Load Balancing Using Artificial Intelligence for Cloud-Enabled Internet of Everything in Healthcare Domain.

In cloud computing, a lot of challenges like the server failures, loss of confidentiality, improper workloads, etc. are still bounding the efficiency of cloud systems in real-world scenarios. For this reason, many research works are being performed to overcome the shortcoming of existing systems. Among them, load balancing seems to be the most critical issue that worsen the performance of the cloud sector, and hence there necessitates the optimal load balancing with optimal task scheduling. With the intention of accomplishing optimal load balancing by effectual task deployment, this paper plans to develop an advanced load balancing model with the assistance acquired from the metaheuristic algorithms. Usually, handling of tasks in cloud system is an NP-hard problem and moreover, nonpreemptive independent tasks are crucial in cloud computing. This paper goes with the introduction of a new optimal load balancing model by considering three major objectives: minimum makespan, priority, and load balancing, respectively. Moreover, a new single-objective function is also defined that incorporates all the three objectives mentioned above. Furthermore, the deployment of tasks must be optimal and for this a new hybrid optimization algorithm referred as Firefly Movement insisted WOA (FM-WOA) is introduced. This FM-WOA is the conceptual amalgamation of standard Whale Optimization Algorithm (WOA) and Firefly (FF) algorithm. Finally, the performances of the proposed FM-WOA model is compared over the conventional models with the intention of proving its efficiency in terms of makespan, task completion (priority), and degree of imbalance as well.

Big data and artificial intelligence based early risk warning system of fire hazard for smart cities

An amazing utilization of internet of things (IoT)-based smart technologies has been observed in recent years. Internet of things (IoT) became smarter and autonomous, leading the way by interconnecting and interacting with the environment. Existing technologies such as big data, AI, and cloud computing have been supported by IoT but with some limitations. Blockchain is the better solution to access and share data with the decentralized system. IoT spreads its applications in healthcare, industrial internet of things, supply chain management, traffic management, etc., out of which smart cities take special attention in recent days by integrating with IoT to create a sustainable ecosystem by using information and communication technology (ICT). Smart cities can offer various smart applications for boosting the life prominence of society. These characteristics of blockchain are beneficial to the creation of smart cities. In this regard, the authors have conducted a systematic review of articles. This study highlights the integration of blockchain with IoT.

New developments in Information and Communication Technology (ICT), such as big data, the Internet of Things (IoT), and blockchain technology provide opportunities for businesses and government organisations to benefit from business-to-government (B2G) information sharing. For example, big data analytics might provide government organisations with knowledge on how to assess risks using the information they receive from businesses. However, B2G information sharing can entail risks as well. Sensitive data could fall in the wrong hands and by that the competitor of the business might obtain this data. In addition, B2G information sharing could be unlawful...

With the rapid development and frequent application of information and communication technology (ICT) in different industrial sectors, the production and manufacturing process relies more on ICT. ICT significantly increases the quality of service and productivity while it comes together with information security risks. As an essential part of a nation and economy, agriculture is provided with many ICT applications. ICT greatly contributes to the weather climate forecast, pest or disease prediction and so on to improve crop yields and food safety. The revolution of the fourth industry accelerates the application of ICT in agriculture and the development of smart agriculture. Smart agriculture is highly based on ICT to improve productivity and reduce waste, loss, and cost, such as big data, sensors, the Internet of things (IoT), artificial intelligence (AI), cloud computing, and so on. All these changes and applications of ICT bring together information security risks. Based on the literature review and content analysis as research methodology, this paper concluded that information security risks are serious and inevitable in agriculture or food security. Therefore the need for information security risks management is significant in agriculture and food security.

Knowledge Management (KM) and Strategic Foresight (SF) are essential for organizational growth, particularly in today’s environment shaped by Information and Communication Technologies (ICT). This study conducts a literature review to investigate the effective integration of KM and SF practices with ICT. It addresses two key research questions: How can KM practices be incorporated into SF processes? How can ICT enhance the management of future-oriented knowledge through SF? The increasing complexity of organizational environments and the challenges posed by information overload and future scenario forecasting highlight the importance of this research. ICT serves as a crucial enabler, utilizing tools such as Big Data analytics, Artificial Intelligence (AI), and the Internet of Things (IoT) to optimize KM and SF practices. However, the integration of these technologies encounters significant barriers that require further exploration. The primary objective of this study is to map the current integration of ICT within KM and SF, emphasizing opportunities, limitations, and the potential contributions of AI to these processes. Utilizing a Rapid Review methodology, which streamlines the systematic review process to provide timely insights, the research involved searches in the Scopus database and a snowballing technique, resulting in an analysis of 12 selected articles. Findings indicate that ICT can significantly improve the efficiency and effectiveness of KM and SF processes, particularly in scenario-building and strategic decision-making. The study identifies specific tools and methods, such as collective knowledge systems and IoT frameworks, that organizations can adopt to enhance these practices. Future research should expand on this groundwork by including larger samples and practical studies to validate the proposed hypotheses. This study aims to encourage organizations to adopt ICT-based solutions, fostering sustainable competitive advantages in dynamic business environments.

