Structural Analysis of Tunnel using FEA

Tunnels are typically built for transportation, such as roads, railways, or canals, but they can also be used for other purposes, such as mining, sewerage, or water supply. Tunnels allow us to travel safely and efficiently through difficult terrain, and they provide us with access to essential resources such as water and energy. The objective of current research is to evaluate the structural characteristics of tunnel structure under geo-mechanical loading conditions. The structural analysis of tunnel is conducted using techniques of FEA. The CAD modelling and FEA simulation of tunnel is conducted using ANSYS simulation package. The shear stress, normal stress and deformation data are generated. From the generated data, the critical regions are identified and the lateral zone of tunnel is one of them. This region is likely to induce damage in the form of crack

AI Evolution in Industry 4.0 and Industry 5.0: An Experimental Comparative Assessment

This paper provides a thorough analysis of the development of artificial intelligence (AI) in the context of Industry 4.0 and the soon-to-be Industry 5.0. Important conclusions come from the data, such as the startling 900% increase in AI applications between 2010 and 2018, which corresponds to a 60% rise in the proportion of industrial enterprises using AI at that time. Moreover, our analysis shows that Industry 4.0's AI integration has resulted in a notable 200% cost reduction and a cumulative 400% boost in production efficiency. Our study delves into the rapid deployment of critical technologies like 5G connectivity and quantum computing within the framework of Industry 5.0. The usage of 5G connectivity has increased by 200% in only two years, while quantum computing has seen a staggering 1000% growth in acceptance over the course of eight years. These findings demonstrate the fast technological transition occurring in Industry 5.0. Furthermore, by 2033, the research predicts a startling 400% increase in human-machine cooperation and an anticipated 133% decrease in mistake rates. The research highlights how Industry 4.0's deep consequences of AI development and Industry 5.0's revolutionary possibilities will impact manufacturing in the future

Security and Privacy in AI-Driven Industry 5.0: Experimental Insights and Threat Analysis

This empirical research offers important insights from simulated industrial situations as it examines security and privacy in AI-driven Industry 5.0. When responding to security problems, participants' remarkable average reaction time of 14 minutes demonstrated their preparedness. On a 5-point rating scale, the clarity and openness of privacy rules were scored 3.8 overall; however, differences between 3.5 and 4.2 indicated the range of privacy issues. These results highlight the need of well-defined security procedures, thorough training, and easily available, transparent privacy regulations in order to manage the ethical integration of AI into Industry 5.0 and promote stakeholder confidence and data protection

Optimal Sizing and Operation of Standalone Power Systems for Remote Industrial Applications

This paper reviews the work in the areas of optimal sizing and operation of standalone power systems for remote industrial applications. The first study delves into an innovative approach applied to sizing in a hybrid power system, focusing on meeting the demands of a residential area in south-east Iran. This system integrates fuel cells, wind units, electrolysers, a reformer, an anaerobic reactor, and hydrogen tanks, utilizing biomass as an energy resource. The system’s design ensures that power produced from wind turbines and fuel cells meets the demand, with excess power directed to the electrolyser and shortages supplemented by stored hydrogen. The primary objective is cost minimization using the PSO algorithm. The subsequent studies emphasize the accelerated development of eco-friendly technologies shaping the future of electric power generation. They present a methodology for capacity optimization of a residential standalone microgrid, incorporating renewable energy sources, diesel generators, and battery storage systems. The microgrid caters to both typical residential loads and electric vehicle charging demands. Through intricate optimization, the studies aim to minimize costs, reduce greenhouse gas emissions, and limit dump energy. The research also explores the impact of load shifting on distributed generators and storage systems, offering valuable insights for decision-makers and policy developers

