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Intelligent Farming: IoT-Powered System for Efficient Soil Condition Analysis

Intelligent Farming: IoT-Powered System for Efficient Soil C...

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International Conference on System Modeling & Advancement in Research Trends (SMART)

作者： Ankur Sisodia Swati Vishnoi Nandini Sharma Shiv Shanker Singh Medha Khenwar Priyanka Gupta Department of Computer Engineering and Application GLA University Mathura Department of Computer Science Banasthali Vidyapith Rajasthan Department of Computer Science and Engineering G.L. Bajaj Group of Institutions Mathura Department of Computer Science and Engineering Sanskriti University Mathura

ISBN: (数字)9798350380583

ISBN: (纸本)9798350380590

Smart farming technology allows farmers to control and analyse variables in real-time, helping them optimize crop growth and manage their operations more efficiently. The use of specialized sensors, data collection tools, and advanced analytics in Internet of Things (IoT) systems is helping to bridge the gap between physical farm conditions and digital monitoring. In this study, we aim to develop a system that monitors soil conditions to support smart farming. The system provides farmers with live data on key environmental factors, such as temperature, humidity, soil moisture, and soil temperature, to improve crop yield and product quality. The IoT setup for this intelligent farming solution includes components like the DHT11 and humidity sensors, a DS18B20 temperature probe, LDR, water pump, and a 12V LED strip, all controlled by a NodeMCU. When the system is activated, it continuously monitors soil and environmental conditions and sends this information to the cloud for real-time access. If the soil moisture falls below a set threshold, the system automatically triggers irrigation. Our experimental results show that this model improves decision-making for managing farming conditions.

关键词： Temperature sensors Temperature measurement Smart agriculture Temperature distribution Soil moisture Real-time systems Internet of Things Monitoring Intelligent sensors Farming

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The Evolution and Integration of Seamlessly Synchronized Data Streams in Modern Businesses 3

The Evolution and Integration of Seamlessly Synchronized Dat...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Acharjya, Kalyan Sharma, Sunil Ezhilarasan, G. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Electrical and Electronics Engineering Karnataka Bangalore India

ISBN: (纸本)9798350343274

In today's age of data-driven decision making, it is crucial for organizations to keep all of their data streams in perfect sync. Research methods and findings from an investigation into 'The Evolution and Integration of Seamlessly Synchronized Data Streams in Modern Businesses' Data analytics, principal component analysis, k-means clustering, and autoregressive integrated moving average (ARIMA) are all included into the suggested technique. This all-encompassing method permits a thorough investigation into the development and incorporation of data synchronization in the present-day corporate environment. The results analysis demonstrates that the suggested approach outperforms the conventional ones. We compared the suggested strategy to six established alternatives. Data analysis, extensive analysis, mathematical modeling, practical insights, scalability, and overall performance are just a few of the areas where the suggested technique excels above conventional approaches. These distinctions are highlighted, and the data are represented robustly by four various forms of visualizations: scatter plots, pie charts, box plots, and heatmaps. The importance of synchronized data streams in contemporary enterprises is highlighted by our research, which highlights the need for a multidimensional and data-driven approach to this topic. The findings of this study may help businesses enhance customer service, save costs, and streamline operations by enhancing their data synchronization techniques. © 2023 IEEE.

关键词： Synchronization

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Privacy-Preserving Techniques for IoT Data Sharing 9

Privacy-Preserving Techniques for IoT Data Sharing

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9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Karthikeyan, P. Teotia, Shashiraj Pawan, Toralkar Reena, B. Ardly Melba Vibhakar, Chirag Kalai Priya, V. Velammal College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Madurai625009 India Swami Vivekanand Subharti University Department of Computer Application Meerut250005 India Madanapalle Institute of Technology & Science Department of Artificial Intelligence Andhra Pradesh Madanapalle517325 India Saveetha University Department of Computer Science And Engineering Tamil Nadu Chennai600124 India Gujarat Power Engineering &. Research Institute Mevad Mehsana Gujarat Technological University Department of Electrical Engineering Gujarat Ahmedabad382710 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

