In view of the complex environment in the tunnel and the uneven lighting of the acquisition system, the lining images produced shadows and low contrast, a method of automatic color equalization combined with Laplacian pyramid (LP-ACE algorithm for short) was proposed in this paper. The computational complexity is reduced from the original O(N^4) to O ), which significantly reduces the amount of image computation and greatly improves the working efficiency. Due to the problems such as short time to identify skylights for cracks in key areas of subway tunnel, slow efficiency of manual method, inaccurate and difficult identification, an improved algorithm for key areas of power plant based on YOLO v5 was proposed: SD-YOLO. Ghost module is used to replace the traditional convolutional module to reduce the model parameters and improve the detection accuracy. The feature learning and feature extraction of crack region images are enhanced by the fusion of CBAM focus mechanism modules, while the influence of background on detection results is weakened. The bidirectional feature pyramid network is used for multi-scale feature fusion to reduce redundant calculation and improve the ability of the algorithm to detect small targets. The SD-YOLO algorithm proposed in this paper performs well in real samples, with an average accuracy of 93.1%, 11.3 percentage points higher than the original model, and significantly reduced parameters compared with the original model. Compared with YOLOv5s under the condition of reducing parameters, the model reasoning speed and detection accuracy are significantly improved by the proposed method, which can be effectively applied to tunnel detection.
{"title":"Subway Tunnel Crack Identification based on YOLOv5","authors":"Chongbin Mei, Yucheng Wen","doi":"10.54097/7gw4nw71","DOIUrl":"https://doi.org/10.54097/7gw4nw71","url":null,"abstract":"In view of the complex environment in the tunnel and the uneven lighting of the acquisition system, the lining images produced shadows and low contrast, a method of automatic color equalization combined with Laplacian pyramid (LP-ACE algorithm for short) was proposed in this paper. The computational complexity is reduced from the original O(N^4) to O ), which significantly reduces the amount of image computation and greatly improves the working efficiency. Due to the problems such as short time to identify skylights for cracks in key areas of subway tunnel, slow efficiency of manual method, inaccurate and difficult identification, an improved algorithm for key areas of power plant based on YOLO v5 was proposed: SD-YOLO. Ghost module is used to replace the traditional convolutional module to reduce the model parameters and improve the detection accuracy. The feature learning and feature extraction of crack region images are enhanced by the fusion of CBAM focus mechanism modules, while the influence of background on detection results is weakened. The bidirectional feature pyramid network is used for multi-scale feature fusion to reduce redundant calculation and improve the ability of the algorithm to detect small targets. The SD-YOLO algorithm proposed in this paper performs well in real samples, with an average accuracy of 93.1%, 11.3 percentage points higher than the original model, and significantly reduced parameters compared with the original model. Compared with YOLOv5s under the condition of reducing parameters, the model reasoning speed and detection accuracy are significantly improved by the proposed method, which can be effectively applied to tunnel detection. ","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128898","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}
Elevators serve as indispensable transportation systems in contemporary buildings, facilitating vertical mobility for occupants. However, the proliferation of tall buildings has exacerbated traffic congestion issues within elevator systems. A significant number of elevator passengers voice dissatisfaction with prolonged wait times, leading to impatience and frustration. Traditional approaches to address elevator traffic problems include installing additional elevators or implementing group control systems. However, these solutions often fall short due to designers' limited understanding of elevator traffic dynamics. This research seeks to address these challenges by employing Gaussian analysis to comprehensively examine elevator traffic patterns within a typical office building context. By analyzing both actual monitored data and predictions generated by LS-SVMs, the study aims to offer valuable insights into elevator traffic behavior. Additionally, the research endeavors to serve as a valuable resource for ETA (Elevator Traffic Analysis), providing designers with a deeper understanding of elevator traffic dynamics and guiding the development of more effective solutions to alleviate congestion and improve passenger experience within vertical transportation systems. Through this approach, the study contributes to advancements in elevator design and operation, ultimately enhancing the functionality and efficiency of vertical transportation systems in built environments.
