AI-Driven Learning Management Systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

Adaptive Momentum-Backpropagation Algorithm for Flood Prediction and Management in the Internet of Things

Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world.Therefore,timely and accurate decision-making is essential for mitigating flood-related damages.The traditional flood prediction techniques often encounter challenges in accuracy,timeliness,complexity in handling dynamic flood patterns and leading to substandard flood management strategies.To address these challenges,there is a need for advanced machine learning models that can effectively analyze Internet of Things(IoT)-generated flood data and provide timely and accurate flood predictions.This paper proposes a novel approach-the Adaptive Momentum and Backpropagation(AM-BP)algorithm-for flood prediction and management in IoT networks.The AM-BP model combines the advantages of an adaptive momentum technique with the backpropagation algorithm to enhance flood prediction accuracy and efficiency.Real-world flood data is used for validation,demonstrating the superior performance of the AM-BP algorithm compared to traditional methods.In addition,multilayer high-end computing architecture(MLCA)is used to handle weather data such as rainfall,river water level,soil moisture,etc.The AM-BP’s real-time abilities enable proactive flood management,facilitating timely responses and effective disaster mitigation.Furthermore,the AM-BP algorithm can analyze large and complex datasets,integrating environmental and climatic factors for more accurate flood prediction.The evaluation result shows that the AM-BP algorithm outperforms traditional approaches with an accuracy rate of 96%,96.4%F1-Measure,97%Precision,and 95.9%Recall.The proposed AM-BP model presents a promising solution for flood prediction and management in IoT networks,contributing to more resilient and efficient flood control strategies,and ensuring the safety and well-being of communities at risk of flooding.

Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

Internet of Things(IoT)is a popular social network in which devices are virtually connected for communicating and sharing information.This is applied greatly in business enterprises and government sectors for delivering the services to their customers,clients and citizens.But,the interaction is success-ful only based on the trust that each device has on another.Thus trust is very much essential for a social network.As Internet of Things have access over sen-sitive information,it urges to many threats that lead data management to risk.This issue is addressed by trust management that help to take decision about trust-worthiness of requestor and provider before communication and sharing.Several trust-based systems are existing for different domain using Dynamic weight meth-od,Fuzzy classification,Bayes inference and very few Regression analysis for IoT.The proposed algorithm is based on Logistic Regression,which provide strong statistical background to trust prediction.To make our stand strong on regression support to trust,we have compared the performance with equivalent sound Bayes analysis using Beta distribution.The performance is studied in simu-lated IoT setup with Quality of Service(QoS)and Social parameters for the nodes.The proposed model performs better in terms of various metrics.An IoT connects heterogeneous devices such as tags and sensor devices for sharing of information and avail different application services.The most salient features of IoT system is to design it with scalability,extendibility,compatibility and resiliency against attack.The existing worksfinds a way to integrate direct and indirect trust to con-verge quickly and estimate the bias due to attacks in addition to the above features.

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Wireless Sensor Networks(WSNs)are a major element of Internet of Things(IoT)networks which offer seamless sensing and wireless connectivity.Disaster management in smart cities can be considered as a safety critical application.Therefore,it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN.Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks.This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management(EAMCR-RTDM).The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region.To achieve this,EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering(YSGF-C)technique to elect cluster heads(CHs)and organize clusters.In addition,enhanced cockroach swarm optimization(ECSO)based multihop routing(ECSO-MHR)approach was derived for optimal route selection.The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime.The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work.For examining the improved outcomes of the EAMCR-RTDM system,a wide range of simulations were performed and the extensive results are assessed in terms of different measures.The comparative outcomes highlighted the enhanced outcomes of the EAMCRRTDM algorithm over the existing approaches.