In this chapter, a discussion is presented about what Big Data and Internet of Things (IoT) really is and what intricacies are used while building big data and internet of things. Further Big Data and Internet of Things have been used for building an application used for Smart City & Agriculture. A smart city is an urban development vision to integrate multiple information and communication technology (ICT) solutions. Smart city's goal is to improve quality of life with technology to improve the efficiency of services and meet residents' needs. Smart agriculture approach is to develop, transform and reorient agricultural development under new realities of climate change. It increases productivity enhances resilience (adaptation), reduces mitigation with achievement of national food security and development goals. This chapter includes detailed discussion on Smart City and Smart Agriculture along with planning, designing as well as various approaches used to build and implement them effectively.

Currently, cities are being reconstructed to smart cities that use an information and communication technology (ICT) framework alongside the internet of things (IoT) technology to increase efficiency and also share information with the public, helping to improve the quality of government services citizens' welfare. This large, diverse set of information called big data is obtained by ICT and IoT technologies from smart cities. This information does not have any meaning of its own but a high potential to make use of smart city services. Therefore, the information collected is mined and processed through use of big data analytic techniques. The environmental footprints in smart cities can be monitored and controlled with the help of ICT. Big data analytic techniques help enhance the functionalities of smart cities and the 4G and 5G network provides strong connectivity for professional devices.

Swarm intelligence (SI) optimization algorithms are fast and robust global optimization methods, and have attracted significant attention due to their ability to solve complex optimization problems. The underlying idea behind all SI algorithms is similar, and various SI algorithms differ only in their details. In this paper we discuss the algorithmic equivalence of particle swarm optimization (PSO) and various other newer SI algorithms, including the shuffled frog leaping algorithm (SFLA), the group search optimizer (GSO), the firefly algorithm (FA), artificial bee colony algorithm (ABC) and the gravitational search algorithm (GSA). We find that the original versions of SFLA, GSO, FA, ABC, and GSA, are all algorithmically identical to PSO under certain conditions. We discuss their diverse biological motivations and algorithmic details as typically implemented, and show how their differences enhance the diversity of SI research and application. Then we numerically compare SFLA, GSO, FA, ABC, and GSA, with basic and advanced versions on some continuous benchmark functions and combinatorial knapsack problems. Empirical results show that an advanced version of ABC performs best on the continuous benchmark functions, and advanced versions of SFLA and GSA perform best on the combinatorial knapsack problems. We conclude that although these SI algorithms are conceptually equivalent, their implementation details result in notably different performance levels.

Internet of things (IoT) is the global interconnection of several heterogeneous devices. It allows people and “things” to connect anytime and anywhere using a variety of wired or wireless communication networks. It will have its presence in all sectors of human lives including healthcare. The market for the IoT in healthcare is growing steadily. IoT in healthcare helps in effectively managing health and thus improving the quality of life. This chapter provides a brief introduction into IoT in healthcare or the use of IoT in the healthcare domain. It begins by presenting an overview on both IoT and healthcare. It discusses Internet of medical things. It covers various applications of IoT in healthcare. It addresses some benefits and challenges of IoT in healthcare.

In the present research, four meta-heuristic algorithms named Genetic Algorithm (GA), Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) have been used for optimal design of cascade spillway to minimize the construction cost.Usually, the traditional design methods such as Vittal and Porey (VP) method or experimental modeling are used to solve this problem leading to infeasible or near optimal solution.The main novelty of this paper is to use effective methods to solve this complex highly constrained problem.Therefore, due to unique features of meta-heuristic algorithms, these algorithms are used here to minimize the construction cost of cascade spillway as the energy dissipater structure.As the case study, cascade spillway of Tehri dam in India had been chosen.The algorithms results have been compared together and with the VP results.Comparison of the results show the effectiveness and affectivity of these algorithms to solve this optimization problem.In other words, when three-stepped spillway are considered, the results are improved with 16.16%, 16.4%, 17.73% and 17.63% respectively using GA, GSA, PSO and ABC algorithms and in the same manner, for four-stepped spillway, the results are improved 14.5%, 16.1%, 16.45% and 16.05% respectively using GA, GSA, PSO and ABC algorithms in comparison with the VP results.

