scholarly journals Artificial Intelligence Technology to Mechanical Vibration Wireless Sensor Monitoring Terminal Design Research

2021 ◽  
Vol 1992 (4) ◽  
pp. 042019
Author(s):  
Yuehui Gao
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Maobin Ding

Study on designing reasonable travel routes with the least time cost and the highest experience index was conducted. An artificial intelligence-based wireless sensor travel route planning study is proposed. First, the improved TSP route planning model is built at the least time consumption and combines the normal distributed random number (ND) with the genetic algorithm (GA) and proposes the ND-GA algorithm, analyzes the overall structure, node structure, communication mode, and network coverage of the wireless sensor network, and gives a mathematical model of wireless transmission energy consumption. Using the proposed algorithm to solve the travel route and detailed itinerary, with time, the 10-year travel route design model based on multitarget dynamic optimization finally detailed analysis of the model results and sensitivity analysis results showing that the application of AI wireless sensor technology can also make the scenic work more efficient; for example, a face recognition system can improve the speed of ticket checking. Although the application of AI technology is widely used in tourism activities, there are some problems, which require the continuous optimization and innovation of AI wireless sensor technology by relevant practitioners, so that it can better serve tourists.


Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.


2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.


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