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17 results for “IoT-Based Agriculture”
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Research ArticleOpen accessEvery word in the titleAssessing the Usability of IoT-Based Smart Farming for Sustainable Organic AgricultureArisaphat Suttidee, Pankom Sriboonlue, Sompoch Tongnamtiang, Varitha LakkhamThis study evaluates the usability of an IoT-based smart farming system developed to support organic agriculture in Thailand. Many small-scale farmers still spend considerable time manually monitoring soil conditions and managing irrigation, often without access to practical technology. This slows farm operations and makes efficient water use more difficult. To address these challenges, the system was designed with wireless soil-moisture … …Journal of Computer Science, Vol. 21, Issue 10 · 7 Dec 2025 · 3,390 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSustainability Through Connectivity: IoT Influence on AgricultureManmohan Singh, Shaheen Ayyub, Dharmendra Sharma et al.Today’s smart farming has ushered in a new era of agriculture, one where information and communication technologies seamlessly integrate with the latest equipment in machinery and sensors based in high-tech farming systems. This transformative shift is driven by the latest technologies notably the IoT and cloud computing which are poised to revolutionize farming practices by introducing robots using artificial intelligence … …Journal of Computer Science, Vol. 21, Issue 1 · 10 Dec 2024 · 5,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-FOM: A Unified Multimodal Deep Learning Framework for Intelligent Pre-Harvest Papaya Classification and Crop ValorisationSovers Singh Bisht, Sanjeev Thakur, Sanjeev PanwarIntelligent pre-harvest crop assessment has become an essential component of precision agriculture, where accurate crop quality evaluation enables informed decision-making and sustainable crop management. However, existing multimodal frameworks often exhibit limited data diversity and insufficient cross-modal semantic interaction, reducing the reliability of intelligent crop valorisation. Address these limitations, this paper proposes a Multimodal Focal-Mamba Optimized Valorisation Model (Multi-FOM), a unified … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 670 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning AlgorithmsPalash Gourshettiwar, K. T. V. ReddyHydroponics, an efficient cultivation method, benefits significantly from the precision and adaptability that Machine Learning (ML) algorithms can offer, along with the real-time monitoring facilitated by the devices using the Internet of Things (IoT). This study summarises the latest research and discusses how Machine Learning and the IoT work together, focusing on nutrient optimization, plant development, and resource efficiency. The … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 3,046 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,772 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomating Paddy Crop Disease Classification With Deep Learning ModelsShiva Shankar J, S. Palanivel, S. China VenkateswarluRice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Agriculture and modern farming is one of the fields where IoT and automation can have a … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 5,696 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Comprehensive Survey on Applications, Challenges, Threats and Solutions in IoT Environment and ArchitectureSadia Waheed, Savera Hanif, Rubab Hafeez et al.The influence of the Internet of Things (IoT) on how people live, interact and conduct business has rapidly increased. Integrating physical objects with electronic networking, or the Internet of Things (IoT), allows for better communication and environment detection. In coming years, higher service levels will be offered by IoT-based technologies, remarkably changing how people would conduct their daily lives. Currently, … …Journal of Computer Science, Vol. 20, Issue 3 · 30 Jan 2024 · 7,261 accessesView PDFCite
Research ArticleOpen accessIn the abstractDelay-Conscious Service Quality Constraint in IoT Sensor Networks for Smart FarmingZatin Gupta, Amit Kumar BindalThe Internet of Things (IoT) offers different services for the agriculture industry, such as monitoring and analysing real-time data related to current weather conditions, water level, irrigation requirements, growth of plant disease and health status/temperature/humidity, etc.,). The performance of IoT networks may vary due to environmental conditions and operational areas (rural area/urban area/underwater). These constraints may degrade the transmission quality … …Journal of Computer Science, Vol. 19, Issue 8 · 9 Aug 2023 · 5,385 accessesView PDFCite