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                <text>Effective Marketing and Consumer Behavior Tactics for High-End Products;pp.1-30</text>
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                <text>Shekhawat D.D.S., Christ University, India; Kaur J., Christ University, India</text>
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                <text>The internet's availability profoundly impacted many aspects of modern life, including business and communication. One of its most notable effects is the development of internet addiction, which has drawn much attention because of its behavioural and psychological ramifications. This addiction can have detrimental effects on one's social, professional, and personal life. It frequently presents as excessive and uncontrollable using the internet. One important area where obsessive online shopping behaviour is one where internet addiction is becoming more evident. This chapter explores the relationship between obsessive online shopping and internet addiction, emphasizing how artificial intelligence is transforming consumer decision-making. This chapter aims to investigate how compulsive purchase behaviour can be made worse by internet addiction and the degree to which AI-driven algorithms play a role in this phenomenon. Several mitigation measures can be used to alleviate the negative effects of obsessive buying behaviour led by AI.  2025, IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Increasing mental health issues in India demands for a strong intervention to curb the rise. According to the World Health Organization, roughly around 21 Indians out of 100,000 die by suicide every year. The burden on mental health domain increases due to the existing system as most of the existing services follow a traditional approach and are most sought after but lack reachability and ease of access. This study recognises the need for programmes that help in reachability and ease of access while simultaneously maintaining anonymity, therefore, analyses the impact of chat-based therapy provided online through the platform. The paper analyses the difference in subjective unit of well-being (SUW) pre and post chat-based sessions among 2624 college students and 805 corporate employees. The Wilcoxon signed rank test between pre and post intervention indicates significant results with the p &amp;lt; 0.001 (Z = -44.100a) suggesting and increase in SUW scores post intervention. Further, the Kruskal-Wallis test revealed that the gender of the clients has an association with the SUW scores (p &amp;lt; 0.05). It was also found that the duration of the sessions had a positive relation with the impact scores (p &amp;lt; 0.001).   The Author(s), 2025.</text>
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                <text>The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making. The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book.  2022 John Wiley &amp;amp; Sons Ltd. All rights reserved.</text>
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                <text>Internet of Healthcare Things: Machine Learning for Security and Privacy, pp. 1-304.</text>
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                <text>This study examines the use of internet of things (IoT) technology in the field of education, concentrating on its uses, advantages, and difficulties. The current educational system frequently fails to provide individualized learning opportunities since it is characterized by traditional classroom settings and teacher-centered learning. But the emergence of IoT and its companion technologies, including big data, artificial intelligence, and network communication, offers fresh chances to transform education. The IoT architecture in the education sector is covered in the opening section of the paper, with an emphasis on the function of IoT devices in building a networked environment. These tools, such as smart HVAC (heating, ventilation, and air conditioning) systems, make it easier to gather and analyze enormous volumes of data. Institutions of higher learning can get important insights and create individualized learning strategies, thanks to the integration of big data and artificial intelligence. The report also examines a variety of IoT uses in education. It emphasizes the importance of IoT in remote learning, which has become more popular recently. It also demonstrates how the internet of things has influenced the development of smart campuses with interactive whiteboards and other IoT gadgets. The importance of personalized learning in contemporary education is also discussed, with IoT acting as a catalyst for experiences that are specifically suited for students. The study also looks at how IoT might benefit students with disabilities and improve staff and student health monitoring. The use of augmented reality and virtual reality tools in teaching is also investigated. The study explores Edutech-based IoT solutions, concentrating on their function in the processes of teaching, learning, and evaluation. It examines management and government initiatives on both a national and international scale, including those from Ireland's Future Schools, Jharkhand's DigiSAT, and Assam's online job advisory portal. The Kajeet Smart Bus, C-Pen, and Ipevo VZ-X Wireless Document Camera are just a few examples of IoT deployments in education that are highlighted in the study. These instances highlight the concrete contribution of IoT to improving educational practices. IoT tools are also examined in relation to several educational contexts, such as primary, secondary, and higher secondary education. The study also examines the distinct needs of special schools and universities and emphasizes the importance of IoT in STEAM teaching at the university level. The chapter discusses the advantages, disadvantages, possibilities, and difficulties that players in the education sector would have when implementing IoT. It highlights how crucial it is to take advantage of the capabilities of big data, artificial intelligence, and network communication to enhance teaching and learning results. The article also highlights problems with the research and suggests potential fixes, noting areas that could use more investigation. This chapter's conclusion highlights the IoT's disruptive potential in the field of education. Education can be revolutionized by integrating IoT devices, utilizing big data and artificial intelligence, and utilizing network communication. It makes it possible to create individualized, engaging, and data-driven learning experiences that get students ready for the digital era.  2024 selection and editorial matter, Alex Khang, Vugar Abdullayev, Vladimir Hahanov and Vrushank Shah; individual chapters, the contributors.</text>
