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513 articles for “Data-driven”
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Big Data, Big Impact: The Role of Analytics in Modern Business
Abstract: In modern business, “Big Data” signifies the vast amount of data collected from various sources, and “Big Data Analytics” refers to the process of analyzing this data to extract valuable insights, enabling companies to make data-driven decisions, optimize operations, better understand customers, and ultimately gain a competitive edge by identifying trends, patterns, and opportunities that might otherwise be missed. This study analyzes large datasets, by which businesses can gain deeper …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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ConnectED-AI: Connecting Education with Artificial Intelligence
Abstract: In a rapidly evolving educational landscape, the role of technology and artificial intelligence (AI) in enhancing learning experiences has gained immense importance. The “ConnectED-AI” project represents a pioneering effort to leverage AI to empower students with personalized and effective educational resources. This report provides an overview of the “ConnectED-AI” project, which is designed to address the diverse and dynamic learning needs of students. Our project aims to connect students with …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 36–50 Read article
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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AIducate: Your Smart Tutor–A Survey
Abstract: The ongoing “datafication” of our social reality has led directly to the emergence of new data-driven business models across various sectors, including education. As a result, the market for educational services is rapidly expanding. Educational technology (EdTech) companies are at the forefront, offering data-driven pedagogical solutions that are reshaping the landscape of learning. Despite the market's growth, few companies are harnessing the full potential of artificial intelligence (AI) and machine …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 25–30 Read article
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Strategic Integration of Machine Learning in Polymer Composite Development: A Framework for R&D Portfolio Management and Technological Adoption
Abstract: The progress of advanced polymer composites is slow, costly and unpredictable due to traditional methods of trial-and-error research. As materials informatics and data-driven modeling speed up the process of discovering technology, there exists a huge disconnect between computational predictions on one hand and strategic decision-making on the other in research and development (R&D). To solve this issue, this paper presents the Agile Materials-Intelligence (AMI) Framework, a systematic combined methodology that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1272–2286 Read article
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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Webpage Extraction and Retrieval Chatbot
Abstract: Web scraping is a fundamental technique for automating data extraction in big data applications. While multiple implementations exist, few leverage Python’s Beautiful Soup library for efficient and structured data retrieval. This project aims to develop a web scraper and retrieval system that extracts relevant information from web pages, stores it in a vector database (Milvus), and enables intelligent querying using semantic search and generative AI. The system is designed to …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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Network Security Secure Communication in Industrial Networks
Abstract: In an era dominated by rapid industrial digitization, ensuring the security of communication in industrial networks has become a critical challenge. Industrial networks, which facilitate seamless communication between machines, devices, and systems, are increasingly targeted by cyber threats that can disrupt operations, compromise sensitive data, and jeopardize safety. This article delves into the key aspects of secure communication in industrial networks, emphasizing the role of advanced encryption techniques, robust authentication …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 1–8 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Leveraging Information Technologies (IoT, Sensor Technologies, AI, and Data Analytics) in Healthcare and Agriculture
Abstract: This paper explores the powerful convergence of digital technologies — the Internet of Things (IoT), Sensor Technologies, Artificial Intelligence (AI), and Data Analytics — in transforming healthcare and agriculture. Both sectors face pressing global challenges: rising population demands, environmental stress, disease burdens, unequal access to services, and food insecurity. Conventional systems alone cannot meet future needs. However, technology-driven, real-time data-driven systems offer innovative solutions: from automating diagnostics to forecasting pest …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 20–28 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Digital Agriculture Schemes in Kerala: Risk Analysis and Multi-Layered Security Framework
Abstract: Kerala’s agricultural sector is undergoing rapid digital transformation, driven by initiatives such as the e-Krishi platform and the growing adoption of Internet of Things (IoT)–enabled precision farming technologies. While these developments promise improved productivity, transparency, and data-driven decision-making, they also introduce significant cybersecurity and data governance challenges that cannot be overlooked. This paper critically examines the emerging security, privacy, and operational risks associated with the digitization of agricultural services in …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 23–30 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Artificial Intelligence Techniques for Image Dehazing: A Review
Abstract: This review explores the application of artificial intelligence (AI) techniques for image dehazing, addressing the pervasive challenge of enhancing image quality in hazy or foggy conditions. Traditional dehazing methods and their role as a foundation for AI-based approaches are discussed. Deep learning-based methods, including single-image and multi-image dehazing, are examined, highlighting their strengths and limitations. Data-driven approaches, leveraging large-scale datasets and domain adaptation, are also investigated. Furthermore, the review outlines …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 26–30 Read article