Marketing Management for Consumer Products in the Era of the Internet of Things

In the Internet of Things (IoT) consumer products like coffee machines and smoke detectors are connected with the Internet, which effectively expands the Internet to the physical world. Such products have the ability to collect and share data from the user’s environment and, thus, their broad emergence will affect well-established concepts presented in the extant marketing literature. In order to provide a distinct contribution, we focus on customer relationship management, product life cycle management, as well as business model development and discuss implications of the enhanced capabilities of IoT products in these fields. By means of an extensive analysis of current developments in theory and practice, we systematically deduce ten research propositions. The paper concludes with a synthesis of findings and an outlook to promising directions for further research in IoT-oriented marketing management.

A Training Mode for Innovative and Entrepreneurial Talents in Tourism Management in the Era of Internet Plus

The development of innovation and entrepreneurship education is gaining momentum.With the arrival of the Internet era,innovation and entrepreneurship have a better development platform.The tourist industry,as a “sunrise industry”,has great potential for development and has become a new economic growth point.In many areas,tourism has been identified as a pillar industry,a leading industry,and an industry receiving priority in developing.In the face of increasingly fierce competitive markets,it is particularly important to cultivate high-quality innovative and entrepreneurial talents in tourism management.For this purpose,this study analyzes the current situation of talent demand in China’s tourist industry and the problems existing in innovation and entrepreneurship education,draws on the successful experience of foreign colleges and universities in talent cultivation,and proposes and constructs a training mode for innovative and entrepreneurial talents in tourism management in the era of Internet Plus.

Improving the Patient Discharge Planning Process through Knowledge Management by Using the Internet of Things

The UK National Health Service (NHS) is faced with problems of managing patient discharge and preventing the problems that result from it such as frequent readmissions, delayed discharge, long waiting lists, bed blocking and other such consequences. The problem is exacerbated by the growth in size, complexity and the number of chronic diseases in the NHS. In addition, there is an increase in demand for high quality care, processes and planning. Effective Discharge Planning (DP) requires practitioners to have appropriate, patient personalised and updated knowledge in order to be able to make informed and holistic decisions about a patients’ discharge. This paper examines the role of Knowledge Management (KM) in both sharing knowledge and using tacit knowledge to create appropriate patient discharge pathways. The paper details the factors resulting in inadequate DP, and demonstrates the use of Internet of Things (IoT) and Machine2Machine (M2M) as candidate technologies and possible solutions which can help reduce the problem. The use of devices that a patient can take home and devices which are perused in the hospital generate information, which can serve useful when presented to the right person at the right time, thus harvesting knowledge. The knowledge when fed back can support practitioners in making holistic decisions with regards to a patients’ discharge.

Supply and Demand Oriented Energy Management in the Internet of Things

The Internet of Things (IoT) is emerging as an attractive paradigm involving physical perceptions, cyber interactions, social correlations and even cognitive thinking through a cyber-physical-social-thinking hyperspace. In this context, energy management with the purposes of energy saving and high efficiency is a challenging issue. In this work, a taxonomy model is established in reference to the IoT layers (i.e., sensor-actuator layer, network layer, and application layer), and IoT energy management is addressed from the perspectives of supply and demand to achieve green perception, communication, and computing. A smart home scenario is presented as a case study involving the main enabling technologies with supply-side, demand-side, and supply-demand balance considerations, and open issues in the field of IoT energy management are also discussed.

Excavation of the Internet of Things in Urban Areas Based on an Intelligent Transportation Management System

Transportation, as one of the most common aspects people use in their daily lives, has resulted in highly complex traffic in urban areas due to the large number of private vehicles. As some results of the traffic congestion, there is energy consumption, environmental pollution, unplanned accidents, and time is wasted due to congestion and traffic jams. With the aid of the Internet of Things (IoT), which is an excellent computerized technology solution for all field claims, Internet of Things (IoT) technology has recently provided an efficient and effective traffic management system, especially in transportation, due to the combined functions IoT can handle, there are management, monitoring, tracking, identifying, computing, and so on. This article provided a comprehensive overview of a variety of intelligent management systems that have been built using IoT to alleviate traffic congestion.