In aperiod dominated by the Internet of Effects (IoT), the sharing of data has become an integral aspect of technological advancements. still, the ubiquitous nature of IoT raises significant enterprises regarding stonerse questration. Thisexploration paper delves into innovatives equestration conservingwaysacclimatized for securing the sharing of IoT-generated data. The explores cryptographic protocols, anonymisation strategies, and decentralized fabrics toguard sensitive information while easing meaningful data exchange. Addressing the contradiction between datamileage and individuals equestration, the paper proposes new methodologies that intricately balance the need for dataparticipation with the imperative tocoverstoner confidentiality. By introducing a comprehensive analysis of sequestration-conserving mechanisms with in the IoT eco system, this exploration contribute sprecious perceptivity to the ongoingconverse on securing the digitalgeography. The findings offer a foundation for developing robustfabrics that harmonize the imperatives of dataparticipating with the consummatesignificance of securing stoner sequestration in the expanding realm of Io'Toperations. © 2024 IEEE.

关键词： Privacy-preserving techniques

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Artificial Intelligence in Cyber Defense: A Study of Modern Security Solutions

Artificial Intelligence in Cyber Defense: A Study of Modern ...

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Cognitive Computing in engineering, Communications, sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Shweta Dwivedi Naushad Varish Priyanka Department of Computer Application Integral University Lucknow India Department of Computer Science and Engineering Gitam(deemed to be University) Hyderabad campus Telangana India Department of Computer Science and Engineering SRM University-AP Guntur

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

AI is transforming cyber security with its creative methods for identifying, thwarting, and lessening cyberthreats. The growing complexity of attacks is too much for traditional security measures to handle. The use of artificial intelligence (AI) in contemporary cybersecurity is examined in this article, with particular attention paid to AI-powered solutions for threat identification, automated incident response, and intrusion detection systems (IDS). Combining machine learning and deep learning techniques improves artificial intelligence's ability to evaluate massive datasets, spot irregularities, and predict possible security breaches. This study also discusses important issues including data privacy, explainability of AI-driven solutions, and adversarial attacks on AI systems. Problems The report highlights how AI has the potential to transform cybersecurity and how further developments are necessary to address emerging security vulnerabilities. To summarise, AI is an effective tool for protecting intelligent systems, but continual innovation is required to guarantee reliable protection against emerging threats.

关键词： Data privacy Technological innovation Intrusion detection Transforms Threat assessment Time factors Reliability Artificial intelligence Protection Robots

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An Extended Approach of Agile Model towards Agile Requirement Quality Inspector 23

An Extended Approach of Agile Model towards Agile Requiremen...

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Proceedings of the 5th International Conference on Information Management & Machine Intelligence

作者： Anju Kalwar Deepika Shekhawat Sunita Singhal Jitender Singh Shekhawat Computer Application Jecrc University India Department of Computer Science & Engineering Manipal University Jaipur India Computer Science and Engineering Manipal University Jaipur India Kingston University London UK

ISBN: (纸本)9798400709418

Every web application is unique and thus requires unique or customized development procedure or phases. Additionally, gathering requirements properly and matching expectation are crucial in proper development of web application. If requirement is misinterpreted, then the company may face technical debt. As a result, traditional software development approaches cannot assure the quality development of online apps. There is a pressing need to establish an iterative development life cycle model capable of accurately responding to the dynamic changing needs of where application development while also maintaining quality in each development phase. The problem may be summed up as the need for an iterative development life cycle model that is simple to govern and can ease web application development by obtaining correct requirements and minimizing the number of iterations. This paper proposed the new model for developing web application and this model analyzed with product matrix.

关键词： Focus factor

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Impact of Glucocorticoid Toxicity Index on Immunosuppressive Management of Inflammatory Bowel Disease 5th

Impact of Glucocorticoid Toxicity Index on Immunosuppressive...

