Artificial intelligence based event detection in wireless sensor networks

Bahrepour, Majid

doi:10.3990/1.9789036535021

Cited by 3 publications

(3 citation statements)

References 76 publications

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“…This article centers around three man-made consciousness innovations: normal language, getting it, AI, and canny pursuit. The effect of man-made brain power on showing the framework configuration is displayed in Figure 2 [11].…”

Section: Figure 2 the Impact Of Ai On Teaching System Designmentioning

confidence: 99%

Computer Aided Teaching System for Football Teaching and Training Based on Video Image

2023

IJST

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With the improvement of instructive changes, PC media innovation has been increasingly more broadly utilized in current training and readiness. The development of new media first depends on our cognition and grasp of the Internet. New media innovation is a new media innovation concept formed on this basis: Internet thinking and "Internet +". In addition, teachers generally feel the adaptability and proficiency that modern multimedia technology brings to education. Multimedia technology can allow students to obtain more knowledge and information in a shorter period of time, ensuring that students can learn complex learning in a simple and easy-to-understand mode. This paper focuses on the application of AI (artificial intelligence) in football teaching and puts forward the related ideas of AI, neural network and computer-aided teaching. This paper embraces the exploration techniques like writing information strategy and numerical measurement strategy, and behaviors as an overview and examination by giving surveys to educators and understudies partaking in open actual instruction classes in a specific college. The experimental results show that 23.3% of the total students think that CAI has a promoting effect on the mastery of knowledge and skills, while only 12.8% of the total students think that it has no promoting effect. Therefore, CAI teaching can undoubtedly promote physical education teaching and improve students' learning efficiency.

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Section: Figure 2 the Impact Of Ai On Teaching System Designmentioning

confidence: 99%

Computer Aided Teaching System for Football Teaching and Training Based on Video Image

2023

IJST

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“…) is composed of a large number of self-organized sensor nodes distributed in a particular space. They cooperate with each other to collect and process data from the target area and communicate with remote base stations [1][2]. Based on these features, wireless sensors are widely used in many fields, such as military defense, industrial and agricultural control, biological medical treatment, environmental monitoring and so on, and have achieved remarkable results [3].Wireless sensor network nodes are usually battery powered and the batteries are difficult to be reclaimed and replaced, saving energy and prolonging the life cycle of the network become one of the hotspots of research.…”

Section: Wsn (Wireless Sensor Networkmentioning

confidence: 99%

Cluster Head Multi-hop Routing Algorithm Based on Improved Social Group Algorithm

Liu¹,

Chen²,

Zou³

et al. 2019

dtetr

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CECA algorithm is a very efficient clustering routing algorithm for solving WSN problems. However, in the CECA algorithm, the cluster heads send data directly to the base station in the form of single hop, this results in excessive energy consumption. To overcome this deficiency, a cluster head multi-hop routing algorithm based on an improved social group algorithm with energy consumption model and network model is proposed in the paper. Firstly, an improved SGO algorithm with adding process of learning historical information is proposed to improve the diversity of the population. Then, the improved algorithm is combined with the CECA protocol to enable the cluster heads in WSN transmit data to the base station in a multi-hop manner to prolong the lifetime of the network. To show the effectiveness of the proposed method, the algorithm is tested on a random distributed sensor network, the experimental results show that the improved algorithm can effectively prolong the life cycle of the network.

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“…In this research, Havinga P focuses on decentralized event detection, where sensor nodes use artificial intelligence, data fusion, and distributed pattern recognition to execute locally in the WSN to collaboratively detect events. Since WSN can be deployed in different environments (contexts) for different applications, the number and types of events may be different in different environments and contexts [7]. Many of the above scholars have their own uniqueness in the application research of wireless sensor networks, but there are often various errors in the experiment process, which makes the calculation process complicated and the accuracy of the experimental results has a certain degree of difference sex.…”

Section: Introductionmentioning

confidence: 99%

The Application of Wireless Sensor Network in Public Environment Art Design

2024

AJETS

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In recent years, affected by the hot development of information technology, big data technology has been fully expanded, and wireless sensor networks, which are popular with their own characteristics, have also ushered in vigorous development. Based on the current emphasis on the public environment, the use of wireless sensor networks to locate the details of the environment has the most fundamental and important impact on the artistic design of the environment. Designs that conform to the concept of environmental development are more in line with public expectations. Based on this, this article proposes a wireless sensor network-based public environment for buildings. Environmental positioning research explores the development of intelligent building environment. This article mainly discusses the application technology of wireless sensor positioning system, and compares the modified positioning algorithm with other positioning algorithms. Under the same acquisition conditions and under the same number of samples, explore the difference in positioning errors. A hybrid positioning system based on multiple positioning algorithms is proposed, and comparative experiments are carried out to obtain experimental results, which can highlight the effectiveness of the results. The experimental results in this paper show that the area judgment of the TOA internal area is very good, with an accuracy rate of 100%; the accuracy rate of the key areas of the corridor is 89%. When the wrong area discrimination occurs in the key area of the corridor, it will cause the time delay of the positioning mode switch. The main influence factor is the interference of the door and wall to the key area range, indicating that more attention should be paid to it in the measurement.

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Artificial intelligence based event detection in wireless sensor networks

Cited by 3 publications

References 76 publications

Computer Aided Teaching System for Football Teaching and Training Based on Video Image

Computer Aided Teaching System for Football Teaching and Training Based on Video Image

Cluster Head Multi-hop Routing Algorithm Based on Improved Social Group Algorithm

The Application of Wireless Sensor Network in Public Environment Art Design

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