{"title":"Gaussian Analysis of the Elevator Traffic under the Typical Office Building","authors":"Mo Shi, Xiaoyan Xu, Yeol Choi","doi":"10.54097/379xzj23","DOIUrl":"https://doi.org/10.54097/379xzj23","url":null,"abstract":"Elevators serve as indispensable transportation systems in contemporary buildings, facilitating vertical mobility for occupants. However, the proliferation of tall buildings has exacerbated traffic congestion issues within elevator systems. A significant number of elevator passengers voice dissatisfaction with prolonged wait times, leading to impatience and frustration. Traditional approaches to address elevator traffic problems include installing additional elevators or implementing group control systems. However, these solutions often fall short due to designers' limited understanding of elevator traffic dynamics. This research seeks to address these challenges by employing Gaussian analysis to comprehensively examine elevator traffic patterns within a typical office building context. By analyzing both actual monitored data and predictions generated by LS-SVMs, the study aims to offer valuable insights into elevator traffic behavior. Additionally, the research endeavors to serve as a valuable resource for ETA (Elevator Traffic Analysis), providing designers with a deeper understanding of elevator traffic dynamics and guiding the development of more effective solutions to alleviate congestion and improve passenger experience within vertical transportation systems. Through this approach, the study contributes to advancements in elevator design and operation, ultimately enhancing the functionality and efficiency of vertical transportation systems in built environments.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128991","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}
In order to solve the problems of poor detection algorithms, high network model complexity, and difficult deployment of algorithms in the field of aerial image target detection. In this paper, based on YOLOv7-tiny algorithm, a lightweight target detection network for UAV aerial images is designed. Partial convolutional PConv is introduced into the network, and the feature extraction block ELAN is improved, which reduces the computational volume of convolution and the number of model parameters in the feature extraction process, thus solving the problem of model lightweight. The feature fusion part of the network is optimal to improve the feature extraction ability of the network for small targets. At the same time, the large target detection layer in the original network is replaced with the small target detection layer in the aerial images, and the attention mechanism is embedded in the backbone network, which solves the problem of imperfect detection algorithms in aerial images. The loss function of the network is improved so that the prediction frames generated by the detection network and the truth frames match each other in the regression process, thus improving the training process of the network. The experimental results on the publicly available dataset VisDrone2019 dataset show that compared with the YOLOv7-tiny algorithm, the detection accuracy of the proposed model is improved by 0.7%, the recall R is improved by 2.2%, the F1 value is improved by 1.6%, the average detection accuracy mean is improved by 2.3%, and the number of parameters is reduced by 52.1%. Moreover, the image detection speed FPS reaches 66/f.s-1, which meets the real-time requirements of the aerial image detection model detection, and provides a research idea for the field of UAV aerial image detection.
{"title":"A Lightweight Object Detection Network for UAV Aerial Images","authors":"Lin Tang, Shunyong Zhou, Xinjie Wang","doi":"10.54097/c5q8fv57","DOIUrl":"https://doi.org/10.54097/c5q8fv57","url":null,"abstract":"In order to solve the problems of poor detection algorithms, high network model complexity, and difficult deployment of algorithms in the field of aerial image target detection. In this paper, based on YOLOv7-tiny algorithm, a lightweight target detection network for UAV aerial images is designed. Partial convolutional PConv is introduced into the network, and the feature extraction block ELAN is improved, which reduces the computational volume of convolution and the number of model parameters in the feature extraction process, thus solving the problem of model lightweight. The feature fusion part of the network is optimal to improve the feature extraction ability of the network for small targets. At the same time, the large target detection layer in the original network is replaced with the small target detection layer in the aerial images, and the attention mechanism is embedded in the backbone network, which solves the problem of imperfect detection algorithms in aerial images. The loss function of the network is improved so that the prediction frames generated by the detection network and the truth frames match each other in the regression process, thus improving the training process of the network. The experimental results on the publicly available dataset VisDrone2019 dataset show that compared with the YOLOv7-tiny algorithm, the detection accuracy of the proposed model is improved by 0.7%, the recall R is improved by 2.2%, the F1 value is improved by 1.6%, the average detection accuracy mean is improved by 2.3%, and the number of parameters is reduced by 52.1%. Moreover, the image detection speed FPS reaches 66/f.s-1, which meets the real-time requirements of the aerial image detection model detection, and provides a research idea for the field of UAV aerial image detection.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128895","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}
Cultivating talents is a major plan for the long-term development of the country and the nation, the new era, the country and society put forward higher requirements for college and university students, college libraries as a culture of education, moral education, as an important position, shoulder with an important mission. This paper uses the new concept of General Secretary Xi Jinping on the work of talents in the new era as a guide, and takes the demand of compound talent cultivation as the orientation. Analyze the shortcomings of intelligent services in university libraries in western border areas such as Yunnan, and explore feasible solutions for improving and optimizing library intelligent services, in order to enhance the efficiency of intelligent services and expand service capabilities of university libraries in the region, thereby promoting the improvement of talent cultivation quality in universities.
