With the increase of energy consumption worldwide in several domains such as industry,education,and transportation,several technologies played an influential role in energy conservation such as the Internet of Things(I...With the increase of energy consumption worldwide in several domains such as industry,education,and transportation,several technologies played an influential role in energy conservation such as the Internet of Things(IoT).In this article,we describe the design and implementation of an IoT-based energy conser-vation smart classroom system that contributes to energy conservation in the edu-cation domain.The proposed system not only allows the user to access and control IoT devices(e.g.,lights,projectors,and air conditions)in real-time,it also has the capability to aggregate the estimated energy consumption of an IoT device,the smart classroom,and the building based on the energy consumption and cost model that we propose.Moreover,the proposed model aggregates the estimated energy cost according to the Saudi Electricity Company(SEC)rates.Furthermore,the model aggregates in real-time the estimated energy conservation percentage and estimated money-saving percentage compared to data collected when the system wasn't used.The feasibility and benefits of our system have been validated on a real-world scenario which is a classroom in the college of computer science and engineering,Taibah University,Yanbu branch.The results of the experimental studies are promising in energy conservation and cost-saving when using our proposed system.展开更多
Smart classroom is an inevitable result of the deepening integration of new-generation information technology and education means,and it is an unavoidable choice of university education informatization in the intellig...Smart classroom is an inevitable result of the deepening integration of new-generation information technology and education means,and it is an unavoidable choice of university education informatization in the intelligent era.The Bridge-in,Outcomes,Pre-assessment,Participatory Learning,Post-assessment,and Summary(BOPPPS)model is used to construct the effective teaching mode of a smart classroom based on the analyses of the connotation and characteristics of a smart classroom,and the teaching reform and practice are carried out on the“Road Engineering Construction Technology and Organization”course.Through a questionnaire survey,it is found that the construction of a smart classroom effective teaching model can fully mobilize students’learning enthusiasm and improve the efficiency and effectiveness of students’learning.展开更多
Facing the information age,college teachers need to innovate teaching methods constantly and realize student-centered teaching reform.This paper takes the“Agile estimation”teaching unit of“Software Project Managem...Facing the information age,college teachers need to innovate teaching methods constantly and realize student-centered teaching reform.This paper takes the“Agile estimation”teaching unit of“Software Project Management”as the research object,and carries out the teaching process design and application of BOPPPS model based on smart classroom according to the teaching purpose and content of the teaching unit.In teaching practice,multi-dimensional blended teaching mode is adopted and a variety of teaching methods are used to realize the teaching loop from online to offline and then to online.The results show that the teaching mode enhances students’learning enthusiasm,enhances students’participation and subjective initiative,and effectively improves the teaching effect of the course.展开更多
Under the guidance of Education Informatization 2.0 with the policy background of“prioritizing the development of education,speed up the education modernization,and build an education powerhouse”,major universities ...Under the guidance of Education Informatization 2.0 with the policy background of“prioritizing the development of education,speed up the education modernization,and build an education powerhouse”,major universities have responded to the policy,and built a batch of smart classrooms in line with the development of university teaching,laying a solid foundation for promoting university teaching reformation.The author complied the necessity of smart classroom construction from the theoretical level,as well as the current construction status of the smart classroom at home and abroad,and finally,this paper takes Guangxi University of Finance and Economics as an example to analyze the teaching advantages of the school,how to promote the deep integration of information technology in education and teaching,and put forward a powerful plan for the construction of the smart classroom in school teaching,and the practical application of group discussion in smart classroom as an example to discuss the smart teaching.This kind of classroom teaching will provide a reference for leaders,students and teachers.展开更多
With the advancement of science and technology as well as the rapid development of next generation information technologies,such as big data and artificial intelligence,smart classrooms have emerged as the times have ...With the advancement of science and technology as well as the rapid development of next generation information technologies,such as big data and artificial intelligence,smart classrooms have emerged as the times have demanded.Adopting innovative teaching modes in smart classrooms allows the realization of various teaching techniques that cannot be achieved in traditional classrooms.Especially for some courses in medical schools,due to changes in the medical environment and the improvement of patients’awareness of medical rights and interests,the traditional teaching methods are becoming more restricted.For example,in clinical surgery,due to the increasing number of medical students in recent years and requirements for strict aseptic principle adherence in operating rooms,practical teaching has encountered great restrictions,thus preventing it from meeting the needs of students.In order to solve this problem,this research constructs a smart classroom teaching model for surgical practice teaching based on hardware equipment,such as smart classrooms,interconnected surgical mobile broadcast equipment,and intelligent medical simulators.Through this teaching model,the teaching effect and quality are further analyzed,laying a foundation for smart teaching in future medical courses.展开更多
