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                <text>Deep reinforcement model; IoT; Prediction; Rainfall forecast</text>
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                <text>This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting.  2023 The Authors</text>
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                <text>Nithyashri J.; Poluru R.K.; Balakrishnan S.; Ashok Kumar M.; Prabu P.; Nandhini S.</text>
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                <text>Measurement: Sensors, Vol-29</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 26659174</text>
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                <text>Nithyashri J., Department of Computing Technologies, School of Computing, SRM Institute of Science and Technology, Chengalpet District, Kattankulathur, 603203, India; Poluru R.K., Department of Information Technology, Institute of Aeronautical Engineering, Hyderabad, India; Balakrishnan S., Department of Computer Science and Business Systems, Sri Krishna College of Engineering and Technology, Coimbatore, India; Ashok Kumar M., Faculty of Computer Science, Department of Computer Science and Software Engineering, Skyline University Nigeria, Kano, Nigeria; Prabu P., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Nandhini S., Department of Computer Science and Engineering, Karpagam Academy of Higher Education, Tamilnadu, Coimbatore, India</text>
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                <text>Iot based real time potholes detection system using image processing techniques</text>
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            <description>The topic of the resource</description>
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              <elementText elementTextId="126006">
                <text>GPS; Image Processing; Index Terms: Bluetooth communication; IoT; Real time pothole detection; Sensors; Smartphones; WiFi</text>
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                <text>Accidents owing to potholes has become an alarming problem in todays life. The first step to solve this problem requires, designing a device embedded on the vehicle which can continuously scan the road surface for identifying potholes, alerting the driver in time and enable the driver to avoid the pothole. The second step is to introduce a technique to enable the device to locate the position of the pothole via GPS (Global Positioning System). The GPS data can be uploaded via a GPRS (General Packet Radio Service) module or Bluetooth module onto a data base which is stored locally. This database can then be transferred to the cloud using WiFi or 4G technology by connecting the system. The third aspect is to link the database to a network system incorporating mapping software such as Google Maps or Open-Street Map. The data in the system can be made available to the general public as well as municipalities and road maintenance agencies. Awareness of the location of potholes will help drivers to avoid those roads and being more careful while driving on the same roads. This paper focuses on the pothole detection task based on image processing algorithms and the data captured from ultrasonic sensor placed on the vehicle. The later steps were implemented through Bluetooth interface available in smartphones.  IJSTR 2020.</text>
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              <elementText elementTextId="126008">
                <text>Singh K.; Hazra S.; Mukherjee C.; Sushanth G.; Gowda S.</text>
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              <elementText elementTextId="126009">
                <text>International Journal of Scientific and Technology Research, Vol-9, No. 2, pp. 785-789.</text>
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              <elementText elementTextId="126010">
                <text>International Journal of Scientific and Technology Research</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079650231&amp;amp;partnerID=40&amp;amp;md5=89c272e822688dededa699ef635aba96" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079650231&amp;amp;partnerID=40&amp;amp;md5=89c272e822688dededa699ef635aba96&lt;/a&gt;</text>
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                <text>ISSN: 22778616</text>
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              <elementText elementTextId="126016">
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                <text>Singh K.; Hazra S.; Mukherjee C., Department of ECE, CHRIST (Deemed to be University, India; Sushanth G.; Gowda S., Department of ECE, CHRIST (Deemed to be University, India</text>
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            <element elementId="50">
              <name>Title</name>
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              <elementTextContainer>
                <elementText elementTextId="51377">
                  <text>Conference Papers</text>
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          <element elementId="50">
            <name>Title</name>
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            <elementTextContainer>
              <elementText elementTextId="177538">
                <text>IoT Based Risk Monitoring System</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="177539">
                <text>Arduino; climate changes; IoT; sensors</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="177540">