{"title":"Intelligent Service of College Library based on the Demand of Compound Talents Training Path Analysis","authors":"Han Song, Luying Gan, Yue Sha","doi":"10.54097/mrgpm695","DOIUrl":"https://doi.org/10.54097/mrgpm695","url":null,"abstract":"Cultivating talents is a major plan for the long-term development of the country and the nation, the new era, the country and society put forward higher requirements for college and university students, college libraries as a culture of education, moral education, as an important position, shoulder with an important mission. This paper uses the new concept of General Secretary Xi Jinping on the work of talents in the new era as a guide, and takes the demand of compound talent cultivation as the orientation. Analyze the shortcomings of intelligent services in university libraries in western border areas such as Yunnan, and explore feasible solutions for improving and optimizing library intelligent services, in order to enhance the efficiency of intelligent services and expand service capabilities of university libraries in the region, thereby promoting the improvement of talent cultivation quality in universities.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128890","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}
This paper describes in detail the development process of Student Attendance Management System based on Spring Boot, Vue.js and MySQL. The system aims to provide an efficient and automated solution for recording and managing student attendance to improve the daily management efficiency of educational institutions and reduce the administrative burden of teachers. The system adopts a modularized design, covering functional modules such as user management, student management, teacher management, class and course management, attendance record, leave management, statistical report and system settings. Through the practice of this project, we can have a deeper understanding of the powerful functions of modern Web development technology and its application prospects, and deepen our knowledge of Spring Boot back-end development, Vue.js front-end design and MySQL database operation in practical applications.
本文详细介绍了基于 Spring Boot、Vue.js 和 MySQL 的学生考勤管理系统的开发过程。该系统旨在为记录和管理学生考勤提供一个高效、自动化的解决方案，以提高教育机构的日常管理效率，减轻教师的行政负担。系统采用模块化设计，涵盖用户管理、学生管理、教师管理、班级和课程管理、考勤记录、请假管理、统计报表和系统设置等功能模块。通过本项目的实践，我们可以更深入地了解现代Web开发技术的强大功能及其应用前景，加深对Spring Boot后端开发、Vue.js前端设计和MySQL数据库操作在实际应用中的认识。
{"title":"Design and Implementation of a Student Attendance Management System based on Springboot and Vue Technology","authors":"Yixuan Liu","doi":"10.54097/nv0yd129","DOIUrl":"https://doi.org/10.54097/nv0yd129","url":null,"abstract":"This paper describes in detail the development process of Student Attendance Management System based on Spring Boot, Vue.js and MySQL. The system aims to provide an efficient and automated solution for recording and managing student attendance to improve the daily management efficiency of educational institutions and reduce the administrative burden of teachers. The system adopts a modularized design, covering functional modules such as user management, student management, teacher management, class and course management, attendance record, leave management, statistical report and system settings. Through the practice of this project, we can have a deeper understanding of the powerful functions of modern Web development technology and its application prospects, and deepen our knowledge of Spring Boot back-end development, Vue.js front-end design and MySQL database operation in practical applications.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128894","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}
This study discusses the application of multi-modal large model in robot control. With the rapid development of AI and robotics, multi-modal large-scale model, as a large-scale deep learning model integrating multiple sensing modes, provides new ideas and methods for intelligent control of robots in complex environments. Firstly, this paper introduces the basic principle and technical characteristics of multi-modal large-scale model, including its structure, training methods and application scenarios. Then, aiming at the specific application scenarios in smart home environment, this paper designs a series of experiments to evaluate the performance of multi-modal large model in path planning, task effect and generalization ability. The experimental results show that the multi-modal large model can achieve more accurate and efficient path planning and task execution in smart home environment, and has strong generalization ability, which can adapt to the needs of different environments and tasks. Finally, this paper summarizes and looks forward to the application of multi-modal large model in robot control, and points out its important significance and potential application prospect in the development of intelligent robot technology.
