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77 articles for “Real-Time Monitoring”
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Research ArticleOpen accessIn the abstractDesign and Implementation of a Smart File Cabinet System With Enhanced Security and Remote AccessAdebayo Afeez Oluwagbenga, Mustapha Favour, Adebiyi Temidayo Daniel et al.In an era increasingly defined by digital interconnectivity, the physical security of sensitive hard-copy documents remains a persistent vulnerability in organizational infrastructure. Traditional filing cabinets, relying on passive mechanical locks, lack the capability for real-time monitoring, remote access control, or active intrusion detection. This research presents the design and validation of a Smart File Cabinet (SFC) system that bridges this … …Journal of Mechatronics and Robotics, Vol. 10, Issue 1 · 25 May 2026 · 1,696 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation and Performance Evaluation of YOLOv8 for Wheat Fungal Disease DetectionShivani Sood, Shallu Duggal, Monika Sethi et al.Among the many difficulties in producing wheat, a vital food source for the world, there are biotic variables like fungal diseases, which drastically lower crop output. Around the world, biotrophic fungi particularly, leaf rust, powdery mildew, and yellow rusts-have become a constant threat to wheat production. Traditional methods of identification and mitigation are labor-intensive, slow, and imprecise, limiting therefore early … …Journal of Computer Science, Vol. 22, Issue 4 · 2 May 2026 · 1,599 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 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 abstractDesign and Implementation of an IoT-Based Application for Export-Import (EXIM) Document ManagementJulia Loisa, Johanes Fernandes Andry, Devi Yurisca Bernanda et al.International trade in the Export-Import (EXIM) sector is a key driver of global economic growth. However, EXIM document management still faces challenges such as data inconsistencies, input delays, and a lack of real-time visibility into document status. These issues result in shipping delays and increase operational costs. This research aims to develop an Internet of Things (IoT)-based EXIM application with … …Journal of Computer Science, Vol. 22, Issue 2 · 18 Feb 2026 · 1,854 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements 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 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 abstractAssessing 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 abstractSM-SCAM YOLO: Enhancing Object Detection with Multi-Scale Module and Spatial Channel Attention MechanismShanmuga Sundari Mariyappan, Kayalvizhi Mohan, K. B. K. S. DurgaDetecting tiny objects remains a significant hurdle in computer vision, primarily due to scale variation, occlusion, and the loss of detail in low-resolution features. Although YOLO-based detectors are popular for their speed and efficiency in real-time tasks, they often struggle with accurately identifying small objects because of information loss during downsampling. This study introduces an improved YOLO-based model that integrates … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,921 accessesView PDFCite