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2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)最新文献

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Research on fast Matching of Moving objects in Internet of Things based on machine vision sampling 基于机器视觉采样的物联网运动物体快速匹配研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332847
Zhu Tian-Yuan
{"title":"Research on fast Matching of Moving objects in Internet of Things based on machine vision sampling","authors":"Zhu Tian-Yuan","doi":"10.1109/IAAI51705.2020.9332847","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332847","url":null,"abstract":"In order to improve the matching speed of moving objects in the Internet of Things, a fast matching method based on machine vision sampling is designed. Firstly, machine vision sampling method is adopted to acquire moving target image, and then image preprocessing is carried out. Finally, image background segmentation and dynamic background moving target detection are performed to realize fast matching of moving target in the Internet of Things. The experimental results show that the rapid matching method based on machine vision sampling for moving objects of Internet of Things in this study has higher matching speed and accuracy than the traditional method, and has practical application significance.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133657972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application Research and Implementation of Face Recognition in Smart Campus 人脸识别在智慧校园中的应用研究与实现
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332876
Zhou Chun-rong
{"title":"Application Research and Implementation of Face Recognition in Smart Campus","authors":"Zhou Chun-rong","doi":"10.1109/iaai51705.2020.9332876","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332876","url":null,"abstract":"Face recognition technology can be applied to the examination room, library, canteen, dormitory and other areas of smart campus. However, when the original method is applied to face recognition technology, the image enhancement effect is poor, resulting in the slow speed of face recognition. Therefore, a new application method of face recognition in smart campus is studied. In this study, the metric learning method was used to recognize facial information, and based on the extracted facial features, the recognition effect of facial images was enhanced to realize facial detection for students and teachers. The experiment set a total of three face recognition distances of 0.1m, 0.5m and 1.0m. According to the test results, it can be seen that the application method of this study has a faster face recognition speed at different distances than the original application method.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134060565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Crack Detection of Highway Prestressed Concrete Bridge based on Image Recognition 基于图像识别的公路预应力混凝土桥梁裂缝检测
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332901
Hongyan Yin, Li Tang
{"title":"Crack Detection of Highway Prestressed Concrete Bridge based on Image Recognition","authors":"Hongyan Yin, Li Tang","doi":"10.1109/IAAI51705.2020.9332901","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332901","url":null,"abstract":"Because the traditional highway prestressed concrete bridge crack detection method has poor ability to detect image edges, the detection rate of the detection method is low. Therefore, a crack detection method of highway prestressed concrete bridge based on image recognition is proposed. Select the image acquisition equipment and acquisition points to complete the bridge image acquisition. The collected image is grayed and enhanced to realize image preprocessing. Taking the above-mentioned image as the detection basis, the threshold method is used to segment the detection to complete the crack edge detection. So far, the design of crack detection method for highway prestressed concrete bridge based on image recognition is completed by comparing with the other two traditional methods, it can be seen that this method has a higher detection rate of cracks, which shows that this method is more effective in use.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124950746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Intelligent Vehicle Automatic Lane Changing Lateral Control Method based on Deep Learning 基于深度学习的智能汽车自动变道横向控制方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332824
Lu Jianglin
{"title":"Intelligent Vehicle Automatic Lane Changing Lateral Control Method based on Deep Learning","authors":"Lu Jianglin","doi":"10.1109/IAAI51705.2020.9332824","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332824","url":null,"abstract":"The steering wheel control accuracy of traditional vehicle automatic lane changing lateral control method is poor, so a new lateral control method of intelligent vehicle automatic lane changing based on deep learning is proposed. Build an autonomous driving platform for smart cars, focus on the design of the automatic steering system, modify the steering wheel, calculate the resistance of the road steering wheel, use millimeter wave radar to complete detection and sensing; design the vehicle's lateral controller, which mainly uses fuzzy algorithm combination The sliding mode variable structure control method reduces the chattering problem of the sliding mode control method and enhances the control stability; optimizes the lane line recognition algorithm, uses the Sobel operator template to solve the pixel point gradient in the horizontal and vertical directions, and completes the lane line recognition. The simulation results show that the control angle of the steering wheel is closer to that of the target.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114301680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Prediction Method of Ground Deformation in Subway Tunnel Construction based on Gaussian Process Regression 基于高斯过程回归的地铁隧道施工地基变形预测方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332896