Cold Chain Logistics Equipment Management and Control Based on Internet of Things

The status and supporting policies of cold chain logistics equipment man- agement and control in China were described. The connotation of Internet of Things and its impact on cold chain logistics equipment management and control were ana- lyzed from external form to internal nature. Through introducing the value chain and relevant equipments of cold chain logistics, the correlation between the main technologies in Internet of Things and the common indices for cold chain logistics equipment management and control was analyzed in detail. The application values of Internet of Things technologies in cold chain logistics equipment management and control were illustrated, including the sample analysis on the application of radio-frequency identification （RFID）. After the establishment of BSC performance evaluation index system of cold chain logistics equipment management and control, the optimization measures and suggestions on cold chain logistics equipment management and control under Internet of Things were put forward.

United States Healthcare Data Breaches: Insights for NIST SP 800-66 Revision 2 from a Review of the NIST SP 800-66 Revision 1

Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publication base as an effective solution. The NIST Special Publication 800-66 Revision 1 was an essential standard in US healthcare, which was withdrawn in February 2024 and superseded by SP 800-66 Revision 2. This review investigates the academic papers concerning the application of the NIST SP 800-66 Revision 1 standard in the US healthcare literature. A systematic review method was used in this study to determine current knowledge gaps of the SP 800-66 Revision 1. Some limitations were employed in the search to enforce validity. A total of eleven articles were found eligible for the study. Consequently, this study suggests the necessity for additional academic papers pertaining to SP 800-66 Revision 2 in the US healthcare literature. In turn, it will enhance awareness of safeguarding electronic protected health information (ePHI), help to mitigate potential future risks, and eventually reduce breaches.

An Efficient SDFRM Security System for Blockchain Based Internet of Things

Blockchain has recently sparked interest in both the technological and businessfirms.The Internet of Things's(IoT)core principle emerged due to the connectivity of several new technologies,including wireless technology,the Inter-net,embedded automation systems,and micro-electromechanical devices.Manu-facturing environments and operations have been successfully converted by implementing recent advanced technology like Cloud Computing(CC),Cyber-Physical System(CSP),Information and Communication Technologies(ICT)and Enterprise Model,and other technological innovations into the fourth indus-trial revolution referred to as Industry 4.0.Data management is defined as the pro-cess of accumulation in order to make better business decisions,and process,secure and store information about a company.In the incipient model,there are interconnected contrivances and Machine-to-Machine(M2M)interactions,and transaction data are stored on the Blockchain.Security is a challenging aspect that must be punctiliously considered during the design and development phases of a CSP.In this research article,we proposed a Secure and Distributed Framework for Resource Management(SDFRM)in Industry 4.0 environments within a distribu-ted and collaborative Industry 4.0 system,the dynamic and trust-based Distributed Management Framework(DMF)of shared resource access.Such issues are focused by taking into account of the traditional characteristics of IoT/Industrial Internet of Things’(IIoT)-predicated environments,an SDFRM in Industry 4.0 environments within a distributed and collaborative Industry 4.0 system.Also,to ensure strong privacy over the procedures associated with Access Control(AC),a privacy-preserving method is proposed and integrated into the DMF.The proposed DMF,based on blockchain technology and peer-to-peer networks,allows dynamic access management and system governance without using third parties who could be attacked.We worked hard to design and implement the pro-posal to demonstrate its viability and evaluate its performance.Our proposal out-performs the Multichain Blockchain in terms of successful storage transactions with an achieved average throughput of 98.15%.