Internet of Things technology is a new type of network technology emerging in the new economic era. It has played a good role in various industries and provided new opportunities for the reform and optimization of the...Internet of Things technology is a new type of network technology emerging in the new economic era. It has played a good role in various industries and provided new opportunities for the reform and optimization of the education industry. This paper takes the intelligent teaching base on the basis of Internet of Things technology as the research object, introduces the connotation of the wisdom teaching base with reference to relevant literature materials, analyzes the research background of the wisdom teaching base on the basis of the Internet of Things technology, expounds the design method of smart teaching base on the basis of Internet of Things technology, and analyzes the function realization and application of intelligent teaching base on the basis of Internet of Things technology.展开更多
The invention of Phasor Measurement Units(PMUs)produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible.PMUs are used in transmit...The invention of Phasor Measurement Units(PMUs)produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible.PMUs are used in transmitting data to Phasor Data Concentrators(PDC)placed in control centers for monitoring purpose.A primary concern of system operators in control centers is maintaining safe and efficient operation of the power grid.This can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal data.The normal data indicates the normal behavior of the grid whereas the abnormal data indicates fault or abnormal conditions in power grid.As a result,detecting anomalies/abnormal conditions in the fast flowing PMU data that reflects the status of the power system is critical.A novel methodology for detecting and categorizing abnormalities in streaming PMU data is presented in this paper.The proposed method consists of three modules namely,offline Gaussian Mixture Model(GMM),online GMM for identifying anomalies and clustering ensemble model for classifying the anomalies.The significant features of the proposed method are detecting anomalies while taking into account of multivariate nature of the PMU dataset,adapting to concept drift in the flowing PMU data without retraining the existing model unnecessarily and classifying the anomalies.The proposed model is implemented in Python and the testing results prove that the proposed model is well suited for detection and classification of anomalies on the fly.展开更多
Computational intelligence(CI)is a group of nature-simulated computationalmodels and processes for addressing difficult real-life problems.The CI is useful in the UAV domain as it produces efficient,precise,and rapid ...Computational intelligence(CI)is a group of nature-simulated computationalmodels and processes for addressing difficult real-life problems.The CI is useful in the UAV domain as it produces efficient,precise,and rapid solutions.Besides,unmanned aerial vehicles(UAV)developed a hot research topic in the smart city environment.Despite the benefits of UAVs,security remains a major challenging issue.In addition,deep learning(DL)enabled image classification is useful for several applications such as land cover classification,smart buildings,etc.This paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification(MDLS-UAVIC)model in a smart city environment.Themajor purpose of the MDLS-UAVIC algorithm is to securely encrypt the images and classify them into distinct class labels.The proposedMDLS-UAVIC model follows a two-stage process:encryption and image classification.The encryption technique for image encryption effectively encrypts the UAV images.Next,the image classification process involves anXception-based deep convolutional neural network for the feature extraction process.Finally,shuffled shepherd optimization(SSO)with a recurrent neural network(RNN)model is applied for UAV image classification,showing the novelty of the work.The experimental validation of the MDLS-UAVIC approach is tested utilizing a benchmark dataset,and the outcomes are examined in various measures.It achieved a high accuracy of 98%.展开更多
Dear Editor,This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment(DSA).Based on tree algorithms technique,the data-driven smart gri...Dear Editor,This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment(DSA).Based on tree algorithms technique,the data-driven smart grid DSA has received significant research interests in recent years.展开更多
Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road accidents.As a resu...Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road accidents.As a result,reckless driving behaviour can cause congestion and delays.Computer vision and multimodal sensors have been used to study driving behaviour categorization to lessen this problem.Previous research has also collected and analyzed a wide range of data,including electroencephalography(EEG),electrooculography(EOG),and photographs of the driver’s face.On the other hand,driving a car is a complicated action that requires a wide range of body move-ments.In this work,we proposed a ResNet-SE model,an efficient deep learning classifier for driving activity clas-sification based on signal data obtained in real-world traffic conditions using smart glasses.End-to-end learning can be achieved by combining residual networks and channel attention approaches into a single learning model.Sensor data from 3-point EOG electrodes,tri-axial accelerometer,and tri-axial gyroscope from the Smart Glasses dataset was utilized in this study.We performed various experiments and compared the proposed model to base-line deep learning algorithms(CNNs and LSTMs)to demonstrate its performance.According to the research results,the proposed model outperforms the previous deep learning models in this domain with an accuracy of 99.17%and an F1-score of 98.96%.展开更多