Dong-xia Liu, Yan Zhou
{"title":"A Prediction Method of Ground Deformation in Subway Tunnel Construction based on Gaussian Process Regression","authors":"Dong-xia Liu, Yan Zhou","doi":"10.1109/IAAI51705.2020.9332896","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332896","url":null,"abstract":"With the continuous development of urban traffic, the coverage area of the subway has gradually expanded, and the number of subway tunnel construction has increased significantly. To ensure that the construction process does not affect the ground, the ground deformation prediction method of subway tunnel construction is often used to predict the ground conditions. The method is not strong enough to analyze the ground deformation mechanism, which causes the problem that the predicted result is quite different from the measured result. Therefore, a prediction method of ground deformation based on Gaussian process regression is proposed. Set the ground displacement monitoring process, combined with the characteristics of tunnel construction, complete the monitoring and analysis of ground displacement data. The mechanism of ground deformation is analyzed, and combined with the grey prediction model, the ground deformation is predicted. Based on Gaussian process regression equation and covariance calculation results, a ground deformation prediction model is established. So far, the design of ground deformation prediction method for subway tunnel construction based on Gaussian process regression is completed. Constructing the experimental link, the comparison shows that the prediction result of this method is closer to the actual measurement result, which shows that this method is more effective for ground deformation prediction.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134464565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Estimation Method of Underwater Operation Robot Motion Pose Based on Bayesian Inference 基于贝叶斯推理的水下作业机器人运动姿态估计方法研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332904
Cheng Peng, Lu Shouqing
{"title":"Research on Estimation Method of Underwater Operation Robot Motion Pose Based on Bayesian Inference","authors":"Cheng Peng, Lu Shouqing","doi":"10.1109/IAAI51705.2020.9332904","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332904","url":null,"abstract":"Aiming at the problem of poor estimation effect of traditional underwater robot motion pose estimation methods, a Bayesian inference-based underwater robot motion pose estimation method is proposed. According to the specific characteristic parameters of the underwater vehicle, the specific transfer functions of the forward and backward motion estimation, the direction estimation and the fixed depth estimation are obtained, and the traditional Bayesian inference estimator, fuzzy Bayesian inference estimator and parallel fuzzy Bayesian are used. Inferred composite estimator, and established simulation estimation models under various motions of the robot according to the advancing and retreating distance, steering angle and depth values. The response results show that the parallel fuzzy Bayesian inference composite estimation algorithm is better for underwater robots. Good estimate effect. Considering the actual structure and motion of the underwater vehicle, a one-dimensional slide table is introduced as the center of gravity adjustment device to compensate the pitch caused by the disturbance of the center of gravity around the longitudinal axis. The disturbance observer is used to estimate the disturbance, and the discrete attitude variable structure estimation is used to estimate the pitch angle The results show that the chattering caused by switching has a weakening effect and has a good estimation effect on the motion of the underwater vehicle.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134112988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Constant Temperature Control System of Energy Storage Battery for New Energy Vehicles based on Fuzzy Strategy 基于模糊策略的新能源汽车蓄电池恒温控制系统
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332862
Yangyong Liu, Zongping Yang
