Abstract
This article carries out the overall design framework of the IoT sensor data processing platform and analyzes the advantages of using the integrated construction platform. The platform is divided into two parts, a web management platform and a data communication system, and interacts with the database by integrating the business layers of the two into one. The web management platform provides configurable communication protocol customization services, equipment information, personal information, announcement information management services, and data collection information monitoring and analysis services. The collected data is analyzed by the sensor data communication service system and then provided to the web management platform for query and call. This paper discusses the theoretical basis of the combination of genetic algorithm and neural network and proposes the necessity of improving genetic algorithm. The improved level involves chromosome coding methods, fitness function selection, and genetic manipulation. We propose an improved genetic algorithm and use an improved genetic algorithm (IGA) to optimize the neural network structure. The finite element method is adopted, the finite element model is established, and the shock piezoelectric response is numerically simulated. The genetic neural network method is used to simulate the collision damage location detection problem. The piezoelectric sensor is optimized, and the optimal sensor configuration corresponding to its initial layout is obtained, which provides guidance for the optimal configuration of the actual piezoelectric sensor.
Highlights
The Internet of Things is an emerging thing
When the platform is started through the Tomcat server, the data communication service based on MINA and the web service based on SSH2 run at the same time and, realize the communication service between the device terminal and the client terminal
The platform is divided into two parts, a web management platform and a data communication service system, and interacts with the database by integrating the business layers of the two into one
Summary
The Internet of Things is an emerging thing. By combining various wired and wireless networks with the Internet, information about objects can be transmitted in real time and accurately [1]. The information data collected by the sensors at the perception level of the Internet of Things needs to be transmitted through the network. The Internet of Things has been developed gradually with the progress of various networks, especially the improvement of the technology of the original wireless sensor. The wireless sensor network is an important part of the perception layer of the Internet of Things. Journal of Sensors all kinds of information that people need and send them to the final application in a timely and stable manner It is a deep-level expansion of the original network and an important material basis for the development of the Internet of Things. The simulation results show that for the initial deployment mode of more sensors, the genetic neural network method can effectively reduce the number of more sensors, thereby reducing costs. The simulation results can provide certain guidance for the optimal configuration of the actual piezoelectric sensor of the structural specimen
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