5G-Powered Industrial Automation: Opportunities and Challenges

Port automation equipment: current developments, challenges, and future directions

Port automation has progressed from standalone mechanical devices to interconnected, data-driven systems that support global trade. This paper examines how port automation has grown, focusing on equipment systems such as quay cranes, Automated Guided Vehicles (AGVs), and Automated Stacking Cranes (ASCs) and other automated yard equipment. Early improvements boosted lifting capacity and reduced manual effort, while newer approaches integrate artificial intelligence (AI), Internet of Things (IoT) sensors, and digital twin simulations to coordinate equipment in real time. These advances have raised efficiency, lowered emissions, and improved safety. However, some obstacles remain. Port managers must solve cooperation challenges, data protocol differences, and cybersecurity risks. Research indicates that advanced autonomy, including reinforcement learning, dynamic scheduling, and AI-based condition monitoring, will be important to solve these problems. The sector also needs to make standards, which ensure that equipment from different managers can communicate easily. Advances in electrification and energy management can help achieve sustainability targets, including reduced carbon footprints and optimized resource consumption. By examining a combined bibliometric analysis, qualitative content coding, and term-frequency analysis, this study reviews current progress and outlines future directions and emphasizes solutions that account for technical, organizational, and social factors. This approach may help modern ports remain adaptable, reliable, and resilient in a rapidly shifting maritime environment.

Future Generation Computer

Integration of Smart Sensors in Next-Generation Engineering Systems

Results demonstrate that smart sensor-based systems outperform conventional sensing systems in efficiency, fault detection, responsiveness, energy savings, and data accuracy, making them a key enabler of Industry 4.0 and future autonomous engineering applications.

5G Deployment in Modern Digital Ecosystems: Practical Implementation, Key Bottlenecks, and Emerging Paradigms

The evolution of wireless communication has significantly transformed the way information is generated, transmitted, and processed across various sectors. As the demand for high-speed, low-latency, and highly reliable communication continues to increase, Fifth Generation (5G) wireless technology has emerged as a key enabler of the future information era. Unlike previous generations of mobile communication, 5G offers enhanced mobile broadband, ultra-reliable low-latency communication, and massive machine-type communication, enabling seamless connectivity among billions of interconnected devices. These capabilities support the rapid growth of emerging technologies, including the Internet of Things (IoT) and Artificial Intelligence (AI) cloud computing, edge computing, autonomous transportation, Industry 4.0, smart healthcare, and smart city infrastructures. Despite its numerous Despite these benefits, several challenges persist, including the high costs associated with implementation, cybersecurity threats, spectrum scarcity, interoperability issues, energy consumption, and privacy concerns. This paper presents a comprehensive review of 5G technology and its applications in the future information era. It discusses the architecture of 5G networks, analyzes major application domains, examines current technical and economic challenges, identifies existing research gaps, and explores future research directions. The study concludes that although 5G provides the technological foundation for next-generation digital transformation, continued research is required to improve network security, intelligent resource allocation, sustainable deployment, and integration with future sixth-generation (6G) communication systems.

6HRRT: 6TiSCH Scheduling for Supporting Highly-Reliable Real-Time Mobile IoT Applications

The landscape of industrial communication systems is rapidly evolving, driven by the proliferation of Industrial IoT (IIoT) devices, increased automation, and the convergence of operational and information technologies. This evolution introduces greater complexity, with diverse requirements in latency, reliability, scalability, and mobility, calling for advanced planning and decision-support tools. In this work, we address the needs of IIoT applications requiring ultra-reliable low-latency communication and mobility support. Instead of relying on 5G ultra-reliable low-latency communications (URLLC), we thoroughly investigate an alternative option, less covered in the existing literature, based on the IETF 6TiSCH architecture and short-range communications. In particular, we propose Highly-Reliable Real-Time Scheduling for 6TiSCH (6HRRT), a novel algorithm designed for mobile IIoT scenarios. By combining intelligent resource allocation with optimized redundancy strategies, 6HRRT achieves reliability up to 99.999% and latencies of tens of milliseconds for applications with heterogeneous requirements. Simulation results show that 6HRRT consistently outperforms state-of-the-art 6TiSCH solutions, particularly under mixed workloads and stringent requirements, ensuring robust real-time performance in IIoT environments.

Smart Manufacturing Systems Using IoT and Automation

Smart Manufacturing Systems (SMS) is the paradigm shift in the contemporary industrial manufacturing that can unite Internet of Things (IoT) technologies, automation, cyber-physical systems, and data-driven intelligence to improve efficiency, flexibility, qualities, and sustainability. Conventional manufacturing systems tend to be inhibited by fixed production lines, reduced real-time visibility, and fixed manual decision making systems. With the advent of Industry 4.0, manufacturers can now use the interconnected and intelligent systems that can operate autonomously, preventive maintenance, adaptive control and optimize the use of the resources. The current paper is a detailed analysis of smart manufacturing systems that utilize the IoT and automation technology. It examines the architectural solutions, it is allowing technology, communication protocol, data analytics, and automation solutions that all constitute smart factories. Through an extensive literature review, recent developments, issues, and research gaps in the context of IoT based manufacturing setting are pointed at. The methodology suggests an integrated smart manufacturing model that will integrate sensor networks, edge and cloud computing, industrial automation, and machine intelligence. Performance evaluation measures are addressed in detail like production efficiency, downtime, reduction, system optimization in energy and scalability of the system. The findings indicate a high improvement in operational performance, predictive accuracy, and decision-making ability when compared to the traditional manufacturing system. The paper ends with a statement of future research directions, which are autonomous manufacturing with artificial intelligence, digital twins, and secure industrial IoT ecosystems.