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113 articles for “Crop Monitoring”
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Profound Study on Sensors Used in Precision Agriculture
Abstract: Abstract: The basic objectives of this paper have to increase the profitability of crop production, improve product quality and protect the environment using sensors. Internet of Things has enabled the agriculture crop monitoring easy and efficient. The various types of sensors that can be used to calculate the statistical parameters of an agricultural fields and it gives a stateof-art of wireless sensor and provide solutions applied to precision agriculture (PA). …
Published in Recent Trends in Sensor Research & Technology · Vol. 6, Issue 1, 2019 · pp. 18–21 Read article
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Study of Agriculture Using Drones in India: Evaluation of Feasibility, Impact, and Adoption Challenges
Abstract: Studies in India show that drone technology is revolutionizing agriculture by enabling precision farming, increasing crop yields, reducing costs, and improving sustainability. Key applications include using drones for efficient spraying, crop monitoring via multispectral sensors, soil health analysis, and optimized water management. Government initiatives like the "Kisan Drones" program are promoting adoption, supported by research that demonstrates significant benefits like yield increases and resource savings[1-3]. Figure 1 shows the usage …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 21–33 Read article
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Technological Advancements in Agricultural Spraying Drones: A Review of Efficiency and Environmental Impact
Abstract: Developing an unmanned aircraft system with cutting-edge sensors for accurate pesticide and fertilizer delivery, crop monitoring, and resource optimization in agriculture is the main goal of the agricultural spraying drone project. The initiative intends to minimize chemical usage and lessen environmental effects while providing a sustainable and environmentally friendly alternative. Real-time monitoring, obstacle avoidance, GPS-based navigation, and data analytics are some of the key features. Airframe design, propulsion, cargo delivery, …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 1–11 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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AI and IoT for Precision Farming: Transforming Indian Agriculture
Abstract: Agriculture plays a crucial role in the global economy with the exponential rise in population. There is a parallel increase in the demand for food and employment exerting pressure on conventional farming methods. These traditional techniques are often inadequate in meeting current agricultural demands. Consequently, automation in agriculture has gained significant attention as an evolving field. The integration of artificial intelligence (AI) into agricultural processes has led to a transformative …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 7–15 Read article
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IT Enabled Sustainable Farming Using UAVs
Abstract: Drones or Unmanned Aerial Vehicles(UAVs) receiving a growing interest in media and literature not only for military and surveillance applications but also for agricultural purposes. In the recent research, we have reviewed the current state of UAVs technology and found that the most of applications are based on remotely controlled piloted observation. Now we have defined potential agricultural applications where the autonomous UAVs can have uses like monitoring crops and …
Published in Journal of Microwave Engineering and Technologies · Vol. 7, Issue 3, 2020 · pp. 24–30 Read article
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Sensor Based Data Acquisition for Smart Agriculture
Abstract: Agriculture is a vital practice for every nation, and it involves both scientific and artistic methods of cultivating plants. To keep up with technological advancements, agriculture has adopted smart techniques that heavily rely on the Internet of Things (IoT). By using sensors, IoT technology collects essential data about crops. This approach allows farmers to monitor their crops through wireless sensor networks that transmit data from various locations. Smart agriculture is …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 12, Issue 2, 2023 · pp. 18–26 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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Leveraging Artificial Intelligence for Precision Agriculture: Opportunities and Challenges
Abstract: AI in the agriculture sector is slowly changing the face of farming and the way it is practiced through enhanced precision, efficiency and sustainability. This study explores the role of AI in precision agriculture, focusing on its potential to revolutionize crop management, soil health monitoring, pest and disease control, and resource optimization. We examine the various AI technologies, including machine learning, computer vision, and robotics, that are being leveraged to …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 1, 2025 · pp. 28–40 Read article
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Host Plant Affinity and Trophic Behavior of Lohita grandis name of author (Hemiptera: Largidae)
Abstract: Lohita grandis (Gray) , commonly known as the red cotton bug, is an emerging pest of cotton and several other economically important crops in India. Its sap-sucking feeding habit causes discoloration of fruits, reduction in seed quality, and yield losses, posing serious challenges to sustainable agriculture. The present study investigates the feeding behaviour and host plant preferences of L. grandis across diverse agroclimatic zones of India, with the aim of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 92–100 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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Smart Crop Recommendation Using IoT Sensor for Precision Agriculture
