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                <text>When making job offers, it is usual practice for businesses to check applicants academic credentials. The organization that issued the certificate must authenticate it for the employer to ensure that it is genuine. Because of the lengthy process involved in certificate verification, the selection process takes longer overall while establishing the legitimacy of a certificate. To address this issue, blockchain provides a verified distributed ledger along with a cryptography mechanism to thwart academic credential counterfeiting. The Blockchain also provides a standardized platform for document access, storage, and verification that takes the least amount of time. The review of the methodologies and performance of the same has been covered in the paper.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.</text>
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                <text>Sabu I.R.; Saju S.; Mary Anita E.A.; Lapin V.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-1207 LNNS, pp. 231-239.</text>
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                <text>Sabu I.R., Christ University, Bangalore, India; Saju S., Christ University, Bangalore, India; Mary Anita E.A., Christ University, Bangalore, India; Lapin V., North-Caucasus Federal University, Stavropol, Russian Federation</text>
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                <text>A smart city is designed using acceptable internet of things (IoT) technologies that solve urban life problems and provide quality of life to the residents. IoT refers to a network of physical devices that are capable of gathering and sharing data and expediting numerous functions without human assistance. IoT supports smart home builders and managers by providing an efficient ecosystem in terms of less operating cost and improvising residence services. In recent days, the initiative of smart homes/buildings/ cities is increasing gradually around the globe. The inclined population in an urban area also expects well-managed automated services in their everyday life.  2023, IGI Global.</text>
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                <text>Rajamohan K.; Rangasamy S.; Abreo A.; Upadhyay R.; Sabu R.</text>
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                <text>Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries, pp. 316-335.</text>
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                <text>Rajamohan K., CHRIST University (Deemed), India; Rangasamy S., CHRIST University (Deemed), India; Abreo A., CHRIST University (Deemed), India; Upadhyay R., CHRIST University (Deemed), India; Sabu R., CHRIST University (Deemed), India</text>
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                <text>Smart City Governance and Citizen Engagement</text>
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                <text>The smart city idea has been put into practice in numerous nations as a response to urban issues. With the ultimate goal of improving quality of life and well-being, smart cities are more and more eager to engage in fruitful dialogue with their residents, better understand their demands, and develop digital platforms for inciting collaborative initiatives between authorities and people. Prior researches have noted challenges with execution and the importance of smart citizens as key components of a smart city. Using an internet-based social platform, this project intends to learn more about how smart cities are implemented and how citizens are involved. Smart city development should be modified to account for local conditions. Local expertise, transformative leadership, sustainability, and political content are the key success criteria for the implementation. Through an online social network, city residents have been participating in the implementation of the smart city. In order to make sure that city citizens are motivated to address the citys challenges, a sort of incentive structure remains necessary. Previous research efforts were conducted in an effort to measure the projects effectiveness by achieving benefits. The people of that country are the end users of public infrastructure projects. Nevertheless, communities all throughout the world have struggled to achieve genuine citizen engagement. This component of citizen engagement has been highlighted as a crucial goal to be accomplished. This chapter examines the role of AI in citizen engagement and participation in the smart city implementation. The chapter also intends to analyse the relevant research works to examine the trends in smart city governance and AI. This study will provide also insights into emerging issues and challenges.  2025 selection and editorial matter Pawan Whig, Pavika Sharma, Nagender Aneja, Ahmed A. Elngar and Nuno Silva; individual chapters, the contributors.</text>
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                <text>Jaiwant S.V.; Dheepa T.; Haridasan A.</text>
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                <text>Artificial Intelligence and Machine Learning for Sustainable Development: Innovations, Challenges, and Applications, pp. 112-124.</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003497189-9" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003497189-9&lt;/a&gt;
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                <text>Jaiwant S.V., CHRIST (Deemed to be University), Bengaluru, India; Dheepa T., CHRIST (Deemed to be University), Bengaluru, India; Haridasan A., CHRIST (Deemed to be University), Bengaluru, India</text>
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                <text>Smart city initiatives and disaster resilience of cities through spatial planning in Pune city, India</text>
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                <text>Disaster Risk Reduction; Smart Cities; Spatial Planning; Urban Resilience; Urban Risks</text>