Smart education is the future and development direction of higher education.Taking the graduate course Crime and Police Theory as the research subject,the shortcomings of smart education,which include the lack of unde...Smart education is the future and development direction of higher education.Taking the graduate course Crime and Police Theory as the research subject,the shortcomings of smart education,which include the lack of understanding of the concept of smart education,the limited content structure of smart education,the poor cognition of smart education among teachers and students,and inadequate hardware and technical support for smart education,are systematically analyzed.In view of these shortcomings,several strategies are proposed,including improving the smart education curriculum development plan and management level,ensuring the construction quality of smart education projects,and raising funds for smart education construction from various sources.展开更多
A significant fraction of the world’s population is living in cities. With the rapid development ofinformation and computing technologies (ICT), cities may be made smarter by embedding ICT intotheir infrastructure. B...A significant fraction of the world’s population is living in cities. With the rapid development ofinformation and computing technologies (ICT), cities may be made smarter by embedding ICT intotheir infrastructure. By smarter, we mean that the city operation will be more efficient, cost-effective,energy-saving, be more connected, more secure, and more environmentally friendly. As such, a smartcity is typically defined as a city that has a strong integration with ICT in all its components, includingits physical components, social components, and business components [1,2].展开更多
This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate ...This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate challenges, the research analyzed how smart city frameworks, aligned with climate neutrality objectives, leverage geospatial technologies for urban planning and climate action. The study included case studies from three leading European cities, extracting lessons and best practices in implementing Climate City Contracts across sectors like energy, transport, and waste management. These insights highlighted the essential role of EU and national authorities in providing technical, regulatory, and financial support. Additionally, the paper presented the application of a WEBGIS platform in Limassol Municipality, Cyprus, demonstrating citizen engagement and acceptance of the proposed geospatial framework. Concluding with recommendations for future research, the study contributed significant insights into the advancement of urban sustainability and the effectiveness of geospatial technologies in smart city initiatives for combating climate change.展开更多
Smart materials,which exhibit shape memory behavior in response to external stimuli,have shown great potential for use in biomedical applications.In this study,an energetic composite was fabricated using a UV-assisted...Smart materials,which exhibit shape memory behavior in response to external stimuli,have shown great potential for use in biomedical applications.In this study,an energetic composite was fabricated using a UV-assisted DIW 3D printing technique and a shape memory material(SMP)as the binder.This composite has the ability to reduce the impact of external factors and adjust gun propellant combustion behavior.The composition and 3D printing process were delineated,while the internal structure and shape memory performance of the composite material were studied.The energetic SMP composite exhibits an angle of reversal of 18 s at 70°,with a maximum elongation typically reaching up to 280% of the original length and a recovery length of approximately 105%during ten cycles.Additionally,thermal decomposition and combustion behavior were also demonstrated for the energetic SMP composite.展开更多
文摘With the increase of energy consumption worldwide in several domains such as industry,education,and transportation,several technologies played an influential role in energy conservation such as the Internet of Things(IoT).In this article,we describe the design and implementation of an IoT-based energy conser-vation smart classroom system that contributes to energy conservation in the edu-cation domain.The proposed system not only allows the user to access and control IoT devices(e.g.,lights,projectors,and air conditions)in real-time,it also has the capability to aggregate the estimated energy consumption of an IoT device,the smart classroom,and the building based on the energy consumption and cost model that we propose.Moreover,the proposed model aggregates the estimated energy cost according to the Saudi Electricity Company(SEC)rates.Furthermore,the model aggregates in real-time the estimated energy conservation percentage and estimated money-saving percentage compared to data collected when the system wasn't used.The feasibility and benefits of our system have been validated on a real-world scenario which is a classroom in the college of computer science and engineering,Taibah University,Yanbu branch.The results of the experimental studies are promising in energy conservation and cost-saving when using our proposed system.
