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The rapid development of new technologies and artificial intelligence offers the field of railway transports and not only that, a series of opportunities related to the aspects of safety, security, performance and other concerns that this sector faces. This paper presents the implications that artificial intelligence can have in railway transports and the relationship between this technology and the transport system. The implications of artificial intelligence in the field of rail transport can cover a wide range of problems that the system faces, such as: safety and security, maintenance and inspection, management and planning, driving and control of railway vehicles and, last but not least, passengers' mobility. This paper provides an overview of the role of artificial intelligence in the development of railways and what it can offer not only at the level of track maintenance, but also at the level of management and decision-making. Despite the rapid development of these new technologies, artificial intelligence research in the railway sector is still in its infancy. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has been widely used across the oil and gas industries that elevate asset management efficiency. Nevertheless, as the industry produces hydrocarbons, reducing CO2 emissions becomes one of the challenges. Therefore, this paper illustrates the utilization of AI to enhance the gas lift operation using pattern recognition and optimization algorithms. Initially, the feature extractor was developed using self-supervised learning to learn features from data without manual labels. Then, the patterns are clustered to build a pattern recognition model using a supervised classification model. Afterward, an optimization algorithm is applied to optimize fluid production under allowable operational and CO2 emission limits. Then, a gas lift stable production model was developed using Machine Learning (ML), relying on controllable and reservoir parameters that will be used for optimization purposes. The study used synthetic data from eleven wells with similar wellbore and mandrel configurations with various depth and Productivity Index (PI) and constant reservoir pressure. An air compressor specification and specific CO2 emission were also determined. In addition, gas injection and adjustable choke are assumed as controllable parameters in the optimization process. This study shows a high prediction model accuracy of 0.99 for K-Nearest Neighbor classifier (KNN) and an R2 score of 0.99 for Multi Layers Perceptron (MLP) as a regressor. As regards the optimization algorithm, Simulated Annealing (SA) was used to achieve the optimum solution in a reasonable time, especially for a near real-time environment. Lastly, the workflow introduced in this paper could be implemented in a real case as the study used widely known information in gas lift operations. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Machine Learning (ML) transforming the Insurance industry by improving efficiency, reducing costs, and providing a better customer experience. As these technologies continue to evolve, more innovation can be expected in the Insurance industry. A Bibliographic analysis is conducted for scientific mapping based on 1,084 SCOPUS-indexed publications between the year 2000-2022 using VOSviewer Application. The Analysis was conducted based on Publications by year, Source, Author, Affiliation, Country, Type, Subject Area and Funding Sponsors. The research found the result, the year 2022 had the highest publication of 203, through documents per year by the source of Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics at 43 publications, Bauder, R.A. author is the maximum contributor, Harvard Medical School has been the major affiliate, United States of America, has the maximum 341 publications, Conference paper has the majority participation at 412 documents at 38 percent and Keywords "Artificial intelligence", Machine Learning" and "Insurance" has the highest occurrence. The maximum number of publications inthe field of computer science at 28 percent. Overall, this bibliographic analysis provides a comprehensive overview of the current state of research in AI and Machine Learning in the Insurance industry and highlights the potential for further innovation and development in this field. [ABSTRACT FROM AUTHOR]

The 5th Parul University International Conference on Engineering and Technology, PiCET-2023, will take place on May 5-6, 2023, in Vadodara, Gujarat, India. The conference, organized by the Faculty of Engineering and Technology at Parul University, aims to address the challenges and opportunities brought about by emerging technologies in engineering and its allied branches. The event will feature keynote lectures, research paper presentations, poster presentations, and technical deliberations. It also serves as a platform for industries and institutions to showcase their products, services, and groundbreaking research. The conference will cover various technical tracks, and a total of 69 papers have been selected for publication in AIP. The event will be attended by esteemed speakers, including Dr. T G Sitharam and Dr. Akhilesh Gupta, among others. [Extracted from the article]

The article describes the possibility of applying artificial intelligence in broad scientific research in the field of magnetic abrasive finishing. Artificial intelligence makes it possible to accelerate research work at certain stages, which reduces costs. A prerequisite for its use is the formulation of appropriate queries and limiting the range of responses. These limitations are mainly due to the lack of access to scientific databases. The paper uses OpenAI software called Chat GPT and describes the specifics of the work. The paper examines the various aspects of creating a scientific study starting with selecting a topic, reviewing the literature, developing a research methodology, developing and analyzing the results, and drawing conclusions. The topic of intellectual property and the originality of the results and conclusions obtained was also touched upon. On this basis, a comparison was prepared showing the areas of scientific activity where the use of artificial intelligence is most effective. [ABSTRACT FROM AUTHOR]

Researchers are currently paying increased attention to the problem of green supplier selection because it affects the performance of green supply performance. However, the previous article never discussed the literature review on Green Supplier Selection for the Agri-food Industry. Therefore, the purpose of this paper is to provide a thorough analysis of the methodology and context of Green Supplier Selection for the Agri-food Industry. From 2014 to 2022, 28 peer-reviewed papers were collected from the Scopus database and Google Scholar searches. This review study is divided into two problem contexts: green supplier selection and green supplier selection and order allocation. Furthermore, this review is based on a methodology that incorporates problem-solving techniques such as Multi Criteria Decision Making (MCDM), Mathematical Programming (MP), Artificial Intelligence (AI), and Hybrid (Integrating MCDM-MP and MCDM-AI). The results show that the Green Supplier Selection problem has received the most attention, followed by the Green Supplier Selection & Order Allocation problem. Furthermore, the MCDM procedure dominates the methodology used in the Green Supplier Selection. [ABSTRACT FROM AUTHOR]

