Distributed Sound Transmission and Smart City Planning Management Based on Convolutional Neural Network

Abstract

In this article, we provide a detection method based on a convolutional neural network algorithm. Preamble detection is very important in underwater acoustic communication. Only the preamble signal can trigger the receiving operation to effectively process the acoustic data received underwater. The prerequisite for specifying the joint position of the distributed acoustic multiarray is the mutual calibration calculation of each array. This paper designs and develops a prototype system for microphone array sound source positioning and provides an optimized system to obtain calibration source mapping points for distributed sound transmission mutual calibration, and for mutual distributed acoustic microphone arrays, use epipolar geometry and normalization algorithm for calibration to provide a basis for a mutual calibration calculation model and functional module design. Finally, perform numerical simulation verification. It provides a design plan and implementation method for the Internet-based smart city education system, aiming to achieve professional education and educational needs related to the Internet of Things. First, we will take Internet application technology as an example to analyze the functional requirements of the education system, including the positioning of human resource development, integrated sensors, C/C#/Java application development technology, and other technical means to realize the smart city education system. Based on the theory of business management, this paper studies the business planning issues of smart city construction. The main content is divided into three parts: business composition and management and planning management. This is an important part of business. It plays a decisive role in the overall planning and implementation stage and protects the implementation progress of the project and ensures the quality of the project by including important content.