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Computing, sciences and Communications (ICCSC), International Conference on

作者： Abhishek Tripathi Sethumadhavan R Jujaru Sasi Kiran Anish S Shubham Aniankar Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamil Nadu India Department of Electronics Engineering Shri Ramdeobaba College of Engineering and Management Nagpur India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353655

In today's rapidly evolving world, numerous people encounter difficulties in accessing medical services for minor health issues. To tackle this problem, we introduce a robust pulse monitoring system that also checks room temperature and humidity. This system harnesses cutting-edge technology to deliver live health and environmental information directly to medical professionals, allowing them to evaluate a patient's health remotely and offer immediate medical guidance or action. The setup includes essential hardware components like the NodeMCU ESP8266 microcontroller, the DHT11 sensor for temperature and humidity measurement, and a pulse sensor to monitor the patient's heart rate. The data from these sensors is sent to the cloud-based service ThingSpeak using the ThingESP library, making it available for healthcare providers to review and act upon. Moreover, the system incorporates TWILIO, a communication service, to facilitate WhatsApp messaging that alerts healthcare professionals instantly in the event of unusual health or environmental readings. This pioneering approach ensures that individuals can obtain prompt medical support and surveillance from their homes, enhancing proactive health management and ultimately improving health outcomes.

关键词： Temperature sensors Temperature measurement Wireless sensor networks Reviews Microcontrollers Surveillance Medical services Libraries Older adults Internet telephony

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IoT-Embedded Traffic Cones with CNN-based Object Detection to Roadwork Safety 2

IoT-Embedded Traffic Cones with CNN-based Object Detection t...

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2nd International Conference on Intelligent Data Communication technologies and Internet of Things, IDCIoT 2024

作者： Saillaja, V. Rehaman Pasha, Mohammed Krishnaveni, S. Ravinder, Bathini Srinivasan, S. Nandagopal, V. SRM Institute of Science and Technology Kattankulathur Faculty of Management Studies Tamil Nadu Chennai India Malla Reddy Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India S.A.Engineering College Department of Information Technology Tamil Nadu Chennai India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India School of Engineering Mohan Babu University Department of Electrical and Electornics Engineering Andrapradesh Tirupathi India

ISBN: (纸本)9798350327533

Motorists and construction workers both need to use extreme caution while passing through roadwork zones. This research provides a novel strategy for increasing the security of roadwork by combining Internet of Things (IoT) devices with object recognition through Convolutional Neural Networks (CNNs). To improve communication and data sharing with a centralized control center, this technology equips conventional traffic cones with integrated IoT devices. Traffic cones with IoT sensors track things like their location, the brightness of the surrounding area, and the volume of vehicles on the road. Useful information about the roadwork environment is supplied wirelessly from the cones to the control center. Live video feeds from the IoT-enabled traffic cones are analyzed using a CNN-based object identification algorithm. The model can view and follow vehicles, pedestrians, and other possible threats in a road construction zone. Construction workers and traffic management officials are immediately notified of potential safety hazards through real-time object detection warnings. In terms of roadwork safety, this integrated system has several advantages, such as enhanced knowledge of the current situation, faster identification of potential dangers, and more effective traffic management. Roadwork zones may be made safer for employees and the public using IoT technology and cutting-edge computer vision methods. © 2024 IEEE.

关键词： Hazard Detection Object Detection Roadwork Environment Safety Alerts Traffic Cones

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Secure Electronic Healthcare Record Using Robust Authentication Scheme

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2023年第2期50卷 468页

作者： Yaseen, Aqeel A. Patel, Kalyani Yassin, Ali A. Aldarwish, Abdulla J. Hussein, Haitham A. Department of Computer Science Gujarat University Ahmedabad380009 India K.S. School of business Management and Information Technology Gujarat University Ahmedabad380009 India Computer Science Department College of Education for Pure Sciences University of Basrah Basrah61004 Iraq Accounting Technologies Department Southern Technical University Basrah61001 Iraq

Electronic Healthcare Record (EHR) has been actively promoted recently. Healthcare records and paper-based medical prescriptions are scattered and unorganized in medical institutions and clinics, thereby prompting many efforts to advance the EHR from traditional clinical settings to an efficient electronic medical model to regulate health records appropriately and accurately. With the development of technology and data exchange over the Internet or local networks, protecting transmitted data in healthcare records is necessary. This paper presents a secure EHR system utilizing robust authentication and RSA digital signature. We performed formal and informal security analyses utilizing the Scyther tool and the Canetti–Krawczyk (CK) model. Therefore, the proposed scheme has a higher level of security than the previous relevant work by resisting the dangers of well-known cyberattacks, such as impersonation, DoS, replay, man-in-the-middle (MITM), and insider attacks. Our work balances the security complexity and the communication cost, and the comparison tables show that the proposed scheme has the lowest communication cost. Moreover, we presented a secure prescription through a QR code generated using the prescription and the physician’s RSA digital signature. © 2023, IAENG International Journal of computer science. All Rights Reserved.