{"title":"Constant Temperature Control System of Energy Storage Battery for New Energy Vehicles based on Fuzzy Strategy","authors":"Yangyong Liu, Zongping Yang","doi":"10.1109/iaai51705.2020.9332862","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332862","url":null,"abstract":"There is a deviation between the set value of the traditional control system and the actual value, which leads to the maximum overshoot of the system output temperature. Therefore, a constant temperature control system of energy storage battery for new energy vehicles based on fuzzy strategy is designed. In terms of hardware design, temperature sensing circuit and charge discharge circuit are optimized, DC-DC temperature controller and BR20 temperature heat exchanger are designed. In the aspect of software design, the modular program is used to design the temperature change signal acquisition process, and the fuzzy set theory of fuzzy strategy is used to quantify the constant temperature control parameters and optimize the constant temperature control algorithm to realize the system design. The experimental results show that the designed system reduces the maximum overshoot of output temperature and shortens the response time of constant temperature control.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125795860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automatic Acquisition Method of Geotechnical Engineering Survey Data based on Artificial Intelligence 基于人工智能的岩土工程测量数据自动获取方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332813
Gu Mudan
{"title":"Automatic Acquisition Method of Geotechnical Engineering Survey Data based on Artificial Intelligence","authors":"Gu Mudan","doi":"10.1109/IAAI51705.2020.9332813","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332813","url":null,"abstract":"The process of collecting survey data, the traditional automatic acquisition method of geotechnical engineering survey data does not integrate enough information, resulting in high packet loss rate. Therefore, an automatic data acquisition method for geotechnical engineering survey based on artificial intelligence is proposed. The 3D laser scanning data can be obtained to represent the local characteristics of rock and soil. GPS control network is set up to collect d-level and e-level GPS data. The information state features are extracted by using artificial agent, and the above data are integrated to realize the automatic acquisition of survey data. Comparing this method with the two traditional methods to collect cross-section node information of rock-soil tunnels, the results show that this method reduces the data packet loss rate and ensures the integrity of survey data.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130596004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimal Path Selection Model of Public Transportation Network Based on Improved Genetic Algorithm 基于改进遗传算法的公交网络最优路径选择模型
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332834
Donghua Long, Jia Tan
{"title":"Optimal Path Selection Model of Public Transportation Network Based on Improved Genetic Algorithm","authors":"Donghua Long, Jia Tan","doi":"10.1109/IAAI51705.2020.9332834","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332834","url":null,"abstract":"At present, the optimal path selection model of public transport network is not comprehensive considering the public transport factors, which leads to the long time of the optimal path selected by the model, and the selected path is not the optimal path. Therefore, algorithm, the optimal path selection model of public transport network is designed. The model constraints such as start and end point walking arc, transfer arc, driving arc and cost are calculated. Based on the optimal iterative selection characteristics of improved genetic algorithm, the optimal path selection model of public transport network is established; By determining the optimal path selection process of the public transportation network, the optimal public transportation network path is selected. Experimental results: The optimal path selection model proposed this time, when selecting the optimal path of the public transportation network, the optimal path selected by the public transportation network is shorter than the optimal path selected by other models, and it is in the public transportation network. In the network, the path selection time is also the shortest.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130519870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Feature Extraction of Color Hierarchical Structure of Indoor Space Based on Virtual Reality Technology 基于虚拟现实技术的室内空间颜色层次结构特征提取
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332899
Jing He, Bing Liu
{"title":"Feature Extraction of Color Hierarchical Structure of Indoor Space Based on Virtual Reality Technology","authors":"Jing He, Bing Liu","doi":"10.1109/iaai51705.2020.9332899","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332899","url":null,"abstract":"The traditional color hierarchical structure feature extraction method needs to establish the spectrum of each color, and the processing structure is highly affected by color resolution, which affects the accuracy of feature extraction. Aiming at the above problems, research on the feature extraction method of indoor spatial color hierarchy based on virtual reality technology. The parameters of virtual space modeling are obtained from the high color resolution images, and the indoor space modeling is carried out by using virtual reality technology. Carry on spatial color correction to the established model, and detect the edge of color hierarchy, and extract the characteristics of indoor spatial color hierarchy according to the principle of clustering. The experimental results show that the feature extraction method based on virtual reality technology has the advantages of short processing time, good extraction effect and reliability.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114160884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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