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                <text>Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy, pp. 251-274.</text>
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                <text>Rajamohan K., School of Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Rangasamy S., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Manoj C. N., School of Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Mary L., School of Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Sabu R., School of Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Jose S.S., School of Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India</text>
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                <text>The Internet of Things (IoT) enables Internet-connected devices to transmit data to private blockchain networks, allowing for the creation of tamper-resistant documents with shareable exchanges. IoT blockchain technology enables you to communicate and connect IoT data with key stakeholders, while avoiding the need for extensive management and control. Each transfer can be checked to ensure there are no disagreements and to build trust in the network. Blockchain technology protects data from being changed, restricts access to Internet-connected devices, and allows vulnerable IoT devices to be shut down. Blockchain encryption eliminates the possibility of someone overwriting existing data records. In addition, storing IoT data on the blockchain adds an extra layer of security, preventing malicious attackers from accessing the system. The many blockchain IoT firms provide significant value in revolutionizing company operations and daily routines. IoT blockchain firms demonstrate the possibility of blockchain and IoT integration. For instance, Helium is a successful blockchain IoT company specializing in securing Internet connections. This chapter presents the vital role of the Internet of Things and blockchain in the healthcare domain. The integration of blockchain technology in the healthcare industry has given us a chance to solve some problems with IoT networks. In recent years, the need for blockchain-enabled IoT transactions has become an essential technology that will change how users share data. A scenario has been developed to enhance this study to analyse the integration, need, and obstacles associated with blockchain-enabled IoT transactions in the healthcare area. As a result, there is also an IoT model designed using devices for hospitals that take into account all of these people and their needs and the office space where they work.  The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024.</text>
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                <text>Arulkumar N., Department of Computer Science, Christ University, Bangalore, India; Manimaran A., Department of Mathematics, School of Advanced Studies, VIT-AP University, Andhra Pradesh, Amaravati, India; Chandramohan D., Department of Computer Science and Engineering, Thapar Institute of Engineering &amp;amp; Technology, Punjab, Patiala, India; Goundar S., School of Science, Engineering, and Technology, RMIT University, Hanoi, Viet Nam</text>
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                <text>The rapid advancement of cloud technology has resulted in the emergence of many cloud service providers. Microsoft Azure is one among them to provide a flexible cloud computing platform that can scale business to exceptional heights. It offers extensive cloud services and is compatible with a wide range of developer tools, databases, and operating systems. In this paper, a detailed analysis of Microsoft Azure in the cloud computing era is performed. For this reason, the three significant Azure services, namely, the Azure AI (Artificial Intelligence) and Machine Learning (ML) Service, Azure Analytics Service and Internet of Things (Io T) are investigated. The paper briefs on the Azure Cognitive Search and Face Service under AI and ML service and explores this service's architecture and security measures. The proposed study also surveys the Data Lake and Data factory Services under Azure Analytics Service. Subsequently, an overview of Azure Io Tservice, mainly Io THub and Io TCentral, is discussed. Along with Microsoft Azure, other providers in the market are Google Compute Engine and Amazon Web Service. The paper compares and contrasts each cloud service provider based on their computing capability.  2022 IEEE.</text>
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                <text>Sreyes K., Tata Consultancy Services, Bangalore, India; Anushka Xavier K., Christ University, Bangalore, India; Davis D., Accenture Solutions Pvt Ltd, Bangalore, India; Jayapandian N., Department of CSE, Christ University, India</text>
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                <text>Sharma B., Christ University, Bangaluru, India; Aggarwal M., Uttaranchal University, Dehradun, India; Bala R., Jan Nayak Chaudhary Devi Lal Vidyapith, Sirsa, India; Dhiman R., Uttaranchal University, Dehradun, India; Badoni M., Uttaranchal University, Dehradun, India</text>
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                <text>Technological advancements have changed the way people think about how they operate. Various new approaches to work and processes have been identified after adopting various technological changes. This paper discusses various changes adopted by the finance and banking sector with the help of various successful changes in the banking industry. The banking sector, where human-to-human interaction was the core of operating technology, has made it machine-to-machine. Various significant and recent changes have been discussed, followed by some challenges faced by this industry even after successfully adopting technology.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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                <text>Internet of Things and Machine Learning based Intelligent Irrigation System for Agriculture</text>