Industry 4.0 is transforming the manufacturing industry through the integration of advanced technologies such as automation and information technology. This paper provides a comprehensive review of the impact of Industry 4.0 on automation and information technology in industry. It examines the potential benefits of Industry 4.0, including improved efficiency, productivity, flexibility, and customization, as well as the challenges businesses face in implementing these technologies. The paper discusses the need for careful planning, collaboration, and investment to ensure that Industry 4.0 investments align with business goals and provide a return on investment. Also, this paper highlights the need to prioritize cyber security and training to mitigate the risks associated with integrating advanced technologies. It identifies the importance of reskilling and upskilling the workforce to prepare for new roles and responsibilities and highlights the need to prioritize cybersecurity in Industry 4.0 strategies. The paper highlights the opportunities that Industry 4.0 offers businesses to create new business models and transform their manufacturing operations. The use of advanced technologies such as 3D printing, artificial intelligence and the Internet of Things enables businesses to create products on demand and tailor them to specific customer needs. This can increase customer satisfaction and create new business opportunities. Alongside this, this paper presents an analysis of the impact of Industry 4.0 on various industries and the growth in adoption of Industry 4.0 technologies over time. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) with mathematical modelling is one of the most metaphoric technologies in modern history. It helps businesses around the world, improving efficiency and optimizing resources especially in supply chain management (SCM) and logistics sector. AI has also made its way into supply chains and logistics, where it provides several advantages to businesses that are prepared to accept new technology. The review refers to the previous research papers with keywords of AI, supply chain, logistics are sorted from five recent years and aims to comprehensively review types of technologies used by optimizing the strategies and the implementation of AI methods highlight several challenges faced by AI to be deployed in this sector. The soft computing extracted in this paper mainly uses AI and fuzzy logic for problem giving and enhances the efficiency of SCM. However, there are challenges that are encountered by AI to predict and drive the decision making with minimum complications. Several challenges addressed in this paper are resources, lack of security especially in RFID systems and the complexity found in robotics systems in logistics. In conclusion, based on the literature review, the research framework, new research based on the research gap is able to be obtained for further research focus. [ABSTRACT FROM AUTHOR]

Natural disasters cause devastation, chaos, destruction, death, displacement, and much more when they occur. With the advancement of recent technologies especially in artificial intelligence and deep learning, the severity and impact of natural disasters could be reduced by predicting their occurrence. In this research, the flood detection (using images) system is developed using the proposed architecture of the Deep Convolutional Neural Network (CNN). In this paper, the main aim is to propose an automated System for precision disaster detection, in particular flood detection. The intelligent system will monitor vast problematic areas that are dubbed flood risk areas during the season. The intelligent automated system will systematically take images with real-time processing to detect floods. If a flood is detected, the system will automatically communicate to the ground station with the early warning to issue an early warning to all the inhabitants in the path of the flood. Since this paper will prove a concept, the other main contribution of this paper is a new dataset consisting of 9000 images collected from various sources on the Internet, labeled, and preprocessed. The Deep CNN architectures were trained and tested by constructing a new dataset of more than 9000 labeled images with flood and non-flood collected from different sources. Several experiments are performed with changing CNN architectural design parameters in order to get the best recognition rates. Experimental results show that 92.50% accuracy was achieved using GoogleNet. The second highest performance was achieved using AlexNet with an accuracy of 92.20%. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is an essential component in modern games. With AI, players can feel the challenges in the game and the game will feel more real. AI has several branches, one of which is path-finding. Pathfinding is a way of finding the shortest path between two points. The main problem in path-finding is how to perform a path-finding accurately and requires fewer computational resources (CPU and memory). This paper describes the results of research that tested the A* and Hierarchical Pathfinding A* algorithms using the Unity 3D platform and the C# programming language. The graph or space to be used is a graph with 8 branch nodes. While the benchmarks used are the path generated and the processing time of an algorithm. This paper results in a conclusion that the path generated by the A* algorithm is shorter than the Hierarchical Pathfinding A* algorithm. The number of paths processed for the A* algorithm is more than the Hierarchical Pathfinding A* algorithm. The total execution time of the A* Algorithm is smaller than that of the A* Hierarchical Pathfinding Algorithm. The Hierarchical Pathfinding A* algorithm experiences spikes in execution time more often than the A* algorithm. However, if the total spike time, the Hierarchical Algorithm is less than the A* Algorithm. [ABSTRACT FROM AUTHOR]

This paper gives the idea of solving some of the problems faced by farmers. The population rate of the world is growing rapidly and will double in the coming decades and the need of food is also increasing simultaneously. To meet this rapid growth in demand for food, automation in agriculture is the best solution. The aim of this paper is to design and develop an automated system to monitor the various conditions of soil and moisture on the crops, and the proper supply of water, which affects the crops [5]. Such a system will contain sensors, a pump and a device called a humidifier, and various advanced techniques like IoT, machine learning, and artificial intelligence. The technical field is racing to provide more optimum solutions. The incorporation of IoT, along with cloud computing, big data analytics, and wireless sensor networks can provide enough scope to predicrocess, analyze situations and improve activities in a real-time situation. Green House is one of the best solutions as the crops can be grown in a controlled climate without the natural environmental conditions. In the last few decades there has been a huge advancement in technology for agriculture, with the help of technology we can help farmers for increasing their rate of yielding. With this, we can overcome the major problems of farmers. This small processor-based unit can be used to control anything from a fan, air-conditioner, humidifier, and watering system from 4 relay outputs. A temperature and humidity range can be set to control relay outputs. The main focus of this paper is to implement the Internet of Things (IoT) in the monitoring of humidity, soil condition, temperature, supply of water to the field, level of water, environmental condition, etc. The IoT-based Smart agriculture System being planned via this paper is integrated with different Sensors. [ABSTRACT FROM AUTHOR]