文摘Smart classroom is an inevitable result of the deepening integration of new-generation information technology and education means,and it is an unavoidable choice of university education informatization in the intelligent era.The Bridge-in,Outcomes,Pre-assessment,Participatory Learning,Post-assessment,and Summary(BOPPPS)model is used to construct the effective teaching mode of a smart classroom based on the analyses of the connotation and characteristics of a smart classroom,and the teaching reform and practice are carried out on the“Road Engineering Construction Technology and Organization”course.Through a questionnaire survey,it is found that the construction of a smart classroom effective teaching model can fully mobilize students’learning enthusiasm and improve the efficiency and effectiveness of students’learning.
文摘Facing the information age,college teachers need to innovate teaching methods constantly and realize student-centered teaching reform.This paper takes the“Agile estimation”teaching unit of“Software Project Management”as the research object,and carries out the teaching process design and application of BOPPPS model based on smart classroom according to the teaching purpose and content of the teaching unit.In teaching practice,multi-dimensional blended teaching mode is adopted and a variety of teaching methods are used to realize the teaching loop from online to offline and then to online.The results show that the teaching mode enhances students’learning enthusiasm,enhances students’participation and subjective initiative,and effectively improves the teaching effect of the course.
文摘Under the guidance of Education Informatization 2.0 with the policy background of“prioritizing the development of education,speed up the education modernization,and build an education powerhouse”,major universities have responded to the policy,and built a batch of smart classrooms in line with the development of university teaching,laying a solid foundation for promoting university teaching reformation.The author complied the necessity of smart classroom construction from the theoretical level,as well as the current construction status of the smart classroom at home and abroad,and finally,this paper takes Guangxi University of Finance and Economics as an example to analyze the teaching advantages of the school,how to promote the deep integration of information technology in education and teaching,and put forward a powerful plan for the construction of the smart classroom in school teaching,and the practical application of group discussion in smart classroom as an example to discuss the smart teaching.This kind of classroom teaching will provide a reference for leaders,students and teachers.
基金2020 Education and Teaching Reform Research Project of Xi’an Medical University“Research on Smart Classroom Model of Surgery Practice Teaching Based on 5G Environment”(Project Number:2020JG-09)2021 Shaanxi Undergraduate and Higher Continuing Education Teaching Reform Research Project of Shaanxi Provincial Department of Education“Research on Smart Classroom Model of Surgical Practice Teaching Based on 5G Environment”(Project Number:21BY135)。
文摘With the advancement of science and technology as well as the rapid development of next generation information technologies,such as big data and artificial intelligence,smart classrooms have emerged as the times have demanded.Adopting innovative teaching modes in smart classrooms allows the realization of various teaching techniques that cannot be achieved in traditional classrooms.Especially for some courses in medical schools,due to changes in the medical environment and the improvement of patients’awareness of medical rights and interests,the traditional teaching methods are becoming more restricted.For example,in clinical surgery,due to the increasing number of medical students in recent years and requirements for strict aseptic principle adherence in operating rooms,practical teaching has encountered great restrictions,thus preventing it from meeting the needs of students.In order to solve this problem,this research constructs a smart classroom teaching model for surgical practice teaching based on hardware equipment,such as smart classrooms,interconnected surgical mobile broadcast equipment,and intelligent medical simulators.Through this teaching model,the teaching effect and quality are further analyzed,laying a foundation for smart teaching in future medical courses.
