The Intelligent Integration of Interactive Installation Art Based on Artificial Intelligence and Wireless Network Communication

With the development of technology and the times, the development of new media technology and interactive installation art has slowly entered the vision of our audience. It is simply “silent art.” The public no longer “retires” like the traditional one, but participates in it and swims with the artists in the world of art. This article is aimed at studying the application of artificial intelligence and wireless network communication to the application of interactive installation art. Through the optimization of various communication equipment and the continuous advancement of various algorithms, we can strengthen the communication and connection between our interactive installation art. This article proposes that with the addition of artificial intelligence and wireless network communication, the interaction between artists and audiences may be more fun, so that we can be more colorful in our lives. The experimental results in this article show that when performing wireless network communication, the communication delay rate of the intelligent algorithm with artificial intelligence is much lower than that of the one without it, which shows that they can better transmit information to the control end. When affected by the outside world, the bit error rate of wireless network communication will increase, however, the artificial intelligence algorithm is added to his impact range, and his bit error rate increase is obviously not so high. In the process of wireless network communication, the improved algorithm is definitely better than the nonimproved algorithm in terms of energy consumption, communication delay, and bit error rate. Through the enhancement of signals and the selection of materials for communication equipment, these are all in continuous progress, and in this respect, are in continuous exploration. Compared with other algorithms, the ml algorithm has improved positioning accuracy by about 70%, 65%, and 30%. Increasing the number of nodes in the transmission signal can greatly reduce the number of hops between nodes, correspondingly reducing the hop distance error, correspondingly reducing the distance estimation error, and improving the positioning accuracy. It can solve the technical barriers of interactive installation art faster.

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Accelerated testing method for bit error rate in wireless network

2014 International Conference on Information and Communications Technologies (ICT 2014) ◽

10.1049/cp.2014.0626 ◽

2014 ◽

Author(s):

Nan Zhang ◽

Ning Huang ◽

Ruiying Li ◽

Xiaolei Sun

Keyword(s):

Wireless Network ◽

Bit Error Rate ◽

Error Rate ◽

Accelerated Testing ◽

Testing Method

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Technical Composition and Creation of Interactive Installation Art Works under the Background of Artificial Intelligence

Mathematical Problems in Engineering ◽

10.1155/2021/7227416 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Yuan Cao ◽

Zhi Han ◽

Rui Kong ◽

Canlin Zhang ◽

Qiu Xie

Keyword(s):

Artificial Intelligence ◽

Installation Art ◽

Human Life ◽

Computer Hardware ◽

Interactive Art ◽

Interactive Installation ◽

Open Design ◽

Art Works ◽

Artificial Intelligence Technology ◽

Neural Network Prediction

Interactive installation art is a kind of art that uses specific software and computer hardware as a platform, a platform for interaction between humans and machines or different people through computer hardware. It is an interactive art that uses material installations in nature as a medium. Traditional interactive installation art is not safe and convenient, in order to solve the shortcomings of traditional interactive installation art. This article introduces artificial intelligence technology by studying the overview, development, and application of artificial intelligence. The encryption algorithm for artificial intelligence data protection and the BP neural network prediction model under artificial intelligence are also introduced to ensure the safety of interactive installation art works. The part also introduces the creation tools and creation process of interactive installation art works. Finally, in the analysis part, a questionnaire analysis of the World Expo is carried out. The results of this article show that the art of connecting inserts is the most complete and open design era. Advances in science and technology, the development of digital art, and the needs of human life have led to the development of interconnected input technologies. In addition, in the survey of people’s satisfaction with artificial intelligence, we can conclude that 89% of people think that the security of artificial intelligence technology is very high. Yes, 92% of people think that artificial intelligence technology has a fast computing speed, 86% of people think that artificial intelligence technology is low in cost.

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A Method for Predicting the Bit Error Rate of Wireless Digital Communication Equipment

2020 IEEE 3rd International Conference on Electronics Technology (ICET) ◽

10.1109/icet49382.2020.9119708 ◽

2020 ◽

Author(s):

Biao Wang ◽

Xue-tian Wang ◽

Hang Li ◽

Hong-min Gao ◽

Yong-wei Sun

Keyword(s):

Bit Error Rate ◽

Error Rate ◽

Digital Communication ◽

Communication Equipment

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H∞-dCNN: Enhancing the SNR using Deep Learning Algorithm in Wireless Communication System

10.21203/rs.3.rs-491094/v1 ◽

2021 ◽

Author(s):

C. Priya ◽

D. Kumutha ◽

M. Shilpa ◽

K. Jayanthi ◽

S. Baskaran

Keyword(s):

Deep Learning ◽

Wireless Communication ◽

Wireless Network ◽

Bit Error Rate ◽

Error Rate ◽

Communication Systems ◽

Mimo Systems ◽

Learning Algorithm ◽

Network Computing ◽

Deep Learning Algorithm

Abstract In Wireless communication systems, the deep learning-based Convolution Neural Networks (dCNN) is performed to gain a better improvement of Quality of Services(QoS) with higher Signal to Noise Ratio (SNR). Multiple Input and Multiple Output (MIMO) systems are presented for real-time evaluation from various technologies, which has served the purpose of services in improving the communication performance of the physical layer of the wireless network. By increasing the communication throughput by focusing on resource allocation, the overall efficiency was not up to the market due to the network’s dynamic behavior. This article proposes the system in two different stages to express the analytical solution for decreasing the Bit Error Rate(BER). The first is to employ the Hybrid Infinity (H∞) through the channel for better robustness in wireless network computing. Next is to optimize Bit Error Rate (BER) with carrier detection as well as other criteria for improving service quality by analyzing the network behavior using Deep Learning Algorithm. The deep Convolution Neural Network with Hybrid Infinity (H∞ - dCNN) is implemented and evaluates the low BER values with high SNR for the performance of QoS. Thus, H∞ - dCNN is proved and outperform the simulated results with better characteristics by using the Matlab software. Hence, the mathematical expression for the proposed system is noticed that a significant improvement is obtained in terms of BER lesser than 0.6 e-4. It is observed the SNR lesser than 18dB, which is comparatively best than the baseline method.

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