The Application of IoT Technology and Deep Learning in Automated Intelligent Control Systems

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Chunhua He
Lijuan Kang


In order to accurately monitor the environmental information of agricultural greenhouses, achieve remote automatic control, and improve crop yield, the author proposes an application method of Internet of Things technology in automatic intelligent control systems. This method utilizes IoT technologies such as WSN, Android, and cloud platforms to design an intelligent agricultural greenhouse monitoring system, taking sensors such as soil moisture, lighting, temperature and humidity as examples, and using shading, water spraying, fans, and fill lights as control devices. Design from aspects such as system architecture, perception control system, cloud database, and mobile terminal management system to achieve automatic monitoring of agricultural greenhouse environmental information.Experimental results show that: The data collected by the sensor is compared with the actual monitoring data of the instrument, taking temperature as an example, the errors are all within ±0.5◦C of multiple measurements. Conclusion: The system has the advantages of good scalability, convenient networking, and high cost performance, which makes up for the difficulties in wiring and inconvenient use of the traditional agricultural greenhouse monitoring system, and has high practical value.

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Special Issue - Deep Learning-Based Advanced Research Trends in Scalable Computing