文摘Internet of Things technology is a new type of network technology emerging in the new economic era. It has played a good role in various industries and provided new opportunities for the reform and optimization of the education industry. This paper takes the intelligent teaching base on the basis of Internet of Things technology as the research object, introduces the connotation of the wisdom teaching base with reference to relevant literature materials, analyzes the research background of the wisdom teaching base on the basis of the Internet of Things technology, expounds the design method of smart teaching base on the basis of Internet of Things technology, and analyzes the function realization and application of intelligent teaching base on the basis of Internet of Things technology.
文摘The invention of Phasor Measurement Units(PMUs)produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible.PMUs are used in transmitting data to Phasor Data Concentrators(PDC)placed in control centers for monitoring purpose.A primary concern of system operators in control centers is maintaining safe and efficient operation of the power grid.This can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal data.The normal data indicates the normal behavior of the grid whereas the abnormal data indicates fault or abnormal conditions in power grid.As a result,detecting anomalies/abnormal conditions in the fast flowing PMU data that reflects the status of the power system is critical.A novel methodology for detecting and categorizing abnormalities in streaming PMU data is presented in this paper.The proposed method consists of three modules namely,offline Gaussian Mixture Model(GMM),online GMM for identifying anomalies and clustering ensemble model for classifying the anomalies.The significant features of the proposed method are detecting anomalies while taking into account of multivariate nature of the PMU dataset,adapting to concept drift in the flowing PMU data without retraining the existing model unnecessarily and classifying the anomalies.The proposed model is implemented in Python and the testing results prove that the proposed model is well suited for detection and classification of anomalies on the fly.
基金Deputyship for Research&Inno-vation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number RI-44-0446.
文摘Computational intelligence(CI)is a group of nature-simulated computationalmodels and processes for addressing difficult real-life problems.The CI is useful in the UAV domain as it produces efficient,precise,and rapid solutions.Besides,unmanned aerial vehicles(UAV)developed a hot research topic in the smart city environment.Despite the benefits of UAVs,security remains a major challenging issue.In addition,deep learning(DL)enabled image classification is useful for several applications such as land cover classification,smart buildings,etc.This paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification(MDLS-UAVIC)model in a smart city environment.Themajor purpose of the MDLS-UAVIC algorithm is to securely encrypt the images and classify them into distinct class labels.The proposedMDLS-UAVIC model follows a two-stage process:encryption and image classification.The encryption technique for image encryption effectively encrypts the UAV images.Next,the image classification process involves anXception-based deep convolutional neural network for the feature extraction process.Finally,shuffled shepherd optimization(SSO)with a recurrent neural network(RNN)model is applied for UAV image classification,showing the novelty of the work.The experimental validation of the MDLS-UAVIC approach is tested utilizing a benchmark dataset,and the outcomes are examined in various measures.It achieved a high accuracy of 98%.
基金supported in part by the Internal Talent Award with Wallenberg-NTU Presidential Postdoctoral Fellowship 2022the National Research Foundation,Singapore and DSO National Laboratories under the AI Singapore Program(AISG2-RP-2020-019)+1 种基金the Joint SDU-NTU Centre for AI Research(C-FAIR),the RIE 2020 Advanced Manufacturing and Engineering(AME)Programmatic Fund,Singapore(A20G8b0102)NOE Tier 1 Projects(RG59/22&RT9/22)。
文摘Dear Editor,This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment(DSA).Based on tree algorithms technique,the data-driven smart grid DSA has received significant research interests in recent years.