                <text>The Internet of things (IoT) aims at connecting different objects, things using internet. The IoT is expanding rapidly and this motivates to apply for the food preservation domain such as preserve the standard of the veggies and fruits. In this paper we have worked on a cold storage system to analyze the environmental conditions under which the food item is being stored. The proposed system senses the temperature, moisture, gas parameters of surrounding environment as these parameters affect nutritional values of food items. An Arduino-based system is created and put into operation; it serves as both a central hub and a network layer for the refrigerated holding tank. It is also linked to the cloud, where an open-source application server supports digital storage functions. By establishing a connection to the database (DB) via its IP address, the measured variables are delivered to the base station (BS) from the cloud and stored there. Then, a cooperative sensing model that uses many observed information as input and one merged informational item or action to be performed as output is tried. As a result, numerous inputs, such as temperature and humidity, were combined and averaged to provide a tightly integrated result. Last, the system integrated an android mobile application which is used to facilitate user interaction and connect through IoT based system that is station or gateway and the internet. GPS is Used to track the remote cold storage and transport container live locations.   2022 IEEE.</text>
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          <element elementId="39">
            <name>Creator</name>
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            <elementTextContainer>
              <elementText elementTextId="177541">
                <text>Joy S.; Neethu P.S.; Babychithra R.; Anju M.I.</text>
              </elementText>
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              <elementText elementTextId="177542">
                <text>International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022 - Proceedings, pp. 349-353.</text>
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            <name>Publisher</name>
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            <elementTextContainer>
              <elementText elementTextId="177543">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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            </elementTextContainer>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="177544">
                <text>2022-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1109/IIHC55949.2022.10060418" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/IIHC55949.2022.10060418&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150840027&amp;amp;doi=10.1109%2FIIHC55949.2022.10060418&amp;amp;partnerID=40&amp;amp;md5=219a3fc58845e4eb0c97006335d9451f" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150840027&amp;amp;doi=10.1109%2fIIHC55949.2022.10060418&amp;amp;partnerID=40&amp;amp;md5=219a3fc58845e4eb0c97006335d9451f&lt;/a&gt;</text>
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                <text>ISBN: 978-166545687-6</text>
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                <text>English</text>
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                <text>Joy S., New Horizon College of Engineering, Dept. of Electronics and Communication, Bangalore, India; Neethu P.S., School of Engineering and Technology, CHRIST (Deemed to Be University), Dept. of Electronics and Communication Engineering, 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</text>
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            <element elementId="50">
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          <element elementId="50">
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            <elementTextContainer>
              <elementText elementTextId="187668">
                <text>IOT Based Smart Agriculture System</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
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            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="187669">
                <text>IOT WSN Smart Agriculture Gateway Sensors</text>
              </elementText>
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              <elementText elementTextId="187670">
                <text>Smart agriculture is an emerging concept, because IOT sensors are capable of providing information about agriculture fields and then act upon based on the user input. In this Paper, it is proposed to develop a Smart agriculture System that uses advantages of cutting edge technologies such as Arduino, IOT and Wireless Sensor Network. The paper aims at making use of evolving technology i.e. IOT and smart agriculture using automation. Monitoring environmental conditions is the major factor to improve yield of the efficient crops. The feature of this paper includes development of a system which can monitor temperature, humidity, moisture and even the movement of animals which may destroy the crops in agricultural field through sensors using Arduino board and in case of any discrepancy send a SMS notification as well as a notification on the application developed for the same to the farmer's smartphone using Wi-Fi/3G/4G. The system has a duplex communication link based on a cellularInternet interface that allows for data inspection and irrigation scheduling to be programmed through an android application. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas.  2018 IEEE.</text>
