Search
58 articles for “Agriculture Efficient Machine”
-
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
-
Kisan Mantra: Enhancing Farmer Productivity, A Web-Based Approach for Efficient Crop Harvesting and Problem Diagnosis
Abstract: India's agricultural sector faces persistent challenges, including limited access to expert guidance, difficulties in managing diverse datasets, unreliable weather forecasting, and a lack of real-time monitoring for farm activities and crop quality. Additionally, farm lenders struggle to obtain accurate insights into farm productivity and risks, hindering their ability to provide tailored financial solutions. The sector also grapples with underemployment among educated professionals, limiting their contributions to agricultural advancement. To tackle …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 71–87 Read article
-
Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
-
Design Of A Novel Drone For Agricultural Application
Abstract: There are several factors that determine the production rate of crops in agriculture , namely, temperature, pressure, humidity, rain, soli, climatic conditions etc. farmers have been using pesticides and fertilizersin order to increase the production rate and to prevent the crops from insects. But these pesticides have an adverse effect on the health of farmers due to prolonged exposure and in turn prove hazardous for their health. WHO (World Health …
Published in Journal of Microcontroller Engineering and Applications · Vol. 8, Issue 2, 2021 · pp. 30–39 Read article
-
Development of A Gyratory Bladed Grinding Machine for Ripe Plantain Processing
Abstract: The processing of ripe plantains faces significant challenges, including inefficient grinding and mortar pasting methods, inconsistent paste quality, and maintenance difficulties with existing equipment. This paper presents the development of a gyratory bladed grinding machine specifically for ripe plantain processing. SOLIDWORKS CAD software was applied to create the machine's CAD, or computer-aided design, model. The design analysis of the machine components was conducted, and appropriate materials were selected to accommodate …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 29–37 Read article
-
Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
-
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
-
AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
-
Myco-Engineering Systems: Harnessing Fungal Networks for Carbon Sequestration and Sustainable Ecosystem Restoration
Abstract: Fungal organisms play a foundational role in global ecosystem stability, particularly through their contributions to nutrient cycling, soil regeneration, and carbon sequestration. Recent scientific advances have highlighted the potential of fungal mycelial networks as natural bioengineered systems capable of supporting sustainable environmental restoration. This paper introduces the concept of Myco-Engineering Systems, an interdisciplinary framework that integrates fungal biology, environmental science, and artificial intelligence (AI) to enhance carbon capture and ecosystem …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 Read article
-
Myco-Engineering Systems: Harnessing Fungal Networks for Carbon Sequestration and Sustainable Ecosystem Restoration
Abstract: Fungal organisms play a foundational role in global ecosystem stability, particularly through their contributions to nutrient cycling, soil regeneration, and carbon sequestration. Recent scientific advances have highlighted the potential of fungal mycelial networks as natural bioengineered systems capable of supporting sustainable environmental restoration. This paper introduces the concept of Myco-Engineering Systems, an interdisciplinary framework that integrates fungal biology, environmental science, and artificial intelligence (AI) to enhance carbon capture and ecosystem …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 · pp. 11–22 Read article
-
Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
-
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
-
Fields of Data: Exploring AI’s Impact on Modern Farming
Abstract: The Food and Agriculture Organization (FAO) of the United Nations projects that by 2050, there will be a further 2 billion people on the planet, but just 4% of that additional land will be used for agriculture. Under such circumstances, the most recent technical developments and solutions to the farming industry’s obstacles can be used to achieve more effective farming methods. The direct implementation of machine intelligence or artificial intelligence …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 14–20 Read article
-
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
-
Revolutionizing Plant Disease Detection: A Comprehensive Review
Abstract: Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 44–55 Read article
-
Design and simulation of Solar Powered Automated Dual Rotor Mechanism for Sugarcane Harvesting
Abstract: Sugarcane being the vast cultivated cash crop of India’s agricultural economy has undoubtedly one of the most difficult harvesting processes. The existing mechanisms to harvest sugarcane are costly and are not affordable by rural based farmers. In this project a novel design mechanism is suggested that would serve the purpose of harvesting with least manpower, being cost effective and serving the purpose of cutting, stripping, sorting and loading of the …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 · pp. 18–26 Read article
-
Jowar Millet Crop Monitoring and Analysis Robot (JMAR): A Smart Solution for Plant and Soil Health in Jowar Millet Farming
Abstract: Farmers cultivating jowar millet (Sorghum) face significant challenges in maintaining crop health and optimizing yield due to the limitations of traditional plant disease detection and soil health assessment methods. Visual inspection and indigenous knowledge are labour-intensive, time-consuming, and often inaccurate, while soil monitoring requires specialized equipment that is not always affordable or accessible. These issues hinder timely intervention and can lead to crop losses and soil degradation. To address these …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
-
Machine Learning-based Peer-to-Peer Platform for Precision Agriculture in Crop Growth and Disease Monitoring
Abstract: Farmer suicides are a significant problem in India due to various circumstances. One of the main problems is the financial side of managing and growing crops while still trying to make a profit. This study proposes a decentralized platform for buying and selling agricultural produce by connecting farmers with individuals interested in investing in their fields and continuous monitoring of quality and crop health using IoT, Blockchain, and Machine Learning …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 3, 2022 · pp. 26–39 Read article
-
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
-
Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article