基金support provided by Thammasat University Research fund under the TSRI,Contract Nos.TUFF19/2564 and TUFF24/2565for the project of“AI Ready City Networking in RUN”,based on the RUN Digital Cluster collaboration scheme.This research project was also supported by the Thailand Science Research and Innovation fund,the University of Phayao(Grant No.FF65-RIM041)supported by National Science,Research and Innovation(NSRF),and King Mongkut’s University of Technology North Bangkok,Contract No.KMUTNB-FF-66-07.
文摘Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road accidents.As a result,reckless driving behaviour can cause congestion and delays.Computer vision and multimodal sensors have been used to study driving behaviour categorization to lessen this problem.Previous research has also collected and analyzed a wide range of data,including electroencephalography(EEG),electrooculography(EOG),and photographs of the driver’s face.On the other hand,driving a car is a complicated action that requires a wide range of body move-ments.In this work,we proposed a ResNet-SE model,an efficient deep learning classifier for driving activity clas-sification based on signal data obtained in real-world traffic conditions using smart glasses.End-to-end learning can be achieved by combining residual networks and channel attention approaches into a single learning model.Sensor data from 3-point EOG electrodes,tri-axial accelerometer,and tri-axial gyroscope from the Smart Glasses dataset was utilized in this study.We performed various experiments and compared the proposed model to base-line deep learning algorithms(CNNs and LSTMs)to demonstrate its performance.According to the research results,the proposed model outperforms the previous deep learning models in this domain with an accuracy of 99.17%and an F1-score of 98.96%.
基金supported by the“Postgraduate Research&Practice Innovation Program of Jiangsu Province”(No.JGKT22_C053)and“Qinglan Project”for Jiangsu Province.
文摘Smart education is the future and development direction of higher education.Taking the graduate course Crime and Police Theory as the research subject,the shortcomings of smart education,which include the lack of understanding of the concept of smart education,the limited content structure of smart education,the poor cognition of smart education among teachers and students,and inadequate hardware and technical support for smart education,are systematically analyzed.In view of these shortcomings,several strategies are proposed,including improving the smart education curriculum development plan and management level,ensuring the construction quality of smart education projects,and raising funds for smart education construction from various sources.
文摘A significant fraction of the world’s population is living in cities. With the rapid development ofinformation and computing technologies (ICT), cities may be made smarter by embedding ICT intotheir infrastructure. By smarter, we mean that the city operation will be more efficient, cost-effective,energy-saving, be more connected, more secure, and more environmentally friendly. As such, a smartcity is typically defined as a city that has a strong integration with ICT in all its components, includingits physical components, social components, and business components [1,2].
文摘This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate challenges, the research analyzed how smart city frameworks, aligned with climate neutrality objectives, leverage geospatial technologies for urban planning and climate action. The study included case studies from three leading European cities, extracting lessons and best practices in implementing Climate City Contracts across sectors like energy, transport, and waste management. These insights highlighted the essential role of EU and national authorities in providing technical, regulatory, and financial support. Additionally, the paper presented the application of a WEBGIS platform in Limassol Municipality, Cyprus, demonstrating citizen engagement and acceptance of the proposed geospatial framework. Concluding with recommendations for future research, the study contributed significant insights into the advancement of urban sustainability and the effectiveness of geospatial technologies in smart city initiatives for combating climate change.
文摘Smart materials,which exhibit shape memory behavior in response to external stimuli,have shown great potential for use in biomedical applications.In this study,an energetic composite was fabricated using a UV-assisted DIW 3D printing technique and a shape memory material(SMP)as the binder.This composite has the ability to reduce the impact of external factors and adjust gun propellant combustion behavior.The composition and 3D printing process were delineated,while the internal structure and shape memory performance of the composite material were studied.The energetic SMP composite exhibits an angle of reversal of 18 s at 70°,with a maximum elongation typically reaching up to 280% of the original length and a recovery length of approximately 105%during ten cycles.Additionally,thermal decomposition and combustion behavior were also demonstrated for the energetic SMP composite.
