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1089 articles for “data modelling”
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 Read article
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Harnessing the Growth Potential of Cloud Computing in Agriculture
Abstract: Unlocking the Green Revolution: A Comprehensive Exploration of Cloud Computing Integration in India's Agricultural Landscape. The integration of cloud computing technology in the agricultural sectors of India is poised to play a pivotal role in propelling the nation's holistic development. This paper delves into the dynamic realm of cloud computing, serving as a catalyst for innovation and efficiency in agriculture. By eliminating the need for maintaining expensive computing infrastructure, cloud …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 32–37 Read article
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article
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Adoption of Major Improved Crop Varieties in Selected Districts of the Southwest Ethiopia Region
Abstract: Agriculture forms the backbone of the Ethiopian economy and significantly contributes to the livelihoods of the majority of the population. It remains a central pillar of food security, employment, and rural development across the country.The present study aims to examine the adoption of improved major crop varieties and to identify the key factors influencing their uptake in the southwest Ethiopia region. The research was carried out in the districts of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 18–31 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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AquaSential: Autonomous UAV-Based Water Quality Monitoring System
Abstract: The increasing occurrence of waterborne health risks and the presence of harmful microorganisms in freshwater environments highlight the need for rapid and continuous water quality monitoring. Traditional laboratory-based testing methods often require significant time and manual sampling, limiting their ability to provide immediate information about changing environmental conditions. This work presents AquaSential, a low-cost, portable, and UAV-ready water quality monitoring system designed for real-time assessment of freshwater bodies. The proposed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Emotions and Artificial Intelligence in Finance: Exploring the Relationship
Abstract: The integration of Artificial Intelligence (AI) into financial systems has profoundly transformed the industry, providing unprecedented efficiency, accuracy, and speed in decision-making processes. These technological advancements have streamlined operations, reduced human errors, and enabled more informed decision-making based on vast datasets analyzed in real-time. However, the role of emotions in finance remains a critical factor that cannot be ignored. Human emotions, such as fear, greed, and optimism, frequently drive market …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 11–17 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article
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Internet of Things in Smart Grid: Applications, challenges, Conditions, Architecture- A Review
Abstract: Future-generation intelligent optimisation in electrical system design is essential for managing electrical networks and distribution systems. It also requires interoperability variations in the implementation of physical or graphical models. The Internet of Things (IoT) plays a significant role in smart grids and distributed electricity systems. IoT enables the monitoring of the smart grid's electrical energy and facilitates the integration of real-time data into electrical grid architecture at various levels. Industrial …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 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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AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
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A Descriptive study to assess the prevalence of Nomophobia among Nursing students in Chirayu College of Nursing Bhopal (MP).
Abstract: Nomophobia, defined as the fear or anxiety of being without access to a mobile phone, has emerged as a growing behavioral concern in the digital age, particularly among young adults. Nursing students are especially vulnerable due to their extensive reliance on smartphones for academic, clinical, and social purposes. The present descriptive study was conducted to assess the prevalence of nomophobia among nursing students at Chirayu College of Nursing, Bhopal (Madhya …
Published in Journal of Nursing Science & Practice · Vol. 16, Issue 1, 2026 · pp. 36–41 Read article
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Automating time based Household electricity Bill Calculations for Efficient Budgeting
Abstract: Recurrent household expenses must be precisely, in time, and openly tracked to make efficient household budgeting. Conventional monthly billing performance tends to delay the financial information, which results in the inefficient cash flow management and inability to modify short-term expenditure patterns. The proposed research is a system to automatize the calculation of household bills per week in order to deliver more frequent and practical insights into the household spending habits. …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 1–16 Read article
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Modelling, Simulation & Optimization of Renewable Energy-Based Hybrid Microgrid for Electrification of Rural Areas
Abstract: Rural electrification in India faces persistent challenges due to unreliable grid connectivity, elevated transmission and distribution costs, and the geographical isolation of remote communities. Insufficient access to reliable electricity constrains economic development, educational opportunities, healthcare delivery, and overall quality of life in these areas. This study details the design and simulation of an off-grid, renewable-based hybrid micro grid for two rural villages: Khirgitola in Chhattisgarh, which has an electrification rate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1206–1218 Read article
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Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms
Abstract: Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 341–366 Read article
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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Unified Mass–Energy Dissolution Cosmology (UMEDC): A Staged Framework for Cosmic Energy Transformation and Late-Time Acceleration
Abstract: The ΛCDM model successfully describes the universe’s expansion but remains fundamentally descriptive: it assigns fixed densities to matter, dark matter, and dark energy without providing a unifying physical mechanism behind their coexistence or evolution. In this work, we introduce the Unified Mass–Energy Dissolution Cosmology (UMEDC), a novel framework based on the staged transformation M → DM → DE, where ordinary matter gradually dissolves into a dark-matter-like reservoir, which subsequently transforms …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 18–34 Read article
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Hybrid Intelligence in Cyber Security: A Study
Abstract: The digital landscape is a battlefield of escalating complexity, where the volume, velocity, and sophistication of cyber threats have exponentially outpaced human-centric defense models. Traditional rule-based security systems and siloed artificial intelligence (AI) solutions, while valuable, are increasingly brittle, overwhelmed by zero-day exploits, polymorphic malware, and coordinated, state-sponsored campaigns that operate in the shadows of big data. This paper posits that the paradigm of cybersecurity must fundamentally shift from one …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article