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              <elementText elementTextId="187671">
                <text>Sushanth G.; Sujatha S.</text>
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                <text>2018 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2018</text>
              </elementText>
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            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="187673">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
              </elementText>
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                <text>Sushanth G., Department of ECE, Christ University, Bangalore, India; Sujatha S., Department of ECE, Christ University, Bangalore, India</text>
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                <text>Patent Number: 202141035598, Applicant: Dr. Poornima G.&#13;
Energy is the essential utility needed. Thus, the management of energy use is a significant priority, as the enormous growth changes are sweeping the globe, and doing so is the best answer, beginning domestically. There are numerous difficulties in the existing home energy meter reading systems, such as construction problems, too little bandwidth, poor real-time, no fast two-way communication, etc. Therefore, based on wireless internet technology, a smart meter is suggested. An Arduino microcontroller and raspberry pi CPU are used for the suggested smart energy meters for house management.</text>
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                <text>Patent Number: 202111031077, Applicant: Dr. Vikas Kumar.&#13;
The Smart Green House concept has been brought into the agricultural area to promote plant development in a short period of time. With an IoT-enabled framework controlled by a Smart Green House Intelligence Decision Support System, the system's quality can be improved. The system uses multiple sensors strategically positioned throughout a greenhouse to make decisions about actions such as water supply and nutrition level. All of the sensors and control systems operate in an automated setting, allowing small farmers to benefit from the greenhouse technology.</text>
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                <text>According to studies, there are approximately 850 million poultry birds across India, with an average of 30 million farmers working in the sector. In other words, a poultry farm is a trustworthy and long-term way to make money in India. However, managing a poultry farm is labour intensive due to the need for constant surveillance and control over a wide range of environmental factors. The actual implementation of this is significantly more complicated, expensive, and time-consuming. The paper suggested a smart poultry system that tries to provide the solution for all the issues. The health of poultry birds heavily relies on environmental parameters, so variables like temperature and humidity are measured and monitored continuously. The website was made so that poultry keepers may get reliable information about their birds' health and use that information to take the appropriate measures. Moreover, in the event of a crisis, such as a fire or the illness of a single bird, the owner will receive a notification. It is also possible to gather information about the poultry in the specified timespan. The Firebase cloud is used for wireless monitoring and managing the poultry system. The suggested automatic smart poultry system will make the birds healthy and it indirectly helps the owners to increase their profit with minimal human effort.   2022 IEEE.</text>
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                <text>Sandhiya R.; Vamshi Mohana T.; Jothi B.; Agarwal J.; Kulshrestha N.; Sandhiya S.</text>
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                <text>6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022 - Proceedings, pp. 150-156.</text>
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                <text>Sandhiya R., R M K College of Engineering and Technology, Department of Computer Science and Engineering, Tamil Nadu, Thiruvallur, 601206, India; Vamshi Mohana T., R B v R R Women's College, Department of Computer Science, Telangana, Hyderabad, 500027, India; Jothi B., Srm Institute of Science and Technology, Department of Computational Intelligence, Tamil Nadu, Kattankulathur, 603203, India; Agarwal J., Vardhaman College, Affiliated to M. J. P Rohilkhand University, Bijnor, Department of Zoology, Uttar Pradesh, Bareilly, 246701, India; Kulshrestha N., Christ Deemed to Be University-Delhi Ncr, Department of Commerce Finance and Accountancy, Uttar Pradesh, Ghaziabad, 201003, India; Sandhiya S., Panimalar Engineering College, Department of Information Technology, Tamil Nadu, Chennai, 600123, India</text>