{"title":"Research on Application of Multi-modal Large Model in Robot Control","authors":"Xiran Su","doi":"10.54097/5f57td48","DOIUrl":"https://doi.org/10.54097/5f57td48","url":null,"abstract":"This study discusses the application of multi-modal large model in robot control. With the rapid development of AI and robotics, multi-modal large-scale model, as a large-scale deep learning model integrating multiple sensing modes, provides new ideas and methods for intelligent control of robots in complex environments. Firstly, this paper introduces the basic principle and technical characteristics of multi-modal large-scale model, including its structure, training methods and application scenarios. Then, aiming at the specific application scenarios in smart home environment, this paper designs a series of experiments to evaluate the performance of multi-modal large model in path planning, task effect and generalization ability. The experimental results show that the multi-modal large model can achieve more accurate and efficient path planning and task execution in smart home environment, and has strong generalization ability, which can adapt to the needs of different environments and tasks. Finally, this paper summarizes and looks forward to the application of multi-modal large model in robot control, and points out its important significance and potential application prospect in the development of intelligent robot technology.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128938","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}
ChatGPT is a kind of natural language processing technology based on generative artificial intelligence, which has powerful ability of language processing, judgment and correction. The development of artificial intelligence has greatly promoted the progress of machine translation, that is, in order to improve the efficiency of translation, artificial intelligence translation technology came into being, so ChatGPT has also gained keen attention in the translation field. However, the challenges and problems brought by new technologies are also prominent, and how to make better use of new technologies to promote the development of translation studies is an important issue that needs to be solved at present. Therefore, this paper discusses the feasibility of artificial intelligence ChatGPT in translation field from the aspects of its application, dilemma and countermeasures.
{"title":"The Feasibility Study of Artificial Intelligence ChatGPT in Translation Field","authors":"Ling Ye","doi":"10.54097/5vp4mn42","DOIUrl":"https://doi.org/10.54097/5vp4mn42","url":null,"abstract":"ChatGPT is a kind of natural language processing technology based on generative artificial intelligence, which has powerful ability of language processing, judgment and correction. The development of artificial intelligence has greatly promoted the progress of machine translation, that is, in order to improve the efficiency of translation, artificial intelligence translation technology came into being, so ChatGPT has also gained keen attention in the translation field. However, the challenges and problems brought by new technologies are also prominent, and how to make better use of new technologies to promote the development of translation studies is an important issue that needs to be solved at present. Therefore, this paper discusses the feasibility of artificial intelligence ChatGPT in translation field from the aspects of its application, dilemma and countermeasures.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128942","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}
Dispersive soil is a kind of special soil with water sensitivity, which is easy to produce ravages such as gully and piping when encountering water in engineering. In order to improve the poor engineering properties of dispersive soil, a kind of lignin was selected to improve the dispersibility and mechanical properties of dispersive soil in western Jilin Province. Pinhole test, fragment test, unconfined compressive strength test and resistivity test were carried out on the improved soil samples with different lignin content. The results showed that lignin could significantly reduce the dispersibility of dispersive soil. With the increasing of curing time, the unconfined compressive strength of the improved soil samples increased gradually. With the increase of lignin content, the unconfined compressive strength of the improved soil first increased and then decreased, and the peak strength appeared when the lignin content was 3%. In the resistivity test, the resistivity of the improved soil decreased gradually with the increase of lignin content. Through microscopic analysis of lignin improved soil samples, it can be concluded that lignin fibers play a stereograin-like bridging role in soil, which promotes the formation of larger aggregates, weakens the dispersion of single soil particles, and thus reduces the dispersion of soil mass and improves the strength of soil mass. This study can provide a basis for the improvement of dispersive soil in seasonal freezing area and has practical engineering significance.
