dai, and Song Wang "Freshness prediction method of large yellow croaker based on Internet of Things and neural network", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131818W (19 July 2024); https://doi.org/10.1117/12.3031223

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