Internet of Things Supported Airport Boarding System and Evaluation with Fuzzy

The existing systems sustained with the investments made require more automation and digital transformation with the continuous advancement of tech-nology.The aviation industry is a sector that is open to more automation and digi-tal transformation,mainly because of the intense competition and the analysis of a large variety of data.The long duration of operations in current airline processes and some processflows cause customer dissatisfaction and cost increase.In this study,the boarding process,which is one of the operational processes of airline transportation and is open to improvement,was discussed.The classical boarding process has been redesigned using Internet of Things technology a model called Boarding 4.0 was created.With Boarding 4.0,it is aimed to design a process where passengers can take their time before boarding more efficiently.In the study,the sub-processes of the Boarding 4.0 model,other processes that the sub-processes interact with,their activities,and data exchange passenger move-ments during the activities are explained in detail.Compared to the classical boarding process and Boarding 4.0 with the fuzzy ahp technique,it has been shown that boarding 4.0 is more advantageous and passenger movement times can be reduced during boarding.As a result of the evaluation made with the fuzzy ahp,it was determined that boarding 4.0 is more advantageous than the classical boarding process.In addition,when the total time of the sub-activities in the board-ing process is calculated,boarding activities for a passenger take 50 min with the classic boarding process and 20 min with Boarding 4.0.Thus,when Boarding 4.0 is used,the passenger gains 30 min.Furthermore,when the calculation is made concerning the airport’s current capacity,two passengers are hosted with the clas-sical boarding process,whilefive passengers are hosted with Boarding 4.0.This acquisition is significant for airports in terms of efficient use of resources.

The Application of PDCA Circulation Method in Improving the Application of Internet + Smart First Aid in the Treatment of Preoperative Patients with Severe Neurological Diseases

Objective: To investigate the application and feasibility of PDCA circulation method in the treatment of patients with severe neurological diseases in Internet + smart first aid, with a view to promoting the sustainable construction of smart first aid. Methods: A total of 105 patients with severe neurological diseases in Zhuji people’s Hospital and cooperative units were selected, and 52 cases in the research group and 53 cases in the control group were divided according to the single and double number visiting time: In this paper, through reading the literature, the development of Internet + wisdom first aid treatment of patients with severe neurological diseases was investigated, and the common problems were analyzed and summarized, and the research group used the PDCA circulation method to sort out the existing problems, analyze the causes of the problems and improve them. The difference in treatment time between the two groups was compared, and the patient’s satisfaction was evaluated for the time of being transferred to the hospital emergency room by 120 ambulances, the time from emergency admission to surgery (Cath lab), and the satisfaction of the patient. Results: The time from emergency treatment to the operation room (catheter room) in the study group was significantly shortened, and patient satisfaction was significantly improved compared with that in the control group, with a statistically significant difference (P Conclusion: Through the application of PDCA circulation method in the Internet + smart emergency treatment of neurologically severe preoperative patients, the Internet + smart emergency mode can be continuously improved, the treatment process can be significantly optimized, the first aid time can be shortened, and the treatment efficiency of neurocritical ill patients can be improved. Therefore, it has been expected to improve the success rate of treatment and improve the success rate of neurological patients.

Cognitive Network Management in Internet of Things

The wide variety of smart embedded computing devices and their increasing number of applications in our daily life have created new op- portunities to acquire knowledge from the physical world anytime and anywhere, which is envisioned as the＂Internet of Things＂ （IoT）. Since a huge number of heterogeneous resources are brought in- to IoT, one of the main challenges is how to effi- ciently manage the increasing complexity of IoT in a scalable, flexNle, and autonomic way. Further- more, the emerging IoT applications will require collaborations among loosely coupled devices, which may reside in various locations of the Inter- net. In this paper, we propose a new IoT network management architecture based on cognitive net- work management technology and Service-Orien- ted Architecture to provide effective and efficient network management of loT.

Application of Internet of Things in Urban Waterlogging Prevention Management System

This paper aims to realize the extensive application of Internet of things technology in urban waterlogging prevention management system, and has analyzed the security requirement and security architecture of Internet of things technology, and discussed the demand of urban waterlogging prevention management system in combination with the key technology of Internet of things technology, to do the overall design and functional design well during designing of urban waterlogging prevention management system. Finally, the application process of the Internet of things technology in Chongqing waterlogging prevention management system is summarized. The application result shows that the flood control and drainage function of Chongqing is gradually improved with smooth drainage facilities;the inspection and maintenance management is gradually standardized;operation monitoring and early warning management is fully strengthened. There is visual management for emergency command and dispatch, and at the same time, the drainage pipe network assessment management can be conducted correctly.