Abstract: This study addresses precision agriculture, which leverages modern technologies to enhance farming efficiency and sustainability. This study proposes a Smart Crop Recommendation System using IoT sensors to optimize crop selection based on real-time environmental conditions. The system integrates multiple sensors, including a temperature sensor, flame sensor, soil sensor, moisture sensor, and LDR sensor, to monitor crucial parameters such as temperature, soil moisture, light intensity, and fire hazards. An Arduino microcontroller …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 · pp. 29–41 Read article
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Design and Implementation of a Smart Irrigation System for Efficient Water Management in Agriculture
Abstract: Water is one of the most important resources in farming, and using it wisely has become more important than ever. Traditional irrigation methods often lead to a lot of water being wasted, especially when watering is done without checking if the soil actually needs it. This project focuses on building a Smart Irrigation System that uses basic electronic components like soil moisture sensor, DC Motor, IC7805, Relay Module and a …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 13–22 Read article
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IoT in Agriculture: A Systematic Review of Smart Farming Solutions and Innovations
Abstract: This paper is based on a project titled “IoT-based smart farming. It discusses the utilization of the power of contemporary technology like sensors and cloud computing. IoT-based smart farming is revolutionizing traditional agricultural practices. This project also enables farmers to manage their farms remotely. The primary goal is to support an existing farmer and a new farmer who wants to start farming as their side income source by remote farming. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 13, Issue 2, 2023 · pp. 17–26 Read article
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Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture
Abstract: Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture" explores the convergence of cutting-edge technologies in revolutionizing traditional farming practices towards sustainability. This study investigates the integration of Internet of Things (IoT), Artificial Intelligence (AI), and Image Processing techniques in agricultural contexts, aiming to enhance efficiency, productivity, and environmental stewardship. Through a comprehensive review of recent advancements and case studies, this research elucidates the transformative potential of IoT-enabled …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 52–69 Read article
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A review on polyhouse monitoring system
Abstract: The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming practices, offering innovative solutions to enhance productivity, sustainability, and resource efficiency. This study explores the role of loT-based systems in smart agriculture, focusing on applications such as environmental monitoring, automated irrigation, crop health prediction, and precision farming. The reviewed systems utilize advanced sensors to monitor parameters like temperature, humidity, soil moisture, and light intensity, transmitting real-time …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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Microclimate Conditions Monitoring using IoT to Maximize Fruits and Vegetables Production
Abstract: AbstractTo save the production cost of the Agro fields and maximizing the economy, production and quality using automation as well as technological advancements. This paper discusses about maximizing the agro-production using control in the microclimate conditions using IIoT (Industrial Internet of Things), yield a healthier crop production with maximum profit. The method includes continuous monitoring of the farm, includes monitoring climate conditions with respect to the crop on the field …
Published in Recent Trends in Sensor Research & Technology · Vol. 4, Issue 3, 2017 · pp. 15–20 Read article
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Fungus Detection System
Abstract: This project identifies fungal pathogens in wet soil with sensors and gives an instant result through an Android app. It helps farmers avoid crop loss, increase yield, and encourage eco-friendly farming practices by enabling early detection and evidence-based decision-making for soil health management. Soil condition is most important to agriculture and environmental health. Having fungus in pre-maturity soil analysis can prevent crop damage and increase the yield. This project seeks …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 30–34 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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APPLICATIONS OF NANOTECHNOLOGY IN CROP IMPROVEMENT: NEW ERA OF AGRICULTURE
Abstract: It represents a transformative force in agriculture, promising to improve the productivity, yield, sustainability, and food security. This review paper focused on the certain advantages of nanoscience and nanotechnology in enhancing the agricultural productivity, disease management, and food safety. By manipulating different materials and objects at the nanoscale, researchers can develop advanced tools such as smart sensors and targeted delivery systems that improve nutrient absorption and combat plant pathogens. By …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 3, 2025 · pp. 46–54 Read article