Speech emotion recognition is actually a challenging and new issue within artificial intelligence discipline. One of the primary bottlenecks of daily speech emotion identification strategies is actually tonal perturbation of speech. The goal of this paper is actually using Support Vector Machine (SVM) classifier to categorizing 7 various feelings like anger, happiness, sad, disgust, normal, boredom and fear. The exploration of futures capabilities consists of pitch, Mel-frequency spectrum coefficients (MFCC), Spectro temporal characteristics, formants as well as power specifications. Within this paper we utilize 3 distinct Tamil emotional collection as well as attribute fusion method to blend all of the spatial element extractions. Performance examination is actually accomplished by utilizing the confusion matrix as well as the precision rate attained by 3 databases are actually 87.5%, 86.25% & 88.5&% and having a typical average accuracy pace of 87.4%. And finally, from the outcomes for spatial feature fusion method on various databases are actually compared and we examined SVM recognition exhibits much better functionality with the very best precision rates in database 3 with 90% in 10-fold for the collected Tamil Emotional database. [ABSTRACT FROM AUTHOR]

Machine learning is an artificial intelligence (AI) technique for automation and prediction that is widely utilized today. This paper looks at the fledgling usage of machine learning in the legal field. The first portion focuses on the fundamentals of machine learning. The relationship between machine learning and law is discussed in the next section. Many parts of the law can be interpreted in terms of data, and machine learning works by recognizing patterns in data. Machine learning technologies can be used to learn about data-driven aspects of the law. After that, this paper looks at how machine learning is used in law while also recognizing the technology's strengths and limitations. It finishes by examining some current social debates around the use of machine learning in legal contexts. [ABSTRACT FROM AUTHOR]

Wireless communication systems must be able to support the high demands of new networks and devices in order to meet the rapidly expanding economic and cultural needs of human society. 5G/Beyond 5G systems must connect with a high number of devices, have significantly lower latency than 3G/4G wireless networks, and meet strict quality-of-service (QoS) requirements. The application of artificial intelligence (AI) and machine learning (ML) to wireless applications will be one of the primary and essential elements of 5G systems. These methods are used in all parts and building blocks of wireless systems at the physical, network, and application layers. Researchers from all over the world are very interested in the 5G criteria and these technologies. A 5G network needs AI technologies to be completely functional and effective. On the other hand, ML is a promising technology that may be applied to data processing. Existing generations broadcast using Internet Protocol (IP) broadband access, which is inefficient. Hence, in order to function 5G networks they must be proactive and predictive to ML and AI. In this regard, this paper highlights the role and significance of AI and ML in 5G communications and also provide potential future research directions. [ABSTRACT FROM AUTHOR]

The advent of new technologies in armed forces and also the relationship between and among states compels to invest more on sophisticated weapons and weapon system. Defense is the mechanism created to safeguard someone or something from a hostile attack. Nations must consistently be on vigilant against internal and external challenges, risks, and attacks of all kinds. These forces must steadily maintain the greatest standard of alertness, readiness, and surveillance. The majority of the defence forces' activities are made much easier by technology. The role of artificial intelligence helps during those operations. AI systems helps to reduce the causalities during military operations. The data help to take quick decisions during emergency responses. This paper focuses especially with the advancement of Artificial Intelligence (AI) and its military implications which helps to acquire speedy data processing against the hypersonic weapons. [ABSTRACT FROM AUTHOR]

The practice of Machine learning and the Internet of things have occupied a significant role in day to day life of human beings. These two trending technologies are simplifying and solving major critical problems. Particularly in the Industrial, Environmental, Education, Agriculture, and Health Care areas, most of the work was automatic and reduced the human effort. In this paper, we have discussed the role of machine learning, the Internet of things in health care, how these techniques diagnose and detect a disease and monitoring the patient in critical care, and alert the needy people whenever they're required. The disease like cancer detection and early prediction, heart attach prediction, pneumonia detection, reoccurrences of deices, and just by considering the features like x-ray images, temperature, age, etc. by monitoring these features, the algorithms are predicting and detecting the risk level of a patient with that the loss of patients reduced. [ABSTRACT FROM AUTHOR]

Search-based data analytics is a big area that requires great attention in many different areas. To address real-time issues, many methods and algorithms are utilised for search-based optimization. Many fields of study include design, accounting, finance, continuous imaging, and many more, but the most important are machine learning and deep learning. The experts are experimenting with a wide range of technologies and advancements, including open source, and have developed methods that enable them to achieve a greater degree of precision. When it comes to deep learning, it's inextricably linked to machine learning since it combines greater levels of execution and accuracy with a lower base error rate. Genetic Method, a high-performance algorithm for engineering optimization, is presented in the paper as use cases. For the purposes of data analytics and in particular for a multiprocessor scheduling strategy, the goal of this article is to provide the effective implementation of the famous evolutionary computing technique of genetic algorithm for genetic algorithms. Due to its better results on a variety of factors, the genetic algorithm described here may offer real and measurable results. There were no successful outcomes from the prior techniques' usage of greedy-based approaches, therefore researchers turned to genetic algorithm-based optimization. To design and simulate the implementation scenarios, we used MATLAB and Java-based development tools, and the results were very useful for optimizing. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) recently plays a major role in the working world. AI in few years will be inevitable in all the businesses and services. AI also plays a virtuous role in supporting Human Resource Management. Most people fear that AI will cause them unemployment, but truly, AI has the capacity to build more jobs in the near future as AI will not remove workers from their jobs, but it will reduce monotony and frees up employees to perform more complex tasks. Transformational leadership are always ready for a positive and innovative change in the organization. By leveraging Artificial Intelligence technologies, leaders can become more transformational, foster a culture of innovation, and drive successful organizational transformations. This article aims at analyzing how artificial intelligence plays a role in enhancing transformational leadership. This paper aims at providing a comprehensive review of how artificial intelligence impacts transformational leadership. The results of the study concluded that AI technologies can help leaders to become more transformational thereby empowering their employees and become a reason for successful organizational changes. This article also helps in gaining new insights into how AI can play a role in enhancing transformational leadership in an organization. [ABSTRACT FROM AUTHOR]

