Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

34 articles for “Challenges in IoT”
Set a search alert
Also matching:6 special issues
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 abstractAn Optimized Multi-Layer Perceptron Framework for Detecting and Classifying IoT AttacksSanchit Vashisht, Shalli RaniThe Internet of Things (IoT) is revolutionizing industries by connecting billions of smart devices, enabling automation and information exchange. The expansion of IoT ecosystems has simultaneously increased the surface area for cyberattacks. These environments are particularly vulnerable to a wide range of threats, such as Distributed Denial-of-Service (DDoS), poisoning, brute-force SSH intrusions, and various network reconnaissance techniques. The dynamic nature … …Journal of Computer Science, Vol. 21, Issue 12 · 11 Feb 2026 · 1,333 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractLatent Feature-Based Trust-Aware Model for Service Delegation in Social Internet of Things (SIoT)Rahul, Venkatesh, Satish B BasapurThe integration of social networking concepts into the Internet of Things (IoT) paradigm has given rise to Social IoT (SIoT) ecosystems, aiming to address challenges related to network navigation, service discovery, and service composition. A fundamental issue in SIoT is the careful selection of trustworthy devices that provide services. A service provider can offer multiple and diverse services, and different … …Journal of Computer Science, Vol. 21, Issue 12 · 9 Jan 2026 · 1,802 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 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 abstractHybrid Optimization to Trust Enhanced Secure Routing Optimization with IABC and CGWAA for MANETYuvaraja Panneer Selvam, Suganthi PerumalRouting in Mobile Ad Hoc Networks (MANET) presents significant challenges due to the dynamic nature of network topology. Optimal route selection and efficient route discovery are matched by effective routing in MANET. This study proposes a Hybrid Optimization to Trust-Enhanced Secure Routing Optimization (HO-TESRO) designed to address these challenges in IoT environments by integrating metrics such as link stability, bandwidth, … …Journal of Computer Science, Vol. 21, Issue 4 · 19 Mar 2025 · 4,983 accessesView PDFCite
Research ArticleOpen accessIn the abstractSustainability 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
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Holistic Approach to Security, Availability and Reliability in Fog ComputingAbdulrahman Alshehri, Hazzaa Alshareef, Samah Alhazmi et al.Abdulkareem, K. H., Mohammed, M. A., Gunasekaran, S. S., Al-Mhiqani, M. N., Mutlag, A. A., Mostafa, S. A., Ali, N. S., & Ibrahim, D. A. (2019). A Review of Fog Computing and Machine Learning: Concepts, Applications, Challenges, and Open Issues. IEEE Access, 7, 153123–153140. https://doi.org/10.1109/access.2019.2947542 Alrawais, A., Alhothaily, A., Hu, C., & Cheng, X. (2017). Fog Computing for the Internet … …Journal of Computer Science, Vol. 20, Issue 6 · 20 Mar 2024 · 6,372 accessesView PDFCite