关键词： Authentication

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Implementation of IoT-Enabled Automatic Solar Power Tracking System

Implementation of IoT-Enabled Automatic Solar Power Tracking...

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Computing, sciences and Communications (ICCSC), International Conference on

作者： Abhishek Tripathi Addepalli Kavya Sree Bhimavarapu Triveni Alluru Rishitha Batta Malleswari Shubham Anjankar Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamil Nadu India Department of Electronics Engineering Shri Ramdeobaba College of Engineering and Management Nagpur India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353655

In order to maximize the performance of solar panels, this paper outlines a systematic approach for creating a tracking system for solar power. The solar power tracking system is a hardware/software prototype that helps solar panels automatically align with the sun at the right time to generate the most electricity. Light Dependent Resistor (LDRs) sensors, solar panels, servo motor, and an Arduino UNO microprocessor are the main components included in this system. By increasing their exposure to sunlight throughout the entire day, the system improves the effectiveness and output of solar system. This study describes the solar panels' ability to detect the light and rotate in response to the sun's location. The solar power tracking system prototype has been designated for use in future. In the proposed setup, it is found that at 12:00 noon, the single-axis tracking system achieves approximately 63.64% higher output power efficiency compared to the fixed-tilt system.

关键词： Systematics Solar farms Prototypes Solar energy Sensor systems Sensors Solar panels Sun Sustainable development Servomotors

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The Role of Cloud Computing in Real-Time Big Data Analytics for Smart Cities and Infrastructure Automation 15

The Role of Cloud Computing in Real-Time Big Data Analytics ...

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15th International Conference on Computing Communication and Networking technologies, ICCCNT 2024

作者： Sarpal, Sumeet Singh Kumar, V. Mathan Pimplapure, Vivek Patil, Shrinivas Marathe, Vijay Henrietta, H. Mary Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Dr. Ambedkar Institute of Management Studies And Research Department of Management Nagpur India School of Mangement - Pg Karnataka Bangalore India Prince Shri Vishwakarma Institute of Technology Department of Electrical Pune India Saveetha Engineering College Department of Mathematics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350370249

With the enhancement of Big Data and Smart Cities, Cloud Computing has emerged as an advanced technology. Innovative city operations require real-time processing of vast volumes of data from various sources like sensors, IOT devices, or social media so that it can be analyzed and acted on in real-time with better automation for its infrastructure against different parameters. This article examines the potential of cloud computing to enable real-time big data analytics for smart cities and infrastructure automation. The cloud allows for real-time big data analytics, collecting input from disparate sources across a business ecosystem and analyzing it immediately for actionable insights. The need for large amounts of data combined with the nature of many Iota devices necessitates processing and storage at scale, a task uniquely suited to cloud computing due to its ability to provide scalability, flexibility, and lower cost essential qualities in building intelligent cities or automated infrastructure. Cloud computing offers a space for shared data and collaborative analysis, allowing the city government to open up its vast browser-based datasets so that other agencies (both within government and outside it), researchers, and even citizens can access this information, in turn driving innovation or assisting with strategic planning. Moreover, the evolution not just in cloud-based machine learning and artificial intelligence algorithms but also device-side AI/ML allows for predictive analytics, which can be helpful to preemptively discern potential failures to prevent them pro-actively, thus augmenting city operations efficacy as well as resource utilization besides operational efficiency of infrastructural management. Cloud computing is integral for real-time and big data analytics and innovates cities, organizations, and infrastructure. © 2024 IEEE.

