A Novel Genetic Service Function Deployment Management Platform for Edge Computing

Li, David Chunhu; Chen, Bo Hun; Tseng, Chia Wei; Chou, Li-Der

doi:10.1155/2020/8830294

Cited by 10 publications

(11 citation statements)

References 32 publications

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“…The road is wide, the sea is blue, and the scenery is extremely beautiful. As shown in Figure 5, the annual temperature here is around 28 °C, which is very suitable for tourists to travel [18].…”

Section: Classification Of Big Data and Ai Technologymentioning

confidence: 99%

Smart Tourism Recommendation Method in Southeast Asia under Big Data and Artificial Intelligence Algorithms

2022

Mobile Information Systems

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Smart tourism recommendation refers to supplementing suggestions for tourists’ self-service sightseeing plans based on Internet technology, and recommending more effective and practical tourism information. This paper uses big data and artificial intelligence algorithms to study the smart tourism recommendation method in Southeast Asia. First of all, this paper gives a brief overview of the definition and classification of big data and artificial intelligence algorithms and then introduces tourism resources and smart tourism in Southeast Asia. Finally, this paper conducts a comparative experiment between the smart tourism development model based on big data and artificial intelligence algorithms and the traditional tourism development model and analyzes the utility of the development model from three aspects, namely, tourists’ sense of experience and satisfaction, the scale of tourism transactions and the growth rate of tourism revenue, and the adequacy and harmony of tourism resource allocation. The final experimental results show that the overall average value of tourists’ experience and satisfaction under the smart tourism recommendation mode based on big data and artificial intelligence algorithms is 88.84 points, which is 7.30 points higher than the traditional tourism mode, which verifies its effectiveness.

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Section: Classification Of Big Data and Ai Technologymentioning

confidence: 99%

Smart Tourism Recommendation Method in Southeast Asia under Big Data and Artificial Intelligence Algorithms

2022

Mobile Information Systems

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“…e process of data uploading first passes through the edge layer and then transmits to the cloud center. For the top layer, it can be seen as decentralizing computing power [11]. We extend the original central infrastructure into a star, as shown in Figure 3.…”

Section: E Edge Cloud Computing Solutionmentioning

confidence: 99%

Construction of Hotel Resource Information Platform Based on the Internet of Things Technology

Meng

2022

Mathematical Problems in Engineering

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In order to meet the expectations and needs of hotel managers and hotel occupants, the author proposes a smart hotel system based on the six-domain model of the Internet of things. The system has designed the intelligent hotel guest control unified management cloud platform in detail, including hotel management, guest room management, equipment management, scene management, authority management, system management, Tmall wizard docking, WeChat applet interface, and MQTT client; we design a smart hotel room controller (RCU) hardware system based on Espressif ESP32 (WiFi Soc) and realize centralized management and control of curtains, lamps, air conditioners, and other equipment in hotel rooms; RCU connects to the MQTT server through WiFi and exchanges and controls data with the cloud intelligent platform by means of message subscription and publishing. At the same time, the equipment set of RCU can be arbitrarily cut and added according to the actual hotel scene, and the logic control function can be reconstructed and designed according to the user’s personalized requirements. In addition, considering the edge-cloud computing processing scheme, the framework of the system is designed and the software to simulate the edge-cloud computing system is finally used; the system simulation results show that the total failure rate of the edge-cloud computing structure is less than 5%, and the processing time of the task is relatively short. Conclusion. It can meet the needs of diversified application scenarios of smart hotels.

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“…In the field of intelligent prosthetic state recognition, in addition to the above recognition methods, there are hidden Markov (HMM) recognition methods, auxiliary vector machines (SVM), and so on. Considering the possible limitations of a single recognition method, we will mainly consider two recognition methods and compare their recognition effects and related features in lower extremity motion pattern classification [15].…”

Section: Recognition and Prediction Of Human Lower Limb Motionmentioning

confidence: 99%

5G Virtual Reality System for Prosthetic Wearer Gait Evaluation and Application in Intelligent Prosthesis Debugging

Yan

Li²,

Xie

et al. 2022

Mobile Information Systems

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The main purpose of developing intelligent lower limb prostheses is to improve the quality of life of the disabled and promote the development of medical care. At the same time, the research of robotic intelligent lower limb prosthesis is a research direction that has been widely concerned in the field of robotics and biomedical engineering technology in recent years. This paper aims to research and discuss the 5G virtual reality system based on the gait evaluation of prosthetic wearers and its application in the debugging of intelligent prostheses. First, this paper analyzes the combination of the concept of lower extremity rehabilitation and virtual reality. Virtual reality technology is a means of exercise rehabilitation for patients with lower extremity hemiplegia, which plays an auxiliary role in the rehabilitation process. Then, the recognition and pre-method of human lower limb motion state are described. In the field of intelligent prosthetic state recognition, in addition to neural network recognition methods, there are hidden Markov (HMM) recognition methods, auxiliary vector machines (SVM), and so on. Finally, the lower limb state phase detection experiment and the prosthetic control experiment based on state phase detection are studied. The results of this experimental study showed that, for the same experimenter, changes in pace and gait did not affect the percentage of standing and swing phases. That is, the standing phase accounts for about 60% of the entire gait cycle, while the swing phase accounts for 40% of the entire gait cycle. This rule has been verified in other experiments.

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A Novel Genetic Service Function Deployment Management Platform for Edge Computing

Cited by 10 publications

References 32 publications

Smart Tourism Recommendation Method in Southeast Asia under Big Data and Artificial Intelligence Algorithms

Smart Tourism Recommendation Method in Southeast Asia under Big Data and Artificial Intelligence Algorithms

Construction of Hotel Resource Information Platform Based on the Internet of Things Technology

5G Virtual Reality System for Prosthetic Wearer Gait Evaluation and Application in Intelligent Prosthesis Debugging

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