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                <text>Water is one of the important needs for a human being. Life on Earth is possible due to the presence of water on its surface. Even though 71% of Earth's surface is covered with water, the availability of water in certain areas is very less. So, the people in these areas must reserve water for ensuring a steady availability. These problems can be rectified with the help of Internet of Things (IOT). IOT is a global infrastructure with certain standards and communication protocols by which virtual and physical things can interact and exchange data by connecting to each other. In this paper, we propose a system for monitoring the availability of water, based on the water level in the storage system. Water level is measured with the help of a waterproof ultrasonic sensor and when the level reaches a threshold value, a notification is sent to the user or to the vendor to take the necessary action. The live feed data is sent to a relational database for storing and analyzing the data to predict when the water will run out, and to make sure that the water storage system gets refilled before that point of time. After processing the raw data from the sensors, the system can generate a fusion chart that can show or indicate the amount of water inside each storage system. With this, the user can have an idea of how much water is left in each of the storage system. The main aim of the proposed system is to showcase the functionalities and uses of different sensors and modules used in an IOT based system with the application of Wireless Sensor Network (WSN). In this present scenario, the world is filled with data both relevant and irrelevant, wherein the data for predicting a water crisis is less. So, through the proposed system we are generating a dataset for the prediction of a water crisis in an organization or a community.  2019 IEEE.</text>
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                <text>Reddy D.R., Department of Electronics and Communication Engineering, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, Telangana, Hyderabad, India; Praveenraj D.D.W., School of Business and Management, Christ University, Karnataka, Bangalore, India; Chandramowleeswaran G., Vel Tech Rangarajan Dr. Sagunthala R&amp;amp;D Institute of Science and Technology, Tamil Nadu, Chennai, India; Karnan C., Department of Mathematics, K. Ramakrishnan College of Engineering, Tamil Nadu, Tiruchirappalli, India; Vallikkannu M., Vel Tech Rangarajan Dr. Sagunthala R&amp;amp;D Institute of Science and Technology, Tamil Nadu, Chennai, India; Murthy A.G., Library and Information Science, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Pallavaram, Chennai, India</text>
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                <text>The modern-day retailing world is struggling to provide real-time and hyper-personalised customer interaction in the context of fragmented behavioural data, sluggish analytics, and in-store interventions that are generic. Current Internet of Things (IoT) retail systems are mainly focused on inventory and transactional insights and do not capture more in-depth behavioural and emotional indicators that affect purchase intent and satisfaction. In this context, this paper will suggest an Internet of Things (IoT)-Based Behavioural Analytics Platform to Hyper-Personalised Consumer Engagement in Retail Management (IBAPS-RM). The framework incorporates multimodal Internet of Things (IoT) sensing, edge computing, and cloud intelligence in creating Multimedia Behavioural Digital Twins (Behavioural Digital Twin (BDT) that dynamically change in response to contextual, environmental, and Interaction-driven information. One of the most notable novelties is the Behavioural Fusion Neural Unit (BFNU) (Behavioural Fusion Neural Unit (BFNU)), that conducts real-time sensor fusion between gaze movement, dwell time, gestures, proximity, and purchase latency to determine behavioural intent and launch micro-personalised interventions in the form of adaptive light, context sensitive offers and personalised digital content. Reinforcement learning also enhances engagement policies through continuous optimisation based on feedback. Experimental analysis shows that IBAPS-RM has better engagement intelligence, with over 93% of personalisation accuracy, 73% shorter decision latency, and 64% higher conversion rate than traditional Internet of Things (IoT) retail systems. The suggested solution improves responsiveness, consumer experience, and operational effectiveness, and promotes privacy-conscious behavioural modelling. In general, IBAPS-RM creates a dynamic, proactive retail intelligence paradigm that dedicates behavioural inference to real-time engagement delivery.  2025, International Academic Institute for Science and Technology. All rights reserved.</text>
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                <text>Nagendran G.A., Dept. Of. Ise, Cmr Institute of Technology, Bengaluru, India; Raj R.J.S., Dept. of Engineering, Design, Information and Communications Technology, Bahrain Polytechnic, PO BOX 33349, Isa Town, Bahrain; Priya C.S.R., Dept. of Computer Science and Engineering, Christ (Deemed to Be University), Bangalore, India; Singh H., Dept. Of. Ise, Cmr Institute of Technology, Bengaluru, India</text>
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                <text>Energy derived from natural sources, such as sunlight, wind, and water, is called green energy. Green energy is a source of energy derived from clean sources such as solar, wind, geothermal, and biomass. The environment benefts from green energy because green energy replaces the harmful effects of fossil fuels with more environmentally friendly options. Green energy sources release far fewer greenhouse gases, as well as little or no air pollutants when looked at in their full life cycle. Taking steps to reduce air pollution benefts not only the planet but also human and animal health. Increasing reliance on the Internet of Things (IoT) has helped modernize the energy industry. Sensor attached to generation, transmission, and distribution equipment is used in IoT applications in green energy production. Alternative energy offers several benefts over traditional energy options. As the demand for clean energy grows and environmental prudence becomes the norm, Internet of Things solutions for energy management keep developing. Using the Internet of Things today benefts green energy, enabling companies in this sector to make the most of their data, and improves effciency and safety.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.</text>