{"title":"Analysis of Dispersibility and Mechanical Properties of Lignin Modified Dispersive Soil","authors":"Zhongyu Yu, Xin Xu, Hao Liu, Zeju Wu","doi":"10.54097/7pxy3d03","DOIUrl":"https://doi.org/10.54097/7pxy3d03","url":null,"abstract":"Dispersive soil is a kind of special soil with water sensitivity, which is easy to produce ravages such as gully and piping when encountering water in engineering. In order to improve the poor engineering properties of dispersive soil, a kind of lignin was selected to improve the dispersibility and mechanical properties of dispersive soil in western Jilin Province. Pinhole test, fragment test, unconfined compressive strength test and resistivity test were carried out on the improved soil samples with different lignin content. The results showed that lignin could significantly reduce the dispersibility of dispersive soil. With the increasing of curing time, the unconfined compressive strength of the improved soil samples increased gradually. With the increase of lignin content, the unconfined compressive strength of the improved soil first increased and then decreased, and the peak strength appeared when the lignin content was 3%. In the resistivity test, the resistivity of the improved soil decreased gradually with the increase of lignin content. Through microscopic analysis of lignin improved soil samples, it can be concluded that lignin fibers play a stereograin-like bridging role in soil, which promotes the formation of larger aggregates, weakens the dispersion of single soil particles, and thus reduces the dispersion of soil mass and improves the strength of soil mass. This study can provide a basis for the improvement of dispersive soil in seasonal freezing area and has practical engineering significance.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128808","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}
In order to simplify the process of patients' medical treatment and realise contactless and efficient medical treatment in the post-epidemic era, a convenient medical treatment system oriented to medical smart cockpit is designed to facilitate patients' medical treatment. The system is based on STM32F103RCT6 as the main controller chip, and the peripheral circuit consists of MAX30102 sensor, DS18B20 sensor, and Bluetooth module, which can realise the transmission of basic physiological data collected from patients to the doctor's end. The system uses Qt Creator to design the application interface, and eventually the patient can complete the relevant medical process in the cockpit. This design reduces the contact between the patient and the healthcare personnel and improves the efficiency of hospital visits.
{"title":"Research and Design of STM32 and Qt based Medical Smart Cockpit Convenient Medical Care System","authors":"Chen Li, Zhesheng Hou, Yu Wang, Xin Zhang","doi":"10.54097/486rm605","DOIUrl":"https://doi.org/10.54097/486rm605","url":null,"abstract":"In order to simplify the process of patients' medical treatment and realise contactless and efficient medical treatment in the post-epidemic era, a convenient medical treatment system oriented to medical smart cockpit is designed to facilitate patients' medical treatment. The system is based on STM32F103RCT6 as the main controller chip, and the peripheral circuit consists of MAX30102 sensor, DS18B20 sensor, and Bluetooth module, which can realise the transmission of basic physiological data collected from patients to the doctor's end. The system uses Qt Creator to design the application interface, and eventually the patient can complete the relevant medical process in the cockpit. This design reduces the contact between the patient and the healthcare personnel and improves the efficiency of hospital visits.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128825","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}
In the fast -paced life, people's pursuit of high -quality audio equipment has continued to increase. With the advancement of science and technology, the combination of cloud and edge computing provides the possibility for processing large amounts of data and real -time response. To deal with, a set of optimized solutions is proposed on the problem of poor sound quality of Bluetooth headsets on the current market. The optimized Bluetooth headset is effective on the reduction of background noise, providing a clearer listening environment. The decline has greatly improved the purity of the audio and the fineness of hearing. In terms of energy consumption efficiency, the battery life of the Bluetooth headset has been improved.
{"title":"Research on the Optimization of Headset Optimization Technology based on Cloud and Edge Computing","authors":"Qijie Lai, Chao Ma, Qiaoyang Yin, Qiuying Li, Kewei Zhou, Zilin Ma","doi":"10.54097/je9wem29","DOIUrl":"https://doi.org/10.54097/je9wem29","url":null,"abstract":"In the fast -paced life, people's pursuit of high -quality audio equipment has continued to increase. With the advancement of science and technology, the combination of cloud and edge computing provides the possibility for processing large amounts of data and real -time response. To deal with, a set of optimized solutions is proposed on the problem of poor sound quality of Bluetooth headsets on the current market. The optimized Bluetooth headset is effective on the reduction of background noise, providing a clearer listening environment. The decline has greatly improved the purity of the audio and the fineness of hearing. In terms of energy consumption efficiency, the battery life of the Bluetooth headset has been improved.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128747","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}
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