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44 articles for “Forest Monitoring”
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Forest Fire Early Detection and Online Remote Monitoring Using Sensors
Abstract: Forest fire device networks represent a strong technology, particularly appropriate for environmental observation. With relation to wildfires, above all, they permit low-priced police work of venturesome locations like wild land urban interfaces. This report presents the work developed throughout the last 4 years targeting a fire device network node for the reliable, on-site detection of forest fires. The tasks dispensed ranged from detective work or sensing of conditions that rise …
Published in Journal of Industrial Safety Engineering · Vol. 9, Issue 1, 2022 · pp. 16–20 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Monitoring and Controlling System of COVID-19 Symptoms Using Random Forest
Abstract: Corona virus (COVID-19) has already claimed hundreds of lives and infected millions of people around the world. The early detection of COVID-19 is shown in this paper. Machine learning random forest techniques were used to implement the detection procedure on cloud computing. Objectives of the study is to provide health assurance directly from home using some smart tools with cloud computing. Our research contribute the categorization of patients into different …
Published in Research and Reviews : Journal of Computational Biology · Vol. 11, Issue 1, 2022 · pp. 22–29 Read article
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Automatic Flame Detection and Tracking
Abstract: Recent advancements in independent robotics, embedded systems, and intelligent perception have appreciably improved the capability of firefighting robots designed for early fire detection, flame localization, and suppression. A broad range of studies explores vision-based and sensor-fusion techniques designed for reliable flame discovery in complex environments. Image-processing approaches—including adaptive edge-detection, infrared/thermal imaging, color-space analysis, and profound learning—are extensively implement to enhance real-time fire gratitude, even in the presence of smoke or …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 6–12 Read article
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Crop Health Monitoring and Weed Detection Using Drone Technology
Abstract: In an agriculture-based economy like ours, farmers and their cultivation play a significant role. With the extension of agriculture to wider fields, manual interference to monitor and detect crop health is becoming more difficult. Unmanned aerial vehicles (UAVs) have become well-known and affordable technology for a variety of precision farm uses in recent years. Combining the capabilities of drone technology and machine learning/deep learning algorithms, we can monitor crop health …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 1–8 Read article
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Comparative Study of Change Detection Methods in High Resolution Images
Abstract: Natural phenomena including weathering, erosion, volcanic eruptions, and plate tectonics, as well as human activities like agriculture, deforestation, and urbanization, cause the Earth's surface to change continuously. In many different applications, such as environmental monitoring, disaster management, urban planning, agriculture and forestry, climate change studies, resource management, and infrastructure monitoring, it may be extremely beneficial to detect and track these changes. There are various algorithms and methods proposed by many …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 1–5 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Forest Fire Detection System
Abstract: The IOT industry is rapidly growing in the current scenario. Each one of us now understands the significance of Internet of Things. At present, it is being used in almost all industries making our lives a bit easier. Forest fires have become a massive threat across the globe, causing numerous negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are among the consequences of such …
Published in Journal of VLSI Design Tools and Technology · Vol. 13, Issue 1, 2023 · pp. 1–5 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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Comparative Study of Classifiers for Monitoring Fake Reviews of Online Products Using Opinion Mining
Abstract: With the increasing popularity of e-commerce, online dealers seek reviews or opinions from customers regarding the quality and service of their sold products. As the number of customer reviews grows rapidly, potential buyers face difficulties in reading and assessing them to make informed decisions. Unfortunately, some review websites include fake positive reviews, either added by the product companies themselves or submitted by users who have not made a purchase. This …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 52–59 Read article
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Animal/Object Recognition and Monitoring
Abstract: This study focuses on teaching a computer to identify leopards in images through a process called Object Detection and Image Recognition. We created a special set of pictures (dataset) containing thousands of leopard images. Using a small camera module called ESP32 CAM, we trained the computer to recognize leopards by comparing the images it captures with the ones in the dataset. The results were obtained using a Convolutional Neural Network …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article
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Meanings from Ground Truth: A Related Affair to Consume
Abstract: Ground truth (GT) ever forms in three dimensional by eye. Similarities by instrumentations have subjected to perform by binocular stereopsis visions. Net visionary has descriptive issued to nodal communicating commands to subscribe communal. Linking messengers may be containment of any arena inform like nodal clusters of vector data to as form metadata to correspond selective issues. This has subjectively called planted data or synthetic communal data. Estimation of prompt informs …
Published in Journal of Mechatronics and Automation · Vol. 7, Issue 1, 2020 · pp. 17–23 Read article
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Identifying and Blocking of Non-productive Calls in Emergency Call System Using Machine Learning and IVRS Integration
Abstract: The Dial 100 emergency reaction gadget handles over 1,000,000 calls every day, with over 95% being unproductive, such as blank, machine-generated, and spoofed calls. These futile calls waste resources and put off responses to actual emergencies. This look presents a comprehensive solution integrating advanced name evaluation, system learning, and an interactive voice response system (IVRS) to filter out and prevent these calls. Our technique starts with studying incoming calls to …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 20–28 Read article
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Understanding the Role of Remote Sensing Techniques in Monitoring Air Quality for Effective Adherence to Environmental Impact Assessment Practices in Nigeria
Abstract: The paper reviews the Nigerian Environmental Impact Assessment (EIA) Act, outlining the established air quality thresholds and emission caps for stationary sources. The standard applies to; common pollutants like sulphur dioxide, carbon monoxide, ozone, particulate matter and nitrogen oxides; toxic metals such as arsenic, nickel, cadmium and mercury; as well as volatile organic compounds, ammonia, antimony, zinc, formaldehyde and radon.It also describes the major classifications of remote sensing applications, including …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Data-Driven Machine Learning Approach for Vehicle Fuel Economy Prediction and Performance Monitoring Using Real-World OBD Data
Abstract: Modern passenger vehicles generate large volumes of operational data through On-Board Diagnostics (OBD) systems, enabling continuous observation of vehicle performance under real-world driving conditions. However, much of the existing research mainly analyses previously recorded data and does not provide predictive mechanisms for monitoring vehicle performance under dynamically varying operating conditions. This study presents an AI and machine learning–based method for predicting and monitoring real-world vehicle performance and fuel economy using …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 47–66 Read article
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Nanotechnology and Nanoparticles for High Altitude Agro-ecosystem and Environmental Sustainability
Abstract: High-altitude agro-ecosystems are widely distributed throughout the world. In the Indian subcontinent, Himalayan region represents the high-altitude ecosystems, which demand extensive management due to their increasing deterioration in recent times. The extremely low temperature, proneness to natural calamities, recurring floods, droughts, low soil moisture and fertility, high solar intensity impose constraints for sustenance of hill agriculture. To enhance crop productivity to sustain increasing population, hill farmers are using excessive amount …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 155–164 Read article