Enhanced-AODV: A Robust Three Phase Priority-Based Traffic Load Balancing Scheme for Internet of Things

The purpose of this research is to use the image recognition technology of smart sensors to establish a preschool education system for preschool children, which can realize interactive image-based learning and education for preschool children. This paper uses CMOS image sensor (IV2-6500CA of KEYENCE) to design the front-end image acquisition hardware system and establishes an image recognition system that can realize most of the recognition functions based on BP neural network algorithm and ImageNet, MS COCO, MNIST, and the Chars74K dataset and integrate the image recognition system into the preschool education interactive system. The image recognition system has a high accuracy rate, with an overall accuracy rate of 85.16%. Compared with the traditional preschool education system, it has a higher recognition rate, better teaching efficiency, and interactivity. It can recognize most of the objects that children touch and have a good interactive education effect.

Section: Preschool Education Experiments Based On Image Recognitionmentioning

confidence: 99%

Preschool Education Interactive System Based on Smart Sensor Image Recognition

Chen¹,

Jin²

2022

“…In different applications, the composition of sensor network nodes is not the same [16,17]. But generally, it is composed of data acquisition unit, data processing unit, data storage unit, data transmission unit, power supply, and embedded operating system, as shown in Figure 3.…”

Section: Kriging Algorithm Based Onmentioning

confidence: 99%

5G Embedded Sensor Network System for Sports Information Service Hotspot Recommendation

Zhou

2022

How to rationally allocate and integrate existing resources has become the top priority of the development of sports public information services in the transition period, but it is also a weak link in the construction of current social information resources. This article is aimed at studying how to develop sports information service hotspots based on 5G embedded sensor network systems. Methods such as the network structure based on 5G embedded sensors, the Kriging algorithm based on global optimization, and sensor distance measurement are proposed and also conducted experiments on the application of 5G embedded sensor network system in sports information service hotspot recommendation. The results show that people are satisfied with the sports information service of the wireless sensor network, with a maximum score of 9.8, which is suitable for the information provision of sports information services. The development of the times has met the needs of most people.

“…The hardware support environment of the online intelligent teaching art resource platform based on the clustering analysis algorithm is based on the clustering analysis algorithm data center, structured storage, unstructured storage, and resource underlying services composed of highperformance computing servers and high-performance storage devices, and resource service open access framework; the second part is the front-end business cluster supported by the virtual computing platform to provide users with access to the operation interface [19][20][21][22]. Follow the principles of completeness, clarity, understanding, query ability, and ease of operation.…”

Section: Hardware Support Environment Of the Online Intelligentmentioning

confidence: 99%

Application of Cluster Analysis Algorithm in the Online Intelligent Teaching Art Resource Platform

2022

With the explosion of knowledge and the high-speed dissemination of information, people’s desire for knowledge and information is getting stronger and stronger. At the same time, the updating of knowledge and information is going on at an unprecedented speed. The traditional teaching mode is affected by time and space. Its limitations have become more and more prominent; the traditional classroom teaching has been unable to meet the existing teaching needs. At present, there are many methods for the analysis of network user behavior, such as statistical methods, association analysis methods, and clustering algorithms. Among them, clustering algorithms are more widely used in network user behavior analysis, which is closely related to the unsupervised and high efficiency of clustering algorithms. This paper combines the advantages of clustering algorithm in network user behavior analysis and, on the basis of the existing clustering algorithm research, proposes an improved algorithm for the analysis of online intelligent teaching art resources, so as to obtain the law of online behavior of student users in campus network. Provide some help for students’ Internet management and network optimization. Finally, summarize and put forward the concept of intelligent teaching and design and implement an online intelligent teaching art resource platform based on cluster analysis algorithm. Studies have shown that the average number of transactions processed by the platform per second is 65.21, which can well simulate real information query use cases. The transaction processing time of the platform will eventually stabilize between 30 s and meet the performance requirements.