Perspective-smart energy management system using machine learning

In today’s rapidly evolving world, the demand for energy is steadily increasing, while the need for sustainability and efficient resource utilization becomes ever more critical. Smart Energy Management Systems (SEMS) are poised to play a pivotal role in addressing these challenges. Leveraging the power of Machine Learning (ML), SEMS offer a promising avenue to optimize energy consumption, enhance grid reliability, and reduce carbon footprints. This review article provides an in-depth exploration of the current state of Smart Energy Management Systems empowered by Machine Learning, highlighting their key components, applications, challenges, and future prospects

AI Evolution in Industry 4.0 and Industry 5.0: An Experimental Comparative Assessment

This paper provides a thorough analysis of the development of artificial intelligence (AI) in the context of Industry 4.0 and the soon-to-be Industry 5.0. Important conclusions come from the data, such as the startling 900% increase in AI applications between 2010 and 2018, which corresponds to a 60% rise in the proportion of industrial enterprises using AI at that time. Moreover, our analysis shows that Industry 4.0's AI integration has resulted in a notable 200% cost reduction and a cumulative 400% boost in production efficiency. Our study delves into the rapid deployment of critical technologies like 5G connectivity and quantum computing within the framework of Industry 5.0. The usage of 5G connectivity has increased by 200% in only two years, while quantum computing has seen a staggering 1000% growth in acceptance over the course of eight years. These findings demonstrate the fast technological transition occurring in Industry 5.0. Furthermore, by 2033, the research predicts a startling 400% increase in human-machine cooperation and an anticipated 133% decrease in mistake rates. The research highlights how Industry 4.0's deep consequences of AI development and Industry 5.0's revolutionary possibilities will impact manufacturing in the future

Advancements in Friction Stir Welding: A Comprehensive Review of Process Variables and Emerging Developments

Friction stir welding (FSW) is a solid-state welding technique widely employed to join materials such as Aluminum (Al), Copper (Cu), Magnesium (Mg), and their respective alloys. These materials find extensive use in industries like transportation, where lightweight materials with superior mechanical properties are in demand due to their reduced mass. Conventional fusion welding methods can adversely affect the mechanical properties of these welds.Over the last two decades, FSW has emerged as a specific and significant advancement in welding technology. Various parameters, including shoulder diameter, shoulder profile, pin length, pin diameter, tool angle, rotating speed, feed rate, and weld speed, play crucial roles in determining weld strength, quality, heat generation, and material mixing.The current research focuses on investigating the process variables that influence the characteristics of welded products. Furthermore, it includes an in-depth exploration of FSW fundamentals, recent advancements, and comprehensive literature reviews

Automated Interview Evaluation

The Interview Automation System is an Artificial Intelligence (AI) powered platform designed to help users prepare for real-life interviews. By asking questions and evaluating responses against original answers, our system provides users with a valuable opportunity to practice and improve their interview skills. The research aims to increase users' familiarity with the interview process, ultimately boosting their confidence and improving their chances of success. The workflow of the research involves several key steps, including data pre-processing and database management, audio-based question delivery, and audio-based answer collection and evaluation. Our platform is easily scalable and can be expanded to include additional functionalities such as users confidence detection, resume-based topic questioning, and body language analysis

A Low-Cost Underground Mining and Miners Monitoring System Using Internet of Things

The safety of mine workers is a serious worry nowadays. the miners construct underground rooms to facilitate the minerals to be taken out of the mine at work in, which requires greater output and a larger workforce. In underground mining work locations, 2753 injuries were reported as non-fatal lost- time, resulting in 190,005 lost workdays. The main aim of this proposed system is to save workers from sudden falling and detect the toxic gases present in the mining area. Using the IOT technology, we created a system with different types of sensors to solve these issues. We used flame sensor, temperature and humidity sensor and Gas sensor, to detect the toxic gas environment inside the mining and detect the fire burst inside mining in the first module. Accelerometer sensor is used to detect the falling of the worker and the pulse sensor is used to detect the heartbeat of the worker in the second module. We have created the two modules where one module is for miners monitoring and another is for mining monitoring All these sensors are integrated with the NodeMCU. All the obtained data is sent to thingspeak cloud and if any abnormality is detected we will receive a notification through email using alert API