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                <text>Cities are attracting populations at alarming rate. Cities provide the need of populations in every way from livelihoods to livability. In doing so it is exhausting its resources resulting in increasing threats of risk. An initiative like Smart City Mission is aiming to enhance the capacities of the cities to increase livability and quality of life for its population and decrease threats of risk. This study examines the impact of smart city initiatives on resilience to earthquakes and floods through a spatial planning perspective for the city of Pune in State of Maharashtra through series of structured interviews with key stakeholders. The findings suggest that smart city initiative is still in its primary stage and requires assimilation with the development strategy to contribute to the resilience of the city. The study further proposes the need to integrate the smart city initiative with all the current and future developmental projects.  2023, World Research Association. All rights reserved.</text>
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                <text>Sujata K.; Mani S.K.; Guru B.</text>
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                <text>Disaster Advances, Vol-16, No. 5, pp. 29-37.</text>
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                <text>Sujata K., School of Disaster Studies, Tata Institute of Social Sciences, Mumbai, India; Mani S.K., Department of Civil Engineering, CHRIST (Deemed to be University), Bangalore, India; Guru B., Department of Geology, School of Earth Sciences, Central University of Tamil Nadu, Thiruvarur, India</text>
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                <text>The main food in India is Rice. Be it the breakfast, lunch, dinner or some snacks, for everything the most preferred ingredient in Rice. In compared with north Indians, Rice is most used by South Indians. Today's youngsters from villages are migrating to cities in search of jobs after their education. Even farmers have stopped their cultivation and are working towards different business. So, the yield of rice is reduced in India. One more reason for this is because of the poor monsoon. Government is finding it challenging to supply rice to all its consumers. It is expected, because for Rice the consumers are more compared to its production. Government has decided to import the rice from the neighboring countries. This neighboring country knows the demand of rice in India and started supplying contaminated rice. Currently our Government has no technology to check the quality of the rice which they are getting imported, so the result is plastic rice arrived in India. Indirectly, India is in huge loss in terms of money and damages for its citizens health. So, there is a need of automated system to detect the quality of the rice that are imported. Another use of such automated system is that most of the people are not able to identify the type of the rice and the quality of the rice. This system helps even common man a facility in identifying the type and quality of rice.  2017 IEEE.</text>
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                <text>Manohar M., Dept. of CSE, Faculty O/Engineering, Christ University, Bangalore, India; Chatrapathy K., Dept. of ISE, School O/Engineering and Technology, Jain University, Bangalore, India; Sowmya M.S., Dept. of ISE, School O/Engineering and Technology, Jain University, Bangalore, India</text>
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                <text>Smart Edge Computing for 5g/6g Satellite IOT for Reducing Inter Transmission Delay</text>
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                <text>5G; cloud computing; DCNN; edge computing; IoT; satellite software model; SDN/NFV</text>
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                <text>5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via satellite to IoT cellular devices. Technological motivation tends to increase the satellites day by day for supporting most of global applications. These applications highly relay on satellite data for processing users request and giving appropriate outcome to the users. World grows very fastly with new technologies which makes demand for fastest data communication. Handling the satellite IoT data is worthiest research problem and it must be paid with more attention. At present inter satellite communication face high delay with lower data utilization rate. The effective utilization of data generated by satellite IoT is processed using our proposed intelligent model called smart edge computing (SEC-5G) for 5G. The SEC-5G embeds with satellite for reducing the data transfer limitation and delay in inter satellite communication. In this research we highly concentrate on satellite IoT data and its problem. Our proposed system reduces the limitation in inter satellite data communication rate which makes higher delay in data processing and utilization. In this article, smart edge computing is designed for satellite IoT using SDN/NFV and deep convolutional neural network (DCNN) with logical ring construction. The task uses SDN/NFV model to choose edge node, cloud node in the smart edge computing. Based on training data, DCNN works on SEC-5G software model. Smart architecture helps to increase the performance, scalability, reliability of satellite edge computing model. This architecture works with machine learning model and helps to improve the future satellite speed on data processing. The performance of the proposed is compared with existing Ground 5G. Evaluated outcome shows proposed embedded satellite outperforms in data communication.  2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>Mohammed A.S.; Venkatachalam K.; HubovskS.; TrojovskP.; Prabu P.</text>
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                <text>Mobile Networks and Applications, Vol-27, No. 3, pp. 1050-1059.</text>