Kidney is one of the significant organs in the human body which performs filtering out blood, balances fluid, removes the waste, maintains the level of electrolytes and hormone levels. So, any disorder or dysfunction in kidney needs to be detected on time in order to preserve life. Segmentation on kidney tumor in medical field is a critical task and many conventional methods have been employed for early prediction of kidney abnormalities but with limitations such as high cost, extended time for computation and analysis with huge amount of data. Due to all such problems, the prediction rate and accuracy has reduced considerably. In order to overcome the challenges, Artificial Intelligence (AI) technology has penetrated into the field of medicine particularly in the renal department. The evolution of AI in kidney therapies improve the process of diagnosis through several Machine Learning (ML) and Deep Learning (DL) algorithms. It has the capability of improving and influencing on the status with its capacity of learning from the massive data and apply them accordingly to differentiate on the circumstances. The storage of larger data and segmentation with AI assistance are highly helpful for the analysis of occurrence of the disease. AI algorithms have predicted the severity of tumor stages with effective accuracies. Hence, this paper provides a critical review of different AI based algorithms being used in the kidney tumor prognostication. Its numerous benefits in field of segmentation have been researched from the existing works and provides an insight on the contribution of AI in the kidney disease prediction. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study of the trends in banking services. The consequences of the severe post-Covid-19 crisis and the isolation have had a strong impact on all areas of business. This has led to a rapid digitization and implementation of smart bank branch technology, aiming at saving financial resources. Transactional models, representing the participants in a mobile payment transaction, as well as the connections, by means of which the communication takes place, are considered. The application of artificial intelligence in the bank activities and in the activities of the new bank branches is analyzed. The trends for future development of both the bank branches and the banking operations are outlined. [ABSTRACT FROM AUTHOR]

This paper aims to understand how Artificial Intelligence (AI) can help the financial sector, in general, promote financial inclusion. Artificial Intelligence (AI) has been growing at an unprecedented rate, thanks to a higher acceptance of new technological advancements. AI applications are being used in diverse fields, and the Banking, Financial Services, and Insurance (BFSI) Industry in India is one of the beneficiaries. The paper showcases the paradigm shifts due to the application of AI in the Indian Banking Sector compared to the earlier traditional banking mechanisms. AI applications, especially in the Banking Sector, benefit the underprivileged community greatly in helping them improve their access to credit lending, banking services and other critical information. The paper recommends using AI applications to ensure that the financially inactive/underprivileged sector participates in financial markets and benefits. Secondary Data is collected to gather information regarding the implementation of AI applications in the Banking and Financial Services industry and its impact on financial inclusion. The paper examines that artificial intelligence significantly affects financial inclusion, especially in solving information asymmetry, improving banking and credit services access to the underprivileged (low-income groups), providing customer service, and support through chatbots, fraud detection, and network security. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are being employed more frequently for defense and civilian applications these days. Despite the fact that modern technology has many advantages, it also creates new business and industrial challenges. Current laws and regulations cannot be applied to UAV's due to the fact as they are not required to use in existing infrastructure. Even in dire circumstances, UAV's may quickly overcome physical obstacles and pose a threat to society. Hence, the present manuscript focused on creating a Drone Protection System (DPS). In India over the past ten years, the use of drones for both military and civilian purposes have been evaluated. To mitigate the dangers posed by UAVs, counter-drone technologies are also being put together in the interim. This paper examines the aforementionedproblem and provides suggestions to reduce the growing threat posed by drones. Moreover, modern technologies like artificial intelligence (AI), cognitive global positioning system avoidance, and hardware application security must be considered when evaluating the efficiency of anti-drone systems. A prototype for the Anti-Drone UAV system that can capture potentially dangerous UAV's in the air is presented in this paper. The aim of the present work includes the state of the art anti-drone capture mechanism with various existing ways to halt unidentified drones, and also to determine the best method for slicing the target in half. With the first preliminary observation, a simplified Net gun is modeled and affixed with the Anti-Drone Quad copter, and successfully deployed for capturing the UAV's. The obtained results and the present concept may be used to further develop a swarm mechanism for national aerial defense as a future work. [ABSTRACT FROM AUTHOR]

There has been a lot of research in recent years into employing optimization approaches to improve artificial intelligence (AI). In this research review paper, we have compared and contrast some of the most usual optimization algorithms, such as Backtracking searching method (BSA), the genetic algorithm (GA), particle swarm optimization (PSO), an artificial bee colony (ABC), and the genetic algorithm, which are all artificial neural networks (ANNs)-based algorithms. The number of recently developed optimization techniques, such as the lightning search algorithm (LSA) and the whale optimization algorithm (WOA) are also compared. All the techniques are categorized based on randomly generated populations. To produce the best possible results, the processing parameters are set within a certain range according to their knowledge. This review paper emphasis on applying optimization techniques to improve the accuracy of simply adjusting the parameters of the neural network. This review paper also presents some results for enhancing neural network performance using various optimization techniques like PSO, GA, and ABC optimization methods to get optimal processing parameters, such as the number of hidden layers, neurons and learning rate etc. The findings of this research review paper will aid in the improvement in the quality of plastic injection molded parts. [ABSTRACT FROM AUTHOR]

Smart cities are a mixture of using different Internet of Things (IoT) devices and artificial intelligence techniques to develop a better environment for living. The paper's primary focus is on the various aspects of smart city infrastructure, and the threats surrounding it. We also discuss the vulnerabilities that cause the threats and the recommended solutions for these problems. We outline our proposed approach not to let these threats violate the infrastructure layout of smart cities. A breakdown of every smart city aspect alongside its threats, vulnerability, and solutions is described in the paper. Smart grid, smart transportation, smart healthcare, and smart buildings are the four main aspects of a smart city, whose details are presented in the paper keeping an information security perspective in mind. [ABSTRACT FROM AUTHOR]