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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： Yadav, Dhyan Chandra Sharma, Sunil Agarwal, Chhaya Mehta, Deepak Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Biotechnology Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Glucocorticoid toxicity index (GTI) is a useful degree proposed by using a meta-evaluation to assess the chance of systemic glucocorticoid exposure in sufferers laid low with inflammatory bowels illnesses (IBD). The GTI is computed based totally on cumulative glucocorticoid cumulative dose and duration within the first yr. After a prognosis of IBD. The contemporary take a look at objectives to check the literature to decide the utility of GTI in predicting the danger of glucocorticoid toxicity in IBD patients. A literature search turned into conducted to pick out research that evaluated the predictive price of GTI for toxicity in IBD patients. The retrieved articles suggest that cumulative glucocorticoid dose and length prior to three hundred and sixty five days of the diagnosis of IBD have been massive factors related to the prevalence of glucocorticoid toxicity in IBD sufferers. However, different next elements may additionally have an effect on the toxicity of glucocorticoid exposure in IBD patients, along with age, comorbidities, and genetic polymorphisms. Moreover, some of the research, the outcomes validated that GTI can be a valuable device for immunosuppressive management in IBD sufferers to be able to discover patients who're much more likely to revel in systemic toxicity at some stage in immunosuppressive treatment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cumulative Exposure Glucocorticoid

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Transforming Agriculture with Cloud Computing: Data Processing and Analysis Innovations

Transforming Agriculture with Cloud Computing: Data Processi...

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Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), International Conference

作者： Shehu Mohammed Arun Singh Harpreet Kaur Department of Computer Application Lovely Professional University Phagwara India Department of Computer Science and Engineering Lovely Professional University Phagwara India School of Computer Science and Engineering Lovely Professional University Phagwara India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

Cloud computing is a game-changer in modern agriculture, providing new forms to access enormous data analysis. In this paper, we investigate how cloud computing solutions are being integrated with agricultural practices to improve the efficiency, scalability and availability in managing data pertaining to agriculture. Farming operations generate massive amounts of data from a multitude of sources like sensors, drones, and satellite imagery., the performance bottleneck becomes the traditional methods with which the data are being processed. So the common factor in all these problems lies with Cloud computing itself, it has a scalable infrastructure that provides reliable analysis and Real-time processing of large data sets throwing light on an array of questions people have about various aspects. In this paper, we explore the major innovations in cloud computing that power precise agriculture and examine how machine learning algorithms, data fusion methods, and distributed processing platforms are utilized. It also discusses cloud-based solutions, which can reduce costs of the use of resources, crop yield prediction, and risk management to weather/climate and pests. Cloud computing opens up a world of monitoring, analysis, and optimization to help provide higher yields more efficiently while maintaining a commitment to sustainable agriculture. Challenges and considerations in deploying cloud computing in agriculture, e.g., data security risks, privacy concerns, and the need for stable internet connection for rural environments are also articulated in the paper. The results of this project underscore the vital importance of cloud technology in redefining the agri-future and providing a robust platform for smarter and more sustainable agriculture.

关键词： Cloud computing Technological innovation Data analysis Agriculture Real-time systems Risk management Internet of Things Sustainable development Crop yield Farming

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Student Perceptions of AI-Enhanced Adaptive Learning Systems: A Pilot Survey 7

Student Perceptions of AI-Enhanced Adaptive Learning Systems...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2024

作者： Katonane Gyonyoru, Klara Ida Katona, Jozsef Institute of Social Sciences University of Dunaujvaros Department of Organizational Development and Communication Science Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Department of Software Development and Application Dunaujvaros Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemet Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary

