The Impact of Manufacturing Transformation in Digital Economy Under Artificial Intelligence - Peixu Wang; Kun Wang; Dong Wang; Hongyuan Liu (IEEE Access, 2024)
To thoroughly investigate the influence of the artificial intelligence (AI) model within the digital economy on the transformation of the manufacturing industry in the Internet of Things (IoT) environment, an AI model for the optimization of the IoT is proposed. This model is specially designed to overcome traditional AI models’ performance constraints in resource-constrained environments. Firstly, this study analyzes the critical role of the IoT in the manufacturing revolution and its combination with AI. Secondly, it investigates the core role of the IoT in the digital economy and manufacturing transformation. Finally, this study focuses on optimizing the AI model in the context of the IoT. Moreover, it makes a comprehensive evaluation of the optimized model regarding energy consumption, running time, prediction accuracy, and recall by comparing it with the standard Convolutional Neural Network and the lightweight Mobile Neural Network. The empirical findings reveal that the optimized model outperforms its traditional counterparts across the aforementioned indicators, particularly excelling in energy efficiency. Supported by case analyses of manufacturing enterprises, it is further substantiated that the optimized model effectively enhances production efficiency, quality, and cost reduction in practical application. Additionally, the research limitations and future work directions are discussed, encompassing extending the model’s applicability to diverse scenarios and enhancing its generalization capabilities. This study presents a fresh perspective on AI deployment within the IoT domain, bearing significant theoretical and practical implications for the continued advancement of intelligent manufacturing and the digital economy.