Artificial intelligence is the simulation of human intelligence and seeks to mimic human knowledge acquisition by using planning, reasoning, and research. Sometimes AI faces challenges due to a large set of rules, and growing demand for learning and searches optimization. Computational intelligence is a form of computing modeled on the methods by which humans learn. Artificial neural networks system learns by being given different image examples, and contain many layers of learning, some of them more complex than others. This paper presents a comprehensive survey on the various artificial neural network open source software for implementing computational intelligence as they seem to be effective in simulation, prediction, building, and studying artificial neural networks. This paper helps the researchers to find which software they should prefer by knowing their requirements. [ABSTRACT FROM AUTHOR]

The global COVID-19 pandemic had a severe impact on various services across the world. This paper analyzes the barriers and challenges in the integration of Information and communication technology (ICT) in the legal education and justice delivery system. The recent pandemic highlighted the lacunae in the traditional legal education sector and court proceedings. Thus, this paper extensively explores and scrutinizes how ICT can be seamlessly integrated in the legal education and judicial processes, such as virtual courts, e-filing systems, digital tools etc. It analyzes the various risks posed by the use of ICT including data and security concerns, algorithmic biases, access issues for marginalized and rural communities. Thus, the paper underscores the need for ICT-based solutions and aims to act as a catalyst in this transition from the traditional systems, by analyzing the different dimensions related to ICT and Artificial Intelligence. [ABSTRACT FROM AUTHOR]

This paper discusses the renewable energy sources and its necessity to fulfil the energy requirement of real world. Renewable energy is one of the booming industries where it represents a highest impact on increasing the economical status, energy needs, and fighting with the natural climate variations. But, due to their inherent intermittency, some of the renewable energy leaders, such as Wind and Solar they can not full fill the huge demand. Also, there is a grow in aggressive objective of greenhouse gas depletion. Furthermore, the money matters of distributed renewable energy plans are coming up with high competition for the risky environment developers. To solve these kinds of solutions and improve the energy distribution for changing climate intelligent energy storage is used. In addition to that, artificial intelligence is enabled for bringing a novel value streams for renewable energy plans. Adding AI to energy storage increases the returns on investment, provide the control and elasticity of varying prices, etc. Hence this paper insists that the integration of Artificial Intelligence into renewable energy industry is more important for enhancing the economic as well as customer satisfaction. [ABSTRACT FROM AUTHOR]

In this paper for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 120 number of tasks and processors. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Automation innovation are growing at a steady rate that are changing organizations and bringing efficiency and adding to the economic development. The utilization of AI and robotization will likewise help improve different areas from wellbeing to horticulture. Furthermore, utilizing Automation and Artificial Intelligence would, follow the schedule, transform the idea of work and the working environment itself. For sure, machines will actually do large numbers of the undertakings typically done by people, just as supplement manual work and play out certain errands that an individual wouldn't have the option to do. Consequently, AI and mechanization have a great deal to bring to organizations and enterprises worldwide. This research paper comes up with a rundown through the blooming of Artificial Intelligence and Automation. We explored the existing potentiality of cognitive emerging technologies. This paper outlines the discussion about artificial intelligence and automation technologies and an overview of the applications. [ABSTRACT FROM AUTHOR]

Artificial intelligence incorporated into machines utilizes capacities to work and replaces people. Knowledge is the method of assembling empowered machines that can mirror human tasks as unique. With digitalization, organizations are remodifying their enterprises and making new business possibilities. Because of AI innovation, organizations change their dynamic cycles and systems and everyday tasks to accomplish the upper hand. An impressive development in the utilization of AI for activities, the board, is fully intent on observing answers for issues that are expanding in intricacy and scale. With the turn of growth and advancement of data innovation, competitiveness has become increasingly more in-depth worldwide. The AI has its own explanations behind examining and settling the sorts of issues that prompted a critical measure of exploration along with the conventional operational research discipline. Many organizations have estimated the fate of operations management. This paper lines with a descriptive research study highlighting the importance of process operations. This paper gives insights about AI technology into operations management and suggests selecting process technology and deploying AI into operations management. [ABSTRACT FROM AUTHOR]

Sustainable development is vital to mankind. The world is finding a growing effort of Artificial Intelligence (AI) towards sustainability, and we made an attempt to address the development in sustainability using AI systems. Sustainable development has three pillars of sustainability (i.e. social, economic, environment), and as such, the pillars of sustainable AI. The entire Life cycle of AI products can foster change in the movement of sustainability from which greater integrity and social justice can be achieved. Sustainable AI helps us to address the whole socio-technical system more than AI applications. This paper tried to address the positive impacts of AI on sustainable indicators in terms of Environmental, Societal and Economy factors. This paper is prepared to make readers, policymakers, AI ethicists and AI developers to inspire and connect with the environment for the current and future generations as there are few AI costs to be made compatible with the environment. [ABSTRACT FROM AUTHOR]

The Propels within the web innovation, web of things, cloud computing, huge information and artificial intelligence have significantly affected fabricating or manufacturing. The volume of information collected in manufacturing is developing. Huge information offers a colossal opportunity within the change of today's manufacturing paradigm to smart fabricating. Enormous information enables companies to receive data-driven methodologies to become more competitive. In this paper, the part of enormous information in supporting smart fabricating is discussed. An authentic viewpoint to information lifecycle in fabricating is overviewed. The enormous data perspectives are backed by a conceptual system proposed within the paper. Common Place application scenarios of the proposed system are sketched out. [ABSTRACT FROM AUTHOR]

The field of robotics research has been well developed with the combination of computers and machinery. With the advancement of artificial intelligence, mobile robots are also attracting more attention today, and path planning is a crucial foundational technology for mobile robots to complete transportation requirements and reach pertinent target areas. In an efficiency-conscious society, the single-goal planning of transmission is gradually failing to meet the needs of enterprises and factories for efficient operations, path planning that can simultaneously plan the optimal methods and reach many target points is increasingly replacing the conventional single-goal path planning. However, there are more factors to be considered in the real complex environment to face various complex road conditions, and for this reason, various single or hybrid algorithms are being optimized and solved for this kind of problem. This paper summarizes the main methods of path planning to simulate the scale of obstacles and environmental scene maps in various conditions, focusing on several basic algorithms and their hybrid algorithms for solving multi-objective path planning problems in global and local path planning, as well as their improvements and innovations on the basic algorithms. This paper's primary idea is to divide the multi-path planning process into various components and substitute each part into a suitable algorithm and model to solve it separately to accomplish the task of reaching multiple target points efficiently. [ABSTRACT FROM AUTHOR]