ISBN: (纸本)9798331531119

Artificial Intelligence (AI) significantly enhances adaptive learning by personalizing and tailoring instruction to individual student needs. AI analyzes data in real-time to create personalized learning paths based on students' strengths, weaknesses, and preferences, which keeps students engaged and motivated. A major benefit of AI in adaptive learning is the provision of real-time feedback and assessment, allowing students to correct mistakes promptly and understand concepts more thoroughly. AI-based intelligent tutoring systems are primarily intended to simulate personalized tutoring processes that guide students in complex problem-solving and answering questions. It is convenient in teaching mathematics, sciences, and languages. AI also supports inclusive education, dealing with diversified learning requirements and styles, such as those of learners with disabilities. For the teacher, AI acts as a reflector of student performance so that one can intervene early and make adjustments in the method of instruction by creating effective learning environments. AI technology is a field in constant development and harbors the potential to change the face of adaptive learning, bringing an upswing in educational outcomes. This article will summarize the advantages and features that merit improvement of the AI-embedded adaptive learning systems with student feedback. © 2024 IEEE.

关键词： Contrastive Learning

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DeepDerm: Elevating Precision in Dermatological Diagnosis with Enhanced CNN 15

DeepDerm: Elevating Precision in Dermatological Diagnosis wi...

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

作者： Mundada, Monica R. Seema, S. Sowmya J, B.J. Student, Sonia Fathima Ramaiah Institute of Technology Department of Masters of Compiuter Application Banglore India Ramaiah Institute of Technology Department of Computer Science and Engineering Banglore India Ramaiah Institute of Technology Department of Artificial Intelligence and Machine Learning Banglore India

ISBN: (纸本)9798350370249

Since human skin illnesses are among the most common dermatological conditions worldwide, visual observations are usually the first step in the diagnosis process. Accurate classification of skin biopsies and scrapings requires dermoscopic analysis and clinical screening due to medical criteria. It gets more difficult to classify skin diseases using medical photographs because of the complex forms, wide range of colors, and data security issues. In this study, we offer a dependable approach for the classification of 20 distinct types of skin illnesses, based on an improved Convolutional Neural Network (CNN) model. Our enhanced CNN design exceeds the standard CNN, which only achieves an accuracy of 31.38%, with an astounding accuracy of 98.21%. The accuracy of two benchmark algorithms, AlexNet and VGG19, is also not particularly high (32.14% and 52.30%, respectively). In contrast to traditional CNN models the enhanced CNN performs better, demonstrating its efficacy and dependability in accurately identifying a wide range of skin disorders. including well-known architectures like AlexNet and VGG19. Positive implications of this discovery include the development of more precise diagnostic tools for dermatology. © 2024 IEEE.

关键词： Benchmark Algorithms CNN Enhanced CNN Skin Disease Classification

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Evaluating Glucocorticoid Toxicity Index as a Predictor of Intestinal Adhesion Formation After Abdominal Surgery 5th

Evaluating Glucocorticoid Toxicity Index as a Predictor of I...

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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： Tyagi, Pankaj Kumar Beemkumar, N. Agarwal, Ankita Kaushik, Harshita Department of Biotechnology Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India

ISBN: (纸本)9789819780426

Stomach surgical operation can cause damage to intestinal tissue and is associated with a better risk of adhesive intestinal ailment. The main symptom of the adhesive intestinal disorder is intestinal adhesion, a continual and probably life-threatening hassle. Glucocorticoid use at the time of abdominal surgical procedures has been related to an increase in the danger of adhesive intestinal sickness. In addition to recognizing this disorder’s threat and protecting factors, the existing examination evaluated the Glucocorticoid Toxicity Index (GTI) as a predictor of intestinal adhesion formation in patients’ present process of stomach surgical operation. A prospective discussion was conducted on 220 sufferers who underwent stomach surgical treatment at an urban coaching hospital. The GTI change was measured at the time of the surgical treatment, and the patients were accompanied for one year after their surgery. The consequences of the look showed that there had been a statistically significant affiliation between higher GTI and the occurrence of postoperative intestinal adhesion after a stomach surgical operation. Moreover, the facts confirmed that there had been an additive effect of other chance factors, together with the acute inflammatory procedure or impaired wound healing, on the hazard of adhesion formation while blended with GTI. Those results propose that GTI is a dependable predictor of intestinal adhesion formation after a belly operation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Transplantation (surgical)

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