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                <text>&lt;a href="https://doi.org/10.1007/s11036-021-01860-z" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s11036-021-01860-z&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124203420&amp;amp;doi=10.1007%2Fs11036-021-01860-z&amp;amp;partnerID=40&amp;amp;md5=fe9952f3b6f4c120d10679462c54f0af" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124203420&amp;amp;doi=10.1007%2fs11036-021-01860-z&amp;amp;partnerID=40&amp;amp;md5=fe9952f3b6f4c120d10679462c54f0af&lt;/a&gt;</text>
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              <elementText elementTextId="107207">
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              <elementText elementTextId="107208">
                <text>ISSN: 1383469X</text>
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                <text>Mohammed A.S., Department of Computer Engineering, College of Engineering and Computer Sceince, Lebanese French University, KR, Erbil, Iraq, Department of Software and Informatics Engineering, Salahaddin University, KR, Erbil, Iraq; Venkatachalam K., Department of Applied Cybernetics, Faculty of Science, University of Hradec Krov Hradec Krov 50003, Czech Republic; HubovskS., Department of Applied Cybernetics, Faculty of Science, University of Hradec Krov Hradec Krov 50003, Czech Republic; TrojovskP., Department of Mathematics, Faculty of Science, University of Hradec Krov Hradec Krov 50003, Czech Republic; Prabu P., Department of Computer Sceince, CHRIST (Deemed to be University), Bangalore, 560074, India</text>
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                <text>Smart Embedded Framework of Real-Time Pollution Monitoring and Alert System</text>
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                <text>Arduino IDE; IoT; pollution; sensors</text>
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                <text>The sustainability and progress of humanity depend on a clean, pollution-free environment, which is essential for good health and hygiene. Huge indoor auditorium does not have proper ventilation for air flow so when the auditorium is crowded the carbon di-oxide is emitted and it stays there for many days this may be a chance to spreading of COVID-19 and other infectious diseases. Without proper ventilation virus may present in the indoor auditorium. In the proposed system, emissions are detected by air, noise, and dust sensors. If the signal limit is exceeded, a warning is given to the authorities via an Android application and WiFi, and data is stored in cloud networks. In this active system, CO2 sensor, noise sensor, dust sensor, Microcontroller and an exhaust fan are used. This ESP-32 based system is developed in Arduino Integrated Development Environment (Aurdino IDE) to monitor air, dust and noise pollution in an indoor auditorium to prevent unwanted health problems related to noise and dust. More importantly, using IoT Android Application is developed in Embedded C, which continuously records the variation in levels of 3 parameters mentioned above in cloud and display in Android screen. Also, it sends an alert message to the users if the level of parameters exceeds the minimum and maximum threshold values with more accuracy and sensitivity. Accuracy and sensitivity of this products are noted which is very high for various input values.   2022 IEEE.</text>
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                <text>Joy S.; Babychithra R.; Anju M.I.; Neethu P.S.</text>
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                <text>2022 International Conference on Futuristic Technologies, INCOFT 2022</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/INCOFT55651.2022.10094405" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/INCOFT55651.2022.10094405&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154042829&amp;amp;doi=10.1109%2FINCOFT55651.2022.10094405&amp;amp;partnerID=40&amp;amp;md5=323e76a995605151e6f93d7fe32704bc" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154042829&amp;amp;doi=10.1109%2fINCOFT55651.2022.10094405&amp;amp;partnerID=40&amp;amp;md5=323e76a995605151e6f93d7fe32704bc&lt;/a&gt;</text>
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            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="176958">
                <text>Restricted Access</text>
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            </elementTextContainer>
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                <text>ISBN: 978-166545046-1</text>
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                <text>Joy S., New Horizon College of Engineering, Dept. of Electronics and Communication, Bangalore, India; Babychithra R., New Horizon College of Engineering, Dept. of Electronics and Communication, Bangalore, India; Anju M.I., New Prince Shri Bhavani College of Engineering and Technology, Dept. of Electronics and Communication Engineering, Chennai, India; Neethu P.S., Dept. of Electronics and Communication Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Bangalore, India</text>
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                <text>Human-Computer Interaction (HCI) in an intelligent way, which aims at creating scalable and flexible solutions. Big tech firms and businesses believe in the success of HCI as it allows them to profit from on-demand technology and infrastructure for information-centric applications without having to use public clouds. Because of its capacity to imitate human coding abilities, facial expression recognition and software-based facial expression identification systems are crucial. This paper proposes a system of recognizing the emotional condition of humans, given a facial expression, and conveys two methods of predicting the age and gender factors from human faces. This research also aims in understanding the influences posed by gender and age of humans on their facial expressions. The model can currently detect 7 emotions based on the facial data of a person - (Anger, Disgust, Happy, Fear, Sad, Surprise, and Neutral state). The proposed system is divided into three segments: a.) Gender Detection b.) Age Detection c.) Emotion Recognition. The initial model is created using 2 algorithms - KNN, and SVM. We have also utilized the architectures of some of the deep learning models such as CNN and VGG - 16 pre-trained models (Transfer Learning). The evaluation metrics show the model performance regarding the accuracy of the Recognition system. Future enhancements of this work can include the deployment of the DL and ML model onto an android or a wearable device such as a smartphone or a watch for a real-time use case.  2022 Elsevier B.V.. All rights reserved.</text>