Since its original announcement in Wuhan, the (COVID-19) has become a well-known medical illness in China and around the world. The plague has wreaked social and economic outcomes all over the world. The increased number of COVID-19 testing provides additional information about the pestilence's spread, potentially allowing our environmental factors to prevent future pollution wearing a facial covering that prevents flying beads, maintaining sufficient separation between individuals, and limiting close contact can all help to combat the outbreak. Hence, this examination paper centers on utilizing As an implanted vision framework, the Face Mask, and the Social Distance Discovery concept are used. Individuals who were found disregarding the local area or not wearing a veil were found. After making and eliminating the models, the anointed one got 100 percent certainty focuses. This paper gives a relative investigation of facial recognition and facial veiling models. Framework execution is tried for precision, memory, F1 focuses, and support. [ABSTRACT FROM AUTHOR]

Recommendation systems are an important feature in our computerized world, where users are often stuck with choices most of the time and need help to be able to find what they are looking for. Since we cannot search the website for all the content and products, whether books, clothes, or others, the primary goal of recommendation systems is to help all users on websites find what they are looking for. Artificial intelligence has contributed to the development of recommendation systems to improve prediction accuracy. This paper presents a comparative study of approaches in recommender systems, starting with a general presentation of each, and then addressing the advantages, limitations, and techniques. All the notes in the paper will help researchers to understand new trends and developments in recommender systems. [ABSTRACT FROM AUTHOR]

In the era of technology and artificial intelligence we always come across different type of interface board. Many students are showing interest in the new emerging field. And for starting their journey it is very important to know about various interfacing board so that they can program them and use it to create new things. The emerging wireless communication vie wi-fi and Bluetooth helpful in connection devise and gadgets with internet. Interface board in help us to connect with devices and the internet. Sometimes it is difficult for students to find about different interface board and which board is best as per there requirement. So, this paper will help students to understand different boards and different type of sensors which can be used on these boars. It will also cover the type of microcontroller used. And for stating from the scratch this paper will also provide them some knowledge of some of the software which they can use for interfacing. [ABSTRACT FROM AUTHOR]

Requirement analysis serves as a link between end-users and the software development team in software development. User requirements are nothing more than their desires, which software must fulfill for them to be satisfied. The processes involved in software development are planning, data gathering, data analysis, design, programming, testing, implementation, and maintenance processes. Planning is the first step in any software development project. Human intervention is required during these processes because they are extremely complex. Several types of knowledge are required during the software development process, including problem domain, programming domain, and programming language knowledge. To create a single solution, it is sometimes necessary to bring together different types of knowledge. The aim of software development is to satisfy and fulfill all users' needs through software, which is the primary goal of all software development. A problem during the requirement analysis phase will cause the entire SDLC process to be halted. It is because the SDLC is cyclic. The SDLC requirement analysis phase is extremely important to mitigate this risk. Because of the high quality of software requirements, it is necessary to have high-quality software requirements. Specifically, this paper aims to discuss the application of artificial intelligence techniques for requirement analysis in the context of software development projects. For this research, end-user requirements are investigated and analyzed and then transformed into AI techniques, among other things. This paper aims to identify requirements problems during the requirement analysis and provide AI techniques to overcome these problems as quickly as possible. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) based applications are gaining much of the limelight in recent days. This paper mainly focuses on how to run IOT based technologies with the use of software. IOT based technologies on today's era are gathered a lot of buzz. With the upbringing of ubiquitous computing, these devices could be powered from anywhere around the globe. IOT is powered by Artificial Intelligence for making quick and effective decisions as well as machine learning to make predictions based on the past data. A software emulation application interface which enables us to build logical networks which works as a blueprint for physical infrastructure as well. This paper mainly builds on the idea of running IOT based technology, making use of this software application. The software application is used by making a connection between different IOT devices and a home portal gateway. The main objective of Smart Home Networks is by connecting the devices at our home together so that one can control all the devices from a single device such as a mobile phone. It can be easily checked if the devices are functioning in a correct manner by going to the web browser and then typing the IP address of the Home Gateway. An interface then allows us to check the working of these networked devices. The model depicted in this paper indicates a Smart Home network including a solar panel and battery as well. For this, Cisco Packet Tracer software is used to control the IOT devices by connecting it to a home portal gateway. It is discussed elaborately how to run IOT devices in real life environment by connecting a solar panel and battery as well. [ABSTRACT FROM AUTHOR]

This paper discusses a review structure in modified Maximum Power Point Tracking (MPPT) for a single phase Z-source inverter (ZSI) when connected to a photovoltaic (PV) module. Both soft computing MPPT mechanisms, Artificial Intelligence (AI) and Evolutionary Algorithm (EA) are very effective in dealing with nonlinear I-V characteristics of PV module. ZSI can be used to buck or to have boost operation at the inverter ac output voltage when the duty cycle is changed. In this paper, the selective MPPT control algorithms have been discussed in order to understand which controllers are the most effectively applied to maximize the power generation at the inverter output. At the end, this paper will tabulate a comparison between the AI and EA techniques which could reduce the complexity of implementation, tracking efficiency, control strategy and reliability towards ZSI. These tables will help in recognizing the suitable MPPT controllers that can be applied to a specific load for a new research exploration in the future. [ABSTRACT FROM AUTHOR]