关键词： Automation Infrastructure Intelligent Organizations Parameters

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IoT-enabled smart gardening with precise soil type monitoring for horticultural crops

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Procedia computer science 2025年 259卷 1463-1471页

作者： Abhishek Tripathi Shubham Anjankar Madhu Mohan Rao A. Parivazhagan Abhishek Pahuja Divyangna Gandhi Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamil Nadu India Department of Electronics Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Koneru Lakshmaiah Education Foundation Andhra Pradesh India Indus Institute of Technology & Engineering Indus University

This manuscript introduces an IoT-enabled Smart Gardening system focused on precise soil type monitoring for horticultural crops. The system is designed to adapt to the unique properties of four primary soil types: Sandy, Silty, Loamy, and Clay. By utilizing advanced soil sensors, the system continuously measures critical parameters, including soil moisture, temperature, pH levels, and nutrient concentrations (NPK), specific to each soil type. These real-time environmental metrics are transmitted to a cloud-based platform, enabling data analysis and dynamic decision-making. The system employs predictive algorithms to optimize irrigation, fertilization, and other cultivation processes. Tailored irrigation strategies are applied based on soil type characteristics—high drainage in sandy soils, moisture retention in silty and clay soils, and nutrient-rich loamy soils. By integrating sensor data with cloud computing, the system allows remote monitoring and control, ensuring accurate water and nutrient management. This reduces resource wastage and minimizes the risks of overwatering or under-irrigation, enhancing crop yield and quality. Field trials conducted on various horticultural crops demonstrated significant improvements in water conservation, nutrient management, and overall crop performance across different soil types. The results highlight the system’s ability to increase productivity while reducing environmental impacts. Additionally, the cloud-based infrastructure supports long-term data collection, enabling predictive insights for future cultivation cycles. This IoT-based approach showcases the potential for precision agriculture, driving sustainable practices and efficient resource utilization in horticultural crop management.

关键词： IoT-Enabled Irrigation Soil Type Monitoring Precision Agriculture Smart Irrigation System Horticultural Crops

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Classification of Rice Variant using Deep Learning

Classification of Rice Variant using Deep Learning

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Modeling, Simulation & Intelligent Computing (MoSICom), International Conference on

作者： K Susheel Kumar Prem Kumari Verma Subham Chaurasia Nagendra Pratap Singh Department of Information Technology Manipal Academy of Higher Education Manipal Institute of Technology Bengaluru Manipal Karnataka India Department of Computer Science and Engineering National Institute of Technology Jalandhar Punjab India Department of Computer Science and Engineering Axis Institute of Technology and Management Kanpur India

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

Rice is a popular crop in the world. This paper has constructed a model using deep Learning for classification. Classification is a critical process in identifying the class of an image. Here, the Rice dataset has been taken to classify the class of rice Breed. Image Classification is a complex process that is affected by various factors. The emphasis is placed on summarizing essential superior class procedures and the strategies used for improving classification accuracy. This paper uses the deep learning approach for classification, such as CNN, and some activation functions, such as ReLu Softmax with Dense layers. The classification process used various domains, such as Machine Learning and deep learning. In this model, five classes of rice breed have been taken and classified with an accuracy of ${9 6 \%}$.

关键词： Deep learning Accuracy Computational modeling Crops Image classification

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Hybrid Algorithms based Software Development System using Artificial Intelligence for the Business Development 3

Hybrid Algorithms based Software Development System using Ar...

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3rd International Conference on Advance Computing and Innovative technologies in Engineering, ICACITE 2023

作者： Hirolikar, Deepali S Tirpude, Raman R. Rithik, B. Varghese, Sony Saraswat, Shalu Jayalwal, Anu Maharashtra National Law University Department of Management Nagpur India Electronics and Communication JSS Academy of Technical Education Bangalore India Management Xavier Institute of Management and Entrepreneurship Kochi India PDEA'S College of Engineering Information Technology Manjari Bk Pune India SPPU Maharashtra Pune India Computer Science Sushant University India