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                <text>Irrigated agriculture methods need a significant volume of water, and causes water waste. It is critically necessary to install an efficient watering system and lessen the volume of water wasted on this tiresome chore. It is a huge benefit of the computer vision (ML) - the Internet of Everything (Ot) era to construct expert machines that carry out this work successfully with little human endeavour. This work suggests an Embedded device Fluid ounces suggestion method for efficient water use with little farm involvement. In the agricultural field, IoT sensors are set up to capture important atmospheric and surface data. The obtained information is sent to and stored on a cloud-based server, where machine learning techniques are used to evaluate the information and recommend treatment to the farmers. This recommender system has an internal development process that makes the solution resilient and flexible. The test demonstrates that the suggested method operates admirably on the agricultural dataset from the National Institutes of Technology (Kit) Bhubaneswar as well as the information that we obtained.   2022 IEEE.</text>
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                <text>Alanya-Arango J.; Alanya-Beltran J.; Ravichandran S.K.; Singh B.; Sasi A.; Gangodkar D.</text>
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                <text>Proceedings of 5th International Conference on Contemporary Computing and Informatics, IC3I 2022, pp. 67-72.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Alanya-Arango J., Ministerio de Desarrollo Agrarioy Riego Del Per(MIDAGRI), Peru; Alanya-Beltran J., Universidad Tecnolica Del Per Department of Electronic, Peru; Ravichandran S.K., Christ University, Department of Computer Science and Engineering, Karnataka, Bangalore, India; Singh B., I.K.Gujral Punjab Technical University, Punjab, Kapurthala, India; Sasi A., Presidency University, Itgalpur Rajanakunte, Department of CSE, Bangalore, Karnataka, Yelahanka, India; Gangodkar D., Graphic Era Deemed to Be University, Department of CSE, Uttarakhand, Dehradun, India</text>
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                <text>Internet of Things Based Autonomous Borewell Management System</text>
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                <text>Bore-well centrifugal pump; Dry run; Energy conversation; Internet of things; IoT controller</text>
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                <text>Water is a basic need for all living beings. At present, due to a large population, water level is getting depleted at an alarming rate particularly in urban region. During summer season, there is no continuous flow of water or availability of water. In electrical contingency situations, bore-wells are prone to damages. The utilization of power at dry run condition affects the economy of the consumers. Despite having no water in the bore-well, if the motor runs, the motor windings may burdened and gives rise to unnecessary power loss. In the present scenario, conservation of energy is a major concern. The conservation of energy as a whole will take place when an individual take an active part by using autonomous and effective methodologies or controllers. The issue is solved by managing the borewell using Internet of Things (IoT) as a platform to automate and manage. The IoT based borewell management system is designed to provision scheduling, manual operation, avoidance of borewell motor running at dry run condition and also nullifies energy loss. The automated borewell operations can be executed from a remote control and measurement unit by the measurement of electrical parameters and analytics. The proposed system minimizes man power, saves time and conserve energy loss. The paper presents operating the conventional borewell by deployment of smart controller which handles the information and communication technology at client and base units.  Springer Nature Switzerland AG 2020.</text>
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                <text>Venkataswamy R.; Paul R.; Jogy J.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-80, pp. 229-243.</text>
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                <text>Venkataswamy R., Department of Electrical &amp;amp; Electronics Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India; Paul R., Department of Electrical &amp;amp; Electronics Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India; Jogy J., Department of Electrical &amp;amp; Electronics Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India</text>
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                <text>Internet of things based metaheuristic reliability centered maintenance of distribution transformers</text>
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                <text>Distributed generation; Machine learning; Optimization; Reliability centered maintenance</text>
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                <text>The transformer is a vital component of the power system. Continuous stress on the transformer due to overload, transient and faults will lead to physical damages. The isolation of the transformer causes significant revenue loss and inconvenience to the consumers at the distribution level. This invites the need to achieve a reliable power supply to the consumers and to perform maintenance activity appropriately. Optimized and predictive maintenance strategies are evolved to improve power availability for consumers. The model considers dispersive generation at the customer end, namely solar photovoltaics standalone system, diesel generation, and vehicle to load capabilities. Incipient or critical status of transformers' functional parameters are observed through the transformer terminal unit and sent to the internet of things platform. The remote processing unit acquires the information from all the distribution transformer and generates the optimized and reliability-centered maintenance schedule. In the proposed work, new reliability indices concerning the consumer dispersive generation are defined. The maximization of the reliability problem is solved using the coconut tree optimization technique. The highest reliability of power supply to the consumer and maintenance schedule are obtained. Economic facet of the estimated maintenance schedule exhibit benefit for both utility and consumer as it encapsulate time of use tariff. The heuristic dataset is used to synthesize the trained model by the machine learning algorithm and future maintenance schedule is predicted. The comparative study is made for the outcome of time-based optimized and predicted maintenance schedules against reliability.  2020 Institute of Physics Publishing. All rights reserved.</text>