In this paper we present a novel method designed for word-level visual speech recognition and intended for use in human-robot interaction. The ability of robots to understand natural human speech will significantly improve the quality of human-machine interaction. Despite outstanding breakthroughs achieved in this field in recent years this challenge remains unresolved. In current research we mainly focus on the visual part of the human speech, so-called automated lip-reading task, which becomes crucial for human-robot interaction in acoustically noisy environment. The developed method is based on the use of state-of-the-art artificial intelligence technologies and allowed to achieve an incredible 85.03% speech recognition accuracy using only video data. It is worth noting that the model training and testing of the method was carried out on a benchmarking LRW database recorded in-the-wild, and the presented results surpass many existing achieved by the researchers of the world speech recognition community. [ABSTRACT FROM AUTHOR]

The paper is devoted to the problems of using methods of cognitive modeling and artificial intelligence in the analysis of controlled dynamic systems. An approach to the dynamic cognitive maps design for modeling pendulum systems is developed. This approach uses the procedure of universal approximation of the inverted pendulum model using the Takagi–Sugeno model. A fuzzy dynamic cognitive map is constructed for the studied model of the pendulum system. The proposed cognitive map takes into account the dynamic change in the weight coefficients inherent in the process being studied. The considered method of cognitive modeling makes it possible to determine the correspondence between the formalized description of the Takagi–Sugeno model and the dynamic cognitive map of the intellectual pendulum system. A generalized algorithm for stabilizing the pendulum using fuzzy cognitive maps is developed. The obtained results can be used in the design and improvement of controlled technical and mechanical engineering systems. [ABSTRACT FROM AUTHOR]

The reality is that the population and number of automobiles on the street are growing day by day. The efficient monitoring of continuously increasing traffic is a critical challenge that traffic operators are facing. Traffic control is generally achieved using stationary video recorders, observers or manual counters. Hence, Unmanned Aerial Vehicles or drones are the high-quality answers to this trouble as they lessen the price of the set-up of numerous cameras and sensors. This paper's principal ideology is split into phases. The first one is the monitoring of traffic using a drone which helps in analyzing the traffic in a particular area and making interpretations. The second is fire detection and extinguisher. Here the drone is used to detect fire with the aid of a fire sensor as it helps the fire-fighters to analyze the affected area and prioritize their work. This project also up-skills in designing a quad-copter. Our motivation for this project lays both personal interests in a better understanding of object detection and academic research. A drone consists of a camera to cover a wider area which helps in traffic analysis. Here, the number of vehicles are estimated. Drones have recently emerged as an outstanding technology in the business market and are geared up with a camera, geo-positioning sensors, and communications hardware that may relay statistics. This project is implemented by using artificial intelligence and the Internet of Things for Fire Detection. To be more specific traffic detection is achieved using Deep Learning algorithm which is the Convolutional Neural Networks Algorithm using python. Fire sensors are mounted on the drone, and it flies on a flight path within the building and sends fire alert data to the system controller upon sensing a fire condition via fire sensor and also puts off the fire using the water pump. For fire detection the sensor used in the drone basically detects IR (Infra-Red) light wavelength that is emitted from the fire flame which helps fire-fighters to quickly assess and monitor dangerous areas which results in more safety and limits the time it takes to scan the whole area. [ABSTRACT FROM AUTHOR]

With the continuous increase of internet usage in today's time, everyone is influenced by this source of the power of technology. Due to this, the rise of applications and games is unstoppable. A major percentage of our population uses these applications for multiple purposes. These range from education, communication, news, entertainment, and many more. Out of this, the application that is making sure that the world stays in touch with each other and with current affairs is social media. Social media applications have seen a boom in the last 10 years with the introduction of smartphones and the internet being available at affordable prices. Applications like Twitch and YouTube are some of the best platforms for producing content and expressing their talent as well. It is the goal of every content creator to post the best and most reliable content so that they can gain recognition. It is important to know the methods of achieving popularity easily, which is what this paper proposes to bring to the spotlight. There should be certain parameters based on which the reach of content could be multiplied by a good factor. The proposed research work aims to identify and estimate the reach, popularity, and views of a YouTube video by using certain features using machine learning and AI techniques. A ranking system would also be used keeping the trending videos into consideration. This would eventually help the content creator know how authentic their content is and healthy competition to make better content before uploading the video on the platform will be ensured. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), Blockchain, and the Internet of Things are all new technologies impacting people's lives. These technologies can change how we communicate, run our businesses, and even how governments work for their people. Artificial intelligence has disrupted the way traditional marketing practices are conducted and changed how business processes are done. Organizations and governments increasingly turn to artificial intelligence (AI) to improve customer experience, operational efficiency, fraud detection, and cyber security. The revolutionary buzzword, artificial intelligence (AI), has transformed our personal and professional lives. Industry 4.0 considers AIadoption significant due to its potential benefits. Since its inception, it has presented several possibilities and difficulties to various businesses. As a result, several AI-powered technologies have been created, and they have the potential to raise significantly living standards while also boosting the economy. This paper has conducted a conducive study of the marketing tools and techniques that adopt AI while looking through the loopholes to suggest howAI can be adopted quickly into the day-to-day lives of the human race. Based on this, it has recommended a course of action for India that entails the development of infrastructure, policies and rules, research and development, and humanresources. It is necessary for all parties involved to gather and address these problems. Infrastructure development, applications in the public sector, policy & regulation, technological development, and human resource development are all key responsibilities of the government. However, with the assistance of business, they may be accomplished effectively. For this study, the authors have employed secondary data. Future empirical studies might be conducted to compare the development of artificial intelligence technology in India to that of other emerging nations. The study is based on secondary data to demonstrate the development of artificial intelligence technology in India and overseas. However, empirical research may be conducted in the future. The writers' original points of view are presented in the article. [ABSTRACT FROM AUTHOR]

