Impact of 5G Connectivity on Industrial Automation and Smart Factories

2026-02-02T11:40:43+00:00

The rapid evolution of industrial automation and the emergence of smart factories have placed unprecedented demands on communication networks, requiring ultra-low latency, high reliability, and massive device connectivity. This paper investigates the role of 5G connectivity as a catalyst for the next generation of industrial automation, particularly within the context of Industry 5.0, where human-centric, resilient, and highly connected manufacturing systems are emphasized. By combining a comprehensive literature review, detailed case analyses of two smart factory pilots, and semi-structured interviews with industry experts and network engineers, the study examines the core enabling features of 5G, including ultra-reliable low-latency communications (URLLC), enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and network slicing. The findings demonstrate that 5G significantly enhances industrial operations by reducing latency from approximately 20 milliseconds (Wi-Fi) to around 1 millisecond, supporting high-bandwidth applications exceeding 200 Mbps, and providing reliable, deterministic communication across densely connected devices. These improvements facilitate real-time robotic control, collaborative human-machine interaction, augmented reality-assisted training, predictive maintenance, and high-resolution process monitoring. The study also identifies persistent challenges, including integration with legacy industrial control systems (ICS) and operational technology (OT), network slicing management, cybersecurity vulnerabilities, and regulatory compliance. Based on these insights, the paper provides a roadmap for 5G adoption in industrial settings, emphasizing best practices for deployment, integration, and operational optimization. Furthermore, it highlights key avenues for future research, including the development of secure and adaptive network management frameworks, advanced integration of edge computing, and strategies to ensure interoperability with existing industrial infrastructures. Overall, this study highlights the transformative potential of 5G in enabling highly responsive, flexible, and resilient smart factories, while providing a structured framework to guide industrial stakeholders in effectively leveraging 5G technologies.

Design and Implementation of an AI-powered CT Scan Report Analyzer for Web and Mobile Platforms

2026-03-07T04:32:28+00:00

Brain tumors are one of the most life-threatening neurological disorders, requiring early and accurate diagnosis for effective treatment planning. Computed tomography (CT) remains one of the most reliable and widely accessible imaging modalities for brain screening, especially in emergency and resource-limited healthcare settings. However, manual interpretation of CT images is highly subjective and prone to variability among radiologists, leading to delays in diagnosis and potential misclassification of tumor regions. This paper presents a highly scalable, intelligent, and explainable AI-based CT scan analyzer (Web/App) that leverages hybrid deep learning and modern web technologies for automated tumor detection and visualization. The proposed system combines three major deep learning paradigms—Convolutional neural networks (CNN) for spatial feature extraction, genetic algorithm (GA) for feature selection and optimization, and bidirectional long short-term memory (BiLSTM) for temporal and contextual classification. The model is deployed via a ReactJS frontend and a Flask-TensorFlow backend, creating a responsive web application capable of real-time inference, visualization through Grad-CAM heatmaps, and secure data handling via MongoDB. This study consolidates literature between 2022 and 2025 and discusses the methodology, architecture, explainability, deployment, and clinical implications of integrating hybrid AI systems in radiological diagnostics.

International Journal of Internet of Things and Smart Computing Environment

Impact of 5G Connectivity on Industrial Automation and Smart Factories

Design and Implementation of an AI-powered CT Scan Report Analyzer for Web and Mobile Platforms