Internet of Things (IoT) has changed view of people about devices and has paved new ways of interaction. These devices form a powerful network that can be controlled from anywhere anytime. Though this is beauty of IoT but it comes with high price of vulnerability and high load. Broker based IoT protocols enable two way communication. One of these protocols is Message Querying Telemetry Transport (MQTT). Load balancing in IoT is huge problem when it comes to application of such publish subscribe models. This issue provides loophole for adversaries to exploit by attempting various attacks on network e.g. Denial of Service (DoS), Distributed Denial of Service (DDoS) etc. These attacks not only deprive network of its bandwidth but also are threat to confidentiality and privacy of any IoT based system. In this paper, we have tried to investigate load balancing problem by investigating different MQTT based threat models and proposing a UML profile for effective handling of load balancing in IoTs employing MQTT protocol. Intuition of proposed profile is to introduce lightweight extension that can provide a robust load-balanced version of MQTT protocol. Validation of profile is performed through case study of Proactive Technical Support System for HealthCare. From validation it is evident that proposed profile is robust in handling load balancing shortcomings in IoT ecosystems.

This article is single-source introduction to the emerging concept of smart cities. It can be used for familiarizing researchers with the vast scope of research possible in this application domain. The smart is primarily concept, and there is still not clear and consistent definition among practitioners and academia. As simplistic explanation, smart is place where traditional networks and services are made more flexible, efficient, and sustainable with the use of information, digital, and telecommunication technologies to improve the city's operations for the benefit of its inhabitants. Smart cities are greener, safer, faster, and friendlier. The different components of smart include smart infrastructure, smart transportation, smart energy, smart health care, and smart technology. These components are what make the cities smart and efficient. Information and communication technology (ICT) are enabling keys for transforming traditional cities into smart cities. Two closely related emerging technology frameworks, the Internet of Things (IoT) and big data (BD), make smart cities efficient and responsive. The technology has matured enough to allow smart cities to emerge. However, there is much needed in terms of physical infrastructure, smart city, the digital technologies translate into better public services for inhabitants and better use of resources while reducing environmental impacts. One of the formal definitions of the smart is the following: connecting the physical infrastructure, the information-technology infrastructure, the social infrastructure, and the business infrastructure to leverage the collective intelligence of the city [4]. Another formal and comprehensive definition is a smart sustainable is an innovative that uses information and communication technologies (ICTs) and other means to improve quality of life, efficiency of urban operations and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects [12]. A broad overview of various components needed in smart is depicted in Figure 1. Any combination of various smart components can make cities smart. A need not have all the components to be labeled as smart. The number of smart components depends on the cost and available technology.

A inovação tecnológica se mantém como relevante fator de crescimento econômico no contexto capitalista dinâmico, marcado pelo avanço das Tecnologias de Informação e Comunicação (TIC), no qual as organizações articulam capacidades dinâmicas na busca de vantagem competitiva sustentável, principalmente através de competências individuais. Nesse cenário, destacam-se a Indústria 4.0 (I4.0) e a Transformação Digital (TD), que inclui Big Data, Internet of Things (IoT) e Artificial Intelligence (AI), com ferramentas baseadas em algoritmos complexos, machine learning e deep learning. Podem servir à mineração de dados, análises preditivas e interação com pessoas através de Agentes Virtuais Inteligentes (AVI) que utilizam linguagem natural e aprendizado contínuo, formas de emular habilidades humanas complexas. Deste modo, os elementos da TD se apresentam como novas tecnologias que impactam a Organização do Trabalho (OT) e intensificam os desafios relacionados à integração da função estratégica da Gestão de Recursos Humanos (GRH), suas práticas e instrumentos, com exemplos de produtos (como HR analytics, people analytics e Artificial Intelligence, oferecidos por startups/spin-offs de HR Tech. Sob essas perspectivas, é proposto discutir o uso de IA (Computação Cognitiva) a partir do caso de um banco brasileiro, inicialmente através da percepção de seus funcionáros, atendidos por um AVI que presta informações sobre os produtos e serviços desta empresa, atividade normalmente atribuída aos atendentes do departamento de contact center. Como complemento, buscou-se observar se o uso dessa nova tecnologia, voltada a processos bancários, também inclui processos de RH.

Internet of things (IoT) enables machine-to-machine, human-to-human and machine-to-human interaction. Recent advancement in IoT systems has positively impacted the daily activities of humans, from accessing information to the delivery of service in real-time. This has improved healthcare management and services, especially in medical hospitals, for effective and timely access to diagnostic information and treatment of patients. Several existing research mainly focused on the design of IoT architecture, its challenges, and benefits to human society with minor or without considering applying IoT in the healthcare domain. To bridge this gap, this study investigates the implications of IoT integration in the healthcare management domain. It presents a detailed discussion on IoT utilization to improve the functionalities of hospital management system. It also discusses some potential emerging innovations that aids the development and application of IoT in hospital management systems. Investigations show that healthcare personnel can administer treatments to patients anytime–anywhere. Patients, especially the elderly are administered treatment, as well as monitoring their wellbeing while at home with the support of wearable sensor devices. Also, some of the challenges that impedes the integration of