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                <text>Venkataswamy R.; Uma Rao K.; Meena P.</text>
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                <text>IOP Conference Series: Earth and Environmental Science, Vol-463, No. 1</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>Venkataswamy R., Department of Electrical and Electronics Engineering, Christ (Deemed to be University), Bangalore, India; Uma Rao K., Department of Electrical and Electronics Engineering, RV College of Engineering, Bangalore, India; Meena P., Department of Electrical and Electronics Engineering, BMS College of Engineering, Bangalore, India</text>
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                <text>Internet of Things Enabled Device Fault Prediction System Using Machine Learning</text>
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                <text>Cloud computing; Home appliance; Internet of Things; Machine learning; Naive Bayes; Sensors</text>
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                <text>Internet of Things (IOT) started as a niche market for hobbyists and has evolved into a huge industry. This IoT is convergence of manifold technologies, real-time analytics, machine learning and Artificial Intelligence. It has given birth to many consumer needs like home automation, prior device fault detection, health appliances and remote monitoring applications. Programmed recognition and determination of different kinds of machine disappointment is a fascinating process in modern applications. Different sorts of sensors are utilized to screen flaws that is discovers vibration sensors, sound sensors, warm sensors, infrared cameras, light cameras, and other multispectral sensors. The modern devices are becoming ubiquitous and pervasive in day to day life. This device is need for reliable and predicate algorithms. This article is primarily emphases on the prediction of faults in real life appliances making our day to day life easier. Here, the database of the device includes previous faults which are restored in online by using cloud computing technology. This will help in the prediction of the faults in the devices that are to be ameliorated. It additionally utilizes Nae Bayes calculation for shortcoming location in the gadgets. The proposed model of this article is involves the monitoring of each and every home appliance through internet and thereby detect faults without much of human intervention.  Springer Nature Switzerland AG 2020.</text>
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                <text>Bhavana K.; Nekkanti V.; Jayapandian N.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-98, pp. 920-927.</text>
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                <text>ISSN: 23673370</text>
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                <text>Bhavana K., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Kengeri Campus, Bangalore, India; Nekkanti V., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Kengeri Campus, Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Kengeri Campus, Bangalore, India</text>
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              <elementText elementTextId="270906">
                <text>Chelekkodan, Danish Muneer; Jayapandian, N.; Abhinav, S.; Shyjan, Aaron</text>
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                <text>Internet of Things Enabled Smart Hand Gesture Virtual Mouse System</text>
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                <text>2025 IEEE 14th International Conference on Communication Systems and Network Technologies, CSNT 2025;pp.1165-1170</text>
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                <text>&lt;a href="https://doi.org/10.1109/CSNT64827.2025.10968594" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/CSNT64827.2025.10968594&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105004553881?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105004553881?origin=resultslist&lt;/a&gt;</text>
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                <text>Chelekkodan D.M., Department of Computer Science and Engineering, Christ University, Kengeri Campus, Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, Christ University, Kengeri Campus, Bangalore, India; Abhinav S., Department of Computer Science and Engineering, Christ University, Kengeri Campus, Bangalore, India; Shyjan A., Department of Computer Science and Engineering, Christ University, Kengeri Campus, Bangalore, India</text>
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                <text>This research is aim to focus on IoT based hand gesture model. Mouse is one of the most important input devices of a computer. It works as a pointing device and allows the user to move the pointer as needed by the user. In the early days, a wired mechanical mouse was used for this purpose. In mechanical mouse a ball is fixed underneath the mouse, which rotates as the user moves the mouse. This movement of the ball is used to move the mouse pointer on the screen. Now mostly we use optical mouse which can be wired or wireless. An optical mouse has a high-power laser below it, which takes more than thousand pictures of the surface below the mouse. An image comparator compares the images and sends the signal to move the mouse pointer as the texture of the image changes. Both the types of mouse works based on old technology. As technology leaps to greater heights, the need for simplicity also increases. With the invention of different kind of sensors, microcontrollers and other electronics, we can eliminate the mouse as an input device and instead use our hands to do the work of a mouse. This prototype is an embedded system which runs with the help of an arduino microcontroller. Flex sensors are used to capture the hand gestures. The proposed IoT based hand gesture model is providing high accuracy rate compare to the regular model. The proposed model is analyzed with accuracy level, the average accuracy level of proposed model is more than 90%.  2025 IEEE.</text>
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                <text>Arduino Controller; Computer Vision; Flex Sensors; Hand Gesture; Internet of Things; Virtual Mouse</text>
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