Abstract
This paper presents a novel approach to improve the accuracy of environmental detection and prediction by incorporating artificial intelligence (AI) technology into existing detection systems. At the heart of our approach lies the combination of a complex AI model with the hardware and software components of the inspection system. This combined approach can significantly improve the accuracy of detection systems through greater ability to predict environmental changes and events, underscoring the superior performance of hardware and software combined with AI technology. This paper delves into the details of hardware and software design, and discusses measurement implementation methods using a build-down machine. We also explore the practical application of AI models within the framework described above. In addition, this paper also describes the implementation of communication protocols to ensure the effective data exchange between the system network and the artificial intelligence model. These protocols are essential for the real-time processing and analysis of environmental data, enabling systems to respond quickly to detected changes.
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