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                <text>Teja Chavali S., Department of Computer Science and Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, Bengaluru, 56003, India; Tej Kandavalli C., Department of Computer Science and Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, Bengaluru, 56003, India; Sugash T.M., Department of Mathematics, CHRIST, Deemed to Be University, Bengaluru, 560029, India; Subramani R., Department of Mathematics, CHRIST, Deemed to Be University, Bengaluru, 560029, India</text>
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                <text>SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems. The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable.  2021 Scrivener Publishing LLC. All rights reserved.</text>
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                <text>Islam S.K.H., Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, West Bengal, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka, India</text>
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                <text>With the increasing age of an individual, the chances of being prone to chronic diseases like diabetes or non-curable diseases like Alzheimer's Syndrome or Parkinson's Syndrome increases. Due to the health issues, elderly must be accompanied by caretakers to monitor their well-being at all times. With growing responsibilities and work pressure, the family members may find it challenging to find a trustworthy caretaker. In such scenarios, an assisted living environment acts as a boon. A normal home embedded with different sensors to monitor an individual's well-being is called as Ambient Assisted Living(AAL). This living environment detects anomalous behaviour and recognizes human activities. In this research paper, a smart home activity recognition model is proposed and implemented using four machine learning algorithms using six different publicly available datasets. It has been observed that Random Forest machine learning algorithm shows the best accuracy on most of the dataset.  The Electrochemical Society</text>
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                <text>ECS Transactions, Vol-107, No. 1, pp. 20253-20264.</text>
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                <text>Naaz S., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India; Rajamohan K., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India</text>
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                <text>Smart Home Systems Using Wireless Sensor Network - A Comparative Analysis</text>
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                <text>Intravenous fluids with vitamins are given to people who are dehydrated and have an imbalance of electrolytes. When the IV bag is empty, the patient's blood flows through the IV line toward the empty bag because their blood pressure is higher than the IV bag's. This process, called diffusion can lead to pain and loss of blood. If the IV bag is empty and hooked up to the patient, air can get into the bloodstream. The air bubble enters the patient's bloodstream, causing the same catastrophic effects. This paper aims to eliminate the danger by creating Smart IV Bags in light of the rising number of risks in the medical sector brought on by the reverse flow of blood in an IV bag (intravenous bag). The Smart IV bags eliminate the need for constant physical monitoring of the IV bag's state while preventing reverse blood flow. For detection of the IV fluid state, a 0.5 ' diameter force-sensitive resistor is deployed. We integrate the system with a NodeMCU module and using Wi-Fi, it establishes communication between the smart IV bag and the person in charge at the hospital, like a nurse or a caretaker. In this study, the IV Bag is the 'thing' connected to the internet where the FSR readings are analyzed using NodeMCU script to determine if it needs to be emptied and send a WhatsApp message to the caretaker. This design establishes an IoT environment where the IV Bag automatically alerts the caretaker and eliminates the need for constant human intervention.   2023 IEEE.</text>
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                <text>Patent Number: 202241059619, Applicant: Dr.C.Rohith Bhat.&#13;
Signals received by one or more sensors and processed by a processor can contain features such as one or more audio, visual, linguistic, and physical features. One or more machine learning algorithms may be used to assess the audio, visual, linguistic, and bodily data, and the results may be used to infer an individual's emotional state. The most recent multimodal speech emotion identification techniques, with an emphasis on audio, text, and visual data. We offer a fresh, descriptive classification of approaches based on how they manage the dynamics of intra- and intramodality in the time dimension.</text>
