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46 articles for “agricultural automation precision agriculture”
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Intelligent Farming: Integrating AI and IoT for Sustainable Agriculture
Abstract: Artificial Intelligence (AI) and the Internet of Things (IoT) are transforming modern agriculture by enabling data-driven, resource-efficient, and climate-resilient farming practices. This review critically examines recent advances in AI-IoT integration across crop production, irrigation management, pest and disease surveillance, and supply chain optimization through an analysis of published literature and documented case studies. The review indicates that AI-assisted predictive analytics combined with IoT-based real-time sensing significantly improves decision-making in precision …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 Read article
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Innovative Technologies for Sustainable Dairy Development: Implications for Improved Efficiency, Resource Utilization and Environmental Footprints
Abstract: This study explores innovative technologies in dairy farming aimed at enhancing sustainability through improved efficiency, optimized resource utilization, and reduced environmental footprints. As global demand for dairy products increases, the need for sustainable practices has become paramount, particularly in regions where agricultural systems face environmental and resource constraints. The paper examines a range of cutting- edge technologies, including precision feeding systems, genomic selection, automated health monitoring, and waste management solutions. …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 Read article
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Next-Gen Agriculture: Deep Learning Algorithms for Real-Time Plant Disease Detection via IoT
Abstract: In addition to providing high-quality food, the agriculture industry plays a critical role in supporting expanding people and economies. Plant diseases can have a detrimental effect on biodiversity and result in significant losses in food production. Automated methods for early and precise identification of plant diseases can reduce financial losses and enhance the quality of food produced. Deep learning has significantly improved object detection and picture classification accuracy in recent …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 1, 2024 · pp. 18–23 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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IoT Based Weather Monitoring System
Abstract: The Internet of Things (IoT)-Based Weather Monitoring System is developed to provide accurate, real- time monitoring of essential environmental parameters, including temperature, humidity, and atmospheric pressure. The system integrates high-precision sensors with a microcontroller, enabling continuous data acquisition from the surrounding environment. Collected data is transmitted wirelessly to a dedicated IoT platform via an internet connection, allowing remote users to access and visualize the information through web or mobile interfaces. …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 26–34 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Comparative FEA Study of Robotic Arms Under Diverse Loading Scenarios
Abstract: The introduction of robotic arms into the industrial and research fields has transformed efficiency, precision, and productivity in a multiplicity of industries. Automating material handling and sorting, among others, the robotic system has optimized operations that enable industries to produce well above the required standards even though there is an enhanced increase in demand, reduces costs, and human labor. Robotic arms find widespread application in manufacturing, medical procedures, and in …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 3, 2024 · pp. 24–32 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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The Future of Farming with IoT-Operated Drones
Abstract: The integration of Internet of Things (IoT) technology with drone systems has revolutionized precision agriculture, offering innovative solutions to address the inefficiencies and environmental concerns linked to conventional pesticide application. This study explores the design, implementation, and impact of IoT-operated drones tailored for automated pesticide spraying. By leveraging real-time sensor data, AI-driven analytics, and cloud-based connectivity, these drones enable dynamic, data-informed decisions to optimize chemical application. Results indicate that IoT-enabled …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 20–26 Read article
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Automatic Seed Planting Using a Controller
Abstract: Agriculture is a critical sector that requires continuous innovation to meet the increasing global demand for food. Traditional seed planting methods often involve labor-intensive processes that are time-consuming and prone to inefficiencies. This project presents an automatic seed planting machine that integrates ESP32 microcontroller technology with various sensors and actuators to enhance the precision, speed, and efficiency of seed planting. The system is designed to automate seed dispensing, soil digging, …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 1–8 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 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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The Role of Precision Agriculture in Enhancing Horticultural Crop Yields
Abstract: This article explores the quantification of lithium and mapping of mineral composition in crushed lithium ore utilizing two distinct calibration techniques with Laser-Induced Breakdown Spectroscopy (LIBS). Thirty samples from a pegmatite lithium deposit were analyzed, with representative mineral samples extracted, mixed with resin, and polished into disks. These disks underwent examination via an analyzer and an integrated mineral analyzer, facilitating mineral identification. The first calibration technique used empirical mineral chemistry …
Published in International Journal of Trends in Horticulture · Vol. 1, Issue 1, 2024 · pp. 18–23 Read article
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A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article
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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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IoT and Sensor Technologies: Pioneering Smart Agriculture for a Sustainable Future
Abstract: Smart agriculture provides creative answers to important global problems including resource efficiency, environmental sustainability, and food security. It improves agricultural yields, reduces waste, and optimizes farming operations by combining technologies like IoT, AI, and big data. This strategy ensures dependable food supply for a growing population while minimizing environmental damage and promoting sustainable development. In addition to solving the problems facing agriculture now, smart agriculture opens the door to a …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 1–8 Read article
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Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
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IoT-Enabled Sustainable Development: Architectures, Applications, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) has developed into a powerful technology that can help tackle key global sustainability issues by enabling real-time monitoring, supporting data-based decisions, and facilitating smart automation. By interconnecting physical devices, sensors, and communication networks, IoT enables continuous data collection and analysis that supports efficient resource utilization across multiple sectors such as energy, agriculture, water management, transportation, and urban infrastructure. Through smart sensing and automated control systems, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Sensor and IoT centered Smart Agriculture by NodeMCU
Abstract: A style of farming that makes use of technology and data to maximize the throughput and efficiency of farming techniques is stated to as smart agriculture. This method of farming is also often referred to as precision farming or digital farming. The fact that this invention in the agricultural sector has the impending to radically transmute how users cultivate and produce food makes it an extremely hopeful and exciting development. …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 3, 2024 · pp. 24–32 Read article