In the world of technology, where technology helps to explore almost everything, including outer space, planets, etc. However, due to the unknown extreme conditions at unexplored places, there is an interest and need to develop a technology which helps explore more about space. Here, we attempted to develop the Artificial Intelligence (AI) enabled rover model to be used for such space exploration scenarios. In this paper, firstly, finite element method (FEM) based design and analysis of the rover model are discussed. The operational and constructive features are explained, such as the real-time camera feed feature, measuring the temperature and humidity values, and detecting the object while measuring the obstacle distance. The AI-enabled rover model uses a real-time object detection algorithm which helps to analyze the object in a real-time manner. The rover model is designed in such a way that it can easily climb on different surfaces having obstacles. The rover model is then fabricated, where wheels are made from a buoyant substance such as polyvinyl chloride (PVC). A special suspension frame based on a modified rocker-bogie system is created to adapt the walker to uneven ground. This means that even in hostile surroundings, the rover can explore independently. The proposed model has a comparable cost as compared with published literature work. [ABSTRACT FROM AUTHOR]

Technologies focusing on the visually impaired play an important role in assisting the visually challenged and easing their living standards. Previously there have been several other technologies and papers proposed under this category to help the visually challenged. Applications have been built, and are being developed, to help these people work independently without anybody else's need and complete daily tasks easily, without any difficulty using Artificial Intelligence. The proposed application, Noon Gil, supports voice commands and performs operations accordingly using architectures and algorithms like The technologies used are Optical Character Recognition (OCR), Convolutional Neural Networks (CNNs), Natural Language Processing (NLP), Mobile Vision API, TensorFlow Lite, Google ML Kit, MobileNet SSD, etc. Our project which is an android application with an overall accuracy of 94.74% comprises three main functions: Text Detection with an accuracy of 90.83%, Object Detection with 94.40% accuracy and barcode scanning with 99%. [ABSTRACT FROM AUTHOR]

Artificial Intelligence is an incessantly evolving and progressing technology. Machines can exhibit humanoid intelligence, every now and then even better than humans. Its models are being extensively used in today's sphere. It is due to the supremacy of data and artificial intelligence. However, in Machine Learning, the data is amassed through numerous devices, including smart gadgets like smart watches, laptops, mobile phones, etc., and is transported to a centralized server. These devices are also called edge devices. When the personal data of users is transferred to the servers where it is used to train models it creates issues related to data privacy. Federated Learning (FL) is contemporary to technologies like Blockchain, on-device AI, IOT, and Edge computing where private/personal data of the user is not sent on the server, rather training of models is carried out locally, on each device. While the nodes are learning continuous communication between them takes place in Federated Learning. Therefore, high bandwidth connections that can exchange parameters of the machine learning model along with adequate computing power and memory of the local devices are desired. Therefore, one of the major challenges involved in FL includes communication efficiency. This paper presents a survey about FL and discusses the recent developments related to overcoming constraints in communication efficiency in Federated Machine Learning. [ABSTRACT FROM AUTHOR]

The paper considers the problem of using end-to-end digital technologies and platform solutions using elements of artificial intelligence. Identification of goods prohibited to be transported across the customs border is accepted as the main object of research. Problematic issues of unambiguous identification of prohibited goods at the border with the use of inspection and inspection complexes are formulated. The dual energy method for recognizing the materials of a controlled object by the effective atomic number and the mathematical foundations of a computed tomography are outlined. Recommendations on the implementation of the method of nonlinear inverse projection and nonlinear tomosynthesis at a small number of projection angles of the controlled object of the developed model in practice are given. Around the world, the time of customs clearance of foreign trade cargoes is one of the key criteria for assessing the effectiveness of the customs service. The use of end-to-end digital technologies and platform solutions using artificial intelligence elements and decision support systems will make it possible to carry out customs control "invisibly" and quickly throughout the entire chain of goods movement [1]. As a tool to speed up customs procedures, prevent and suppress offenses at the border, high-tech equipment is used, including large-sized inspection complexes (IC). Currently, the customs authorities of the Republic of Uzbekistan are equipped with modern IC, which allow you to get an x-ray image of the vehicle and the goods transported in it. However, the analysis of X-ray images and the detection of items prohibited for transportation in them requires high qualifications from a customs officer. Consequently, the task of studying the methods of artificial intelligence and recognition of goods prohibited for transport across the customs border is relevant. Therefore, the task of researching artificial intelligence methods and automatic recognition of goods prohibited for transportation across the customs border is relevant. [ABSTRACT FROM AUTHOR]

Mental stress is one of the major contributors to a variety of health issues. Various measures and diagnoses have been created by neurologists and psychiatrists to determine the intensity of mental stress in its early phases. In the literature, several neuroimaging devices and methods for assessing mental stress have been presented. The key candidate chosen is the electroencephalogram (EEG) signal which contains valuable information regarding mental states and conditions. This paper presents reviews of current works on EEG signal analysis for assessing mental stress. The reviews emphasize the significant disparities in the research outcomes and claims of different results from various data analysis methodologies. Accordingly, methods of EEG signals analysis will be used to study the effect of various extracted features and classification methods that associate with mental stress. Apart from that, the utilization of Artificial Intelligence (AI) approach is also investigated to study its significance towards stress detection. [ABSTRACT FROM AUTHOR]

Nowadays the use of Artificial Intelligence (AI) around the globe is constantly growing. These processes were accelerated even more due to the COVID-19 pandemic. In the cybersecurity realm, the real implementations of AI solutions are also constantly growing. For some enterprises, AI is considered more as a risk for overall cybersecurity while others see AI as the way forward to achieve cyber resilience. That kind of uncertainty points out that cybersecurity leaders are still not united around AI and do not fully understand the effects of utilizing it. That lack of understanding is emphasizing again the need for more research into AI for cybersecurity and in addition to that the urgency of attracting young talent to the cybersecurity career path. On the other hand, cyber threat actors are getting more and more sophisticated and may already be on the way to integrating AI into their future attacks. In this paper, we are analyzing the artificial intelligence methods for cybersecurity in Industry 4.0. In addition, we detail the challenges, motivations, and pre-conditions to be taken into consideration when using these AI methods for improving overall cybersecurity in Industry 4.0. [ABSTRACT FROM AUTHOR]