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                <text>Medical sensors facilitate health-care applications to save a patient's life by continuously monitoring the patient's health. The combined feature of medical sensors and the fastest growing techniques that are Internet of things improves the accuracy of treatment. Internet of things techniques serve the smart and very effective medical service. Early diagnosis of the symptoms helps the health-care provider to get success in the treatment to save a patient's life. Many medical sensors are available in the health-care application that can monitor continuously patient health. Medical sensors can be wearable and nonwearable. There are some common parameters such as body temperature and a heart rate that are used to monitor human activity. These parameters are measured by using wearable and body-embedded sensors. The data collected from these parameters are analyzed by the medical devices for early detection of disease. The advanced internet of things techniques help to connect the sensors, patients, hospitals, and other medical devices. In this chapter, we highlight the use of different types of sensors with advanced technology (internet of things).  2023 Elsevier Inc. All rights reserved.</text>
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                <text>Subramanian V., Department of Data Science, CHRIST (Deemed to be University), Maharashtra, Lavasa, India; Dahiya S., School of Computing Science and Engineering, Galgotias University, Uttar Pradesh, Greater Noida, India; Thiruppathiraju G., School of Computing Science, KPR College of Arts Science and Research, Tamil Nadu, Coimbatore, India; Balusamy B., Shiv Nadar University, Tamil Nadu, Chennai, India</text>
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                <text>This paper presents a unique research problem in the area of automation system by using IoT. The mentioned approach utilizes Google assistant, which is incorporated within Google home which uses voice-controlled inputs and voice feedbacks. This paper discusses a new method to develop a smart energy meter at a distributor level and to make use of this technology to monitor the power consumption of each device individually which can help the user to monitor the electricity usage in real time and thus helps to save electricity and reduce cost on your electricity bill.  2020, Asian Research Association. All rights reserved.</text>
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                <text>Jaison A.M.; Julian Benadit P.; Kumar K.P.</text>
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                <text>Jaison A.M., Department of Computer Sciences of Engineering, Christ University, Bangalore, India; Julian Benadit P., Department of Computer Sciences of Engineering, Christ University, Bangalore, India; Kumar K.P., Department of Computer Sciences of Engineering, Christ University, Bangalore, India</text>
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                <text>Smart Mobile Device to Trace Moving Rogue Objects in Smart City Utilizing Dynamic Source Dynamic Destination Tracking Algorithm</text>
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              <elementText elementTextId="101939">
                <text>Ant Colony Optimization; Autonomous vehicles; Dynamic Source Dynamic Destination; Meta-heuristic; Mobile Edge Computing; Optimization; Shortest path estimation; Swarm intelligence</text>
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                <text>In the present literature, various algorithms are available for computing the shortest path between two objects. The maximum number of these algorithms compute the shortest path either between two static objects or one static object and one dynamic object. This article presents an insight to integrated Mobile Edge Computing (MEC) based smart devices for tracking mobile rogue objects based on dynamic source and dynamic destination optimal cost estimation. This device considers any two mobile objects to estimate the shortest path between them. The proposed Ant Colony Optimization (ACO) based algorithm considers the property of dead-end removal and nth path exploration with efficient self-loop removal strategy. To review the performance of the proposed algorithm, experimentations are carried out and compared with several well-established shortest cost estimation techniques available in the literatureFloyd Warshall, Bellman Ford, Dijkstra, A* algorithms and the only dynamic shortest path algorithm. The detailed algorithmic comparisons clearly indicate the superiority of the proposed one over the existing dynamic and present state-of-the-art shortest path estimation methodologies.  2023 IETE.</text>
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              <elementText elementTextId="101941">
                <text>Mukhopadhyay D.; Chakraborty T.; Saha A.; Mondal K.; Purkayastha R.</text>
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                <text>IETE Journal of Research, Vol-69, No. 9, pp. 5822-5829.</text>
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                <text>ISSN: 3772063</text>
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                <text>Mukhopadhyay D., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST Deemed to be University, Bangalore, 560 074, India; Chakraborty T., EURECOM, Biot, 06410, France; Saha A., Department of Computer Science &amp;amp; Engineering, Indian Institute of Technology Patna, Bihar, India; Mondal K., Indian Institute of Technology (Indian School of Mines), Dhanbad, India; Purkayastha R., Department of Computer Science and Engineering, Adamas University, Barasat, West Bengal, Kolkata, India</text>
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                <text>Smart Online Oxygen Supply Management though Internet of Things (IoT)</text>
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                <text>We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker.   2022 IEEE.</text>
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                <text>Gehlot A.; Rajat Mohan L.; Gupta A.; Anandaram H.; Alanya-Beltran J.; Kalyan Chakravarthi M.</text>
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