ISBN: (纸本)9798350399264

In this essay, we look at how to provide a product to a consumer as quickly as possible without compromising its quality. We'll show how putting six continuous architectural principles into practise will help us ensure the quality of the finished project while shortening the manufacturing cycle. Prior to reducing costs, it's important to provide the things as fast as feasible. We can do this by using a variety of strategies, such availability plans, that enable us to maintain the greatest levels of quality, just as the software team was able to. He talks about these approaches, as well as a few more, for delivering top-notch printer software designs quickly. India has a big food-related industry, principal means of support. In this essay, I want to look at how to provide items to customers as quickly as possible without sacrificing product quality. Even while making enhancements, we will consider how the six comparable design components may ensure that the finished product has the highest possible quality in the shortest period of time possible. Giving excellent goods quickly and doing them effectively are both essential. To do this, we may use a range of strategies, such as unavailability techniques, which enable us to maintain the highest level of accuracy that our team of engineers is capable of. He discusses these methods and a few options for the goods' distribution. Using this stock market idea, growers can sell their goods at the highest bidder pricing. Farmers that fill out this form may register themselves and have access to a variety of facilities, such as market alerts, merchant engagement, assessments, and more. The creation of knowledge devices, automated weapon systems,[1] language comprehension, computer vision, legal analysis, and agricultural monitoring are just a few examples of the many uses for data modelling. The problem of the expanding global agricultural output will be addressed by the employment of Al in contemporary agriculture. Based on Al

关键词： Agricultural products

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Exploring Financial Literacy's Impact on Preventing Economic Crimes: A Random Forest Analysis

Exploring Financial Literacy's Impact on Preventing Economic...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Pol, Naveen Guled, Anand Manikumar, T. Praba, R. Suyam Arulkarthick, E.K. Raj, Roop ISBR Business School Karnataka Bangalore India Department of Management Studies Global Academy of Technology Bengaluru India Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Deemed to be University Tamilnadu India School of Management Sri Krishna College of Engineering and Technology Coimbatore India Electronics and Communication Engineering Nandha Engineering College Erode India Department of Economics HNBG Central University Uttarakhand India

ISBN: (纸本)9798350355338

Financial crime poses a substantial menace to individuals, businesses, and economies on a global scale. In spite of attempts to hinder such unlawful acts, the intricate characteristics of deceitful activities require inventive methods for identification and reduction. This study aims to investigate the correlation between financial literacy and the prevention of economic crime by utilising sophisticated machine learning techniques, notably Random Forest Analysis. The approach we present combines data collection, preprocessing, feature selection, model construction, and Random Forest Analysis to forecast economic crime using financial literacy levels. In contrast to previous studies, our methodology provides several benefits, such as thorough feature selection, resilient model training, and exceptional predicted accuracy. The assessment of the suggested system reveals outstanding outcomes, with an accuracy of 0.94, precision of 0.92, recall of 0.90, F1-score of 0.95, and AUC of 0.92. These findings emphasise the efficacy of utilising financial literacy to reduce the dangers of economic crime and showcase the promise of modern machine learning approaches in tackling intricate social issues. © 2024 IEEE.

关键词： Adversarial machine learning

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Mqtt Routing Optimizing Based Intrusion Detection for Internet of Things Using Hybrid Machine Learning

Mqtt Routing Optimizing Based Intrusion Detection for Intern...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Hoomod, Haider K. Al-Hamami, Mohammad Alaa Kadhim, Aqeel Kamil Mohammed, Qutaiba Humadi Niaf, Jolan Rokan College of Education Mustansiriyah University Baghdad Iraq Applied Science University Manama Department of Management Information Systems Manam Bahrain Imam Al-Kadhim College Computer Techniques Engineering Department Baghdad Iraq College of Nursing University of Baghdad Baghdad Iraq Informatics Institute for Postgraduate Studies University of Information Technology and Communications Baghdad Iraq

ISBN: (纸本)9798350369106

With the advent of the Internet of Things, a world was born in which everything could be uniquely identified and monitored, tracked, and managed by computer programs. Items can self-configure using a predefined communication protocol. Other software programs can be linked to operate together using Message Queue Telemetry Transport Protocol (MQTT) or MQSeries components. Business integration software and middleware are common terms for this category of applications. With its suggested lightweight, easy-to-implement, and lowbandwidth system for billions of smart items, the MQTT protocol offers a wide range of potential applications, including home automation. In order to enhance the power savings in MQservice routing, we presented an intelligent assistant for optimizing routing model. For Internet of Things (IoT) purposes, it introduces an optimal routing model based on optimized hybrid machine learning-based anomaly detection (OHMLA). In order to extend the reach of a network, the offered approach allows Internet of Things devices to make efficient use of energy. To further enhance Intrusion Detection identification and get optimum network selection routes, the moth Salp Swarm technique (SSA) technique is used for the optimized hyperparameters. The model is capable of accurately detecting attacks that result in network congestion, causing delays in connection response and data transfer in IoT network. © 2024 IEEE.

关键词： Middleware

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