Based on Laboratory Management of the Intemet of Things Technology Progress And Research

Laboratory information management based on the technology of Interact of things technology is the development trend of digital and information technology education in our country and the inevitable choice. Through the fiLnher study of the current situation of laboratory management in colleges and universities and the characteristics of the Internet of things technology, this paper introduces the concept of Interact of things tec^mology, history and current situation of the development. With the most representative IOT architecture and Ubiquitous ID IOT system as an example, analyzes the RFID technology, sensor network and detection technology, intelligent technology and characteristics of Nanometer technology. Analysis the technical foundation for the development of the campus Interact of things, and give the Internet of things technology in the application of the laboratory management technology.

A Dynamic Management Scheme for Internet of Things(IoT)Environments:Simulation and Performance Evaluation

In recent years,the Internet of Things(IoT)technology has been considered one of the most attractive fields for researchers due to its aspirations and implications for society and life as a whole.The IoT environment contains vast numbers of devices,equipment,and heterogeneous users who generate massive amounts of data.Furthermore,things’entry into and exit fromIoT systems occur dynamically,changing the topology and content of IoT networks very quickly.Therefore,managing IoT environments is among the most pressing challenges.This paper proposes an adaptive and dynamic scheme for managing IoT environments is proposed.This management scheme depends on the use of previous management methodologies,considering two main factors.The first factor is network status,which is determined in real-time.The second factor is a management method’s suitability according to its desired administration.To test the proposed management scheme,a simulation environment is created using NS3.The metrics used to measure the management scheme performance are bandwidth consumption,energy consumption,packet loss,throughput,delay,usage rate of individualmanagement techniques,and transformation.The simulation results prove that the proposed management scheme outperformed the individual 6LowPANSNMP,CoAP,and LWM2M management schemes.

Jointly optimizing user clustering,power management,and wireless channel allocation for NOMA-based Internet of Things

In order to accommodate the large number of Internet of Things(IoT)connections in mobile networks,Non-Orthogonal Multiple Access(NOMA)has been applied as the resource sharing mechanism in mobile access networks to improve the spectrum efficiency.The NOMA-based resource management for uplink communications comprises two problems,i.e.,user clustering and power&wireless channel allocation.User clustering refers to assigning users in terms of IoT devices to different clusters(where users in the same cluster are sharing the wireless channels to upload their data),and power&wireless channel allocation is to optimize the transmission power of the users and the number of wireless channels allocated to the users in a cluster.The two problems are coupled together,thus making it difficult to solve the NOMA-based resource management problem.In this paper,we propose a QoS-aWarE resourcE managemenT(SWEET)for NOMA algorithm to jointly optimize the user clustering,power management,and wireless channel allocation such that the number of wireless channels is minimized and the data rate requirements of the users can be satisfied.The performance of SWEET is validated via extensive simulations.

Internet of Things Enabled Intelligent Energy Management and Control System for Heavy Equipment Industrial Park and Fuzzy Assessment of Its Schemes

In order to solve the problems of poor informationflow,low energy utilization rate and energy consumption data reuse in the heavy equipment industrial park,the Internet of Things(IoT)technology is applied to construct the intelligent energy management and control system(IEMCS).The application architecture and function module planning are analyzed and designed.Furthermore,the IEMCS scheme is not unique due to the fuzziness of customer demand and the understanding deviation of designer to customer demand in the design stage.Scheme assessment is of great significance for the normal subsequent implementation of the system.A fuzzy assessment method for IEMCS scheme alternatives is proposed to achieve scheme selection.Fuzzy group decision using triangular fuzzy number to express the vague assessment of experts is adopted to determine the index value.TOPSIS is modified by replacing Euclidean distance with contact vector distance in IEMCS scheme alternative assessment.An experiment with eight IEMCS scheme alternatives in a heavy equipment industrial park is given for the validation.The experiment result shows that eight IEMCS scheme alternatives can be assessed.Through the comparisons with other methods,the reliability of the results obtained by the proposed method is discussed.