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                <text>Power Systems, pp. 119-145.</text>
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                <text>Patent Number: 202241015394, Applicant: Geetha V.&#13;
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                <text>The benefit of IoT devices is that they allow for automation; nevertheless, billions of connected devices connected with one another waste a substantial amount of energy. IoT systems will have difficulty in wide adoption if the energy requirements are not adequately managed. This study proposes a solution for IoT devices to regulate their energy consumption. Both hardware and software aspects are taken into consideration. Using a mobile computer or smartphone with Internet connectivity to interact with actual scenarios has grown more prevalent as technology has advanced over the years. An intelligent home automation system based on android applications has been developed to save electricity and human energy. This study aims to create comprehensive Energy optimization through intelligent home automation utilizing widely available mobile applications and Wi-Fi technologies. The devices are turned on and off using Wi-Fi. Intelligent home, in the area of electronics, automation is the most purposely misused term. Numerous technological revolutions have occurred as a result of this demand for automation. These were more essential than any other technologies due to their ease of use. These can be used in place of household current switches, resulting in sparks and, in rare instances, such as fires. A unique energy optimization system was developed to control household appliances while taking advantage of Wi-Fi benefits.  2023, Bentham Books imprint.</text>
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                <text>Chitra Kiran N., Department of Electronics and Communication Engineering, Alliance University, Karnataka, Bengaluru, India; Viswanatha Rao J., VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India; Aurelia S., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Skanda M.G., Department of Industrial &amp;amp; Production Engineering, JSS S&amp;amp;T University, SJCE, Mysore, India; Lakshminarayana M., Department of Medical Electronics Engineering, M S Ramaiah Institute Of Technology, Karnataka, Bengaluru, India</text>
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                <text>cancer detection; Internet of Things; routing; shepherd convolutional neural network; social optimization algorithm</text>
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                <text>The Internet of Things (IoT) has tremendously spread worldwide, and it influenced the world through easy connectivity, interoperability, and interconnectivity using IoT devices. Numerous techniques have been developed using IoT-enabled health care systems for cancer detection, but some limitations exist in transmitting the health data to the cloud. The limitations can be accomplished using the proposed chronological-based social optimization algorithm (CBSOA) that effectively transmits the patient's health data using IoT network, thereby detecting lung cancer in an effective way. Initially, nodes in the IoT network are simulated such that patient's health data are collected, and for transmission of such data, routing is performed in order to transmit the health data from source to destination through a gateway based on cloud service using CBSOA. The fitness is newly modeled by assuming the factors like energy, distance, trust, delay, and link quality. Finally, lung cancer detection is carried out at the destination point. At the destination point, the acquired input data is fed to preprocessing phase to make the data acceptable for further mechanism using data normalization. Once the feature selection is done using Canberra distance, then the lung cancer detection is performed using shepard convolutional neural network (ShCNN). The process of routing as well as training of ShCNN is performed using the CBSOA algorithm, which is devised by the inclusion of the chronological concept into the social optimization algorithm. The proposed approach has achieved a maximum accuracy of 0.940, maximum sensitivity of 0.941, maximum specificity of 0.928, and minimum energy of 0.452.  2022 John Wiley &amp;amp; Sons Ltd.</text>
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                <text>Gnanasigamani Samuel Raj E.S.; Diana Jeba Jingle I.; Maram B.; Ananth J.P.</text>
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                <text>International Journal of Adaptive Control and Signal Processing, Vol-37, No. 1, pp. 224-243.</text>
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                <text>&lt;a href="https://doi.org/10.1002/acs.3518" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1002/acs.3518&lt;/a&gt;
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                <text>Gnanasigamani Samuel Raj E.S., Department of Computer Science and Engineering, Thiagarajar College of Engineering, Tamil Nadu, Madurai, India; Diana Jeba Jingle I., Department of Computer Science and Engineering, Christ University, Karnataka, Bengaluru, India; Maram B., Department of Computer Science and Engineering, Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, Baddi, India; Ananth J.P., Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Tamil Nadu, Coimbatore, India</text>
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                <text>Proceedings of 2025 6th International Conference on Communication, Computing and Industry 6.0, C2I6 2025;</text>
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                <text>Ganachar S.R., Christ University, School of Engineering and Technology, Department of CSE, Bengaluru, India; Sharon Roji Priya C., Christ University, School of Engineering and Technology, Department of CSE, Bengaluru, India</text>
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                <text>The growth in demand for remote and prolonged healthcare monitoring has led to a strong growth in adoption of wearable technologies and Internet of Things -based solutions. These technologies are meant to help solve real-time health supervision challenges, particularly for older adults and those suffering from long-term conditions, through reduced need for constant onsite medical care. Here, we describe the design and deployment of an intelligent health monitoring system that utilizes low-cost sensors and wireless communication to enable real-time, continuous monitoring of important physiological and environmental parameters. The suggested system combines an array of sensors: the DHT11 sensor to measure environmental temperature and humidity, the MAX30102 sensor for heart rate and SpO2 monitoring in real-time, and the MPU6050 sensor to sense body posture, orientation, and motion. The sensors are connected to an ESP8266 Wi-Fi MCU, which serves as the hub node for data sensing and transmission. Sensor data that is aggregated is processed locally and then sent to a cloud-based platform for analysis, storage, and visualization. To improve the functionality of the system, the system utilizes a cloud-hosted rule-based Artificial Intelligence (AI) engine for interpreting physiological patterns, identifying signs of abnormal health conditions at an early stage, and offering context-aware, personalized health suggestions. The platform provides dual output modes for added accessibility and reliability: an OLED display for local feedback, and an offdevice cloud dashboard for caregivers and health workers to view patients in real time. This study demonstrates the potential for the integration of embedded systems, cloud computing, and light AI methods to make predictive health analytics and facilitate proactive healthcare interventions possible. Through emphasizing modular design, low power, and scalability, the system is particularly suitable for deployment in elderly care, post-surgery recovery, and chronic disease management. Experimental assessments suggest that the system offers a credible, cost-efficient alternative.  2025 IEEE.</text>
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                <text>chronic disease management; cloud computing; DHT11; elderly care; ESP8266; Internet of Things (IoT); MAX30102; MPU6050; real-time health analytics; remote patient monitoring; rule-based AI; wearable health monitoring</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>ISBN: 979-833150240-9;</text>
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                <text>IoT Framework, Architecture Services, Platforms, and Reference Models</text>
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                <text>Actuators; Architecture; Connected devices; Frameworks; Internet of things (IoT); Platforms; Sensors</text>
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                <text>Internet of things (IoT) is spawning a twirl in the world of connected devices by aiding the devices to connect, compute, and coordinate with each other. While the concept of IoT is still embryonic, its outcomes are trailblazing. IoT acts as a facilitator in creating a smart world by connecting devices through sensors and actuators to the Internet. The acceptance of IoT in various sectors indicates that the partakers in an IoT ecology are diverse. This demands common functionalities, interoperability standards, and network protocols across sectors. But there exists an extremity of incongruency in devices, capabilities, and network protocols, and therefore it is imperative to have a complete reference architecture model that necessitates the existing diversities and defines a new monody for the IoT environment. The lack of standard and uniform architectural knowledge, frameworks, and platforms is presently resisting the researchers to reap the benefits that the Internet of things (IoT) offers. This chapter summarizes various Internet of things frameworks, architectures, platforms, and reference models and thereby paves way for businesses to build IoT on it.  2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Mahalakshmi S.; Desai K.</text>
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                <text>EAI/Springer Innovations in Communication and Computing, pp. 37-59.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-3-030-77528-5_2" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-030-77528-5_2&lt;/a&gt;
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                <text>ISSN: 25228595</text>
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                <text>Mahalakshmi S., CMS Business School, Jain University, Bangalore, India; Desai K., Department of Professional Studies, CHRIST (Deemed to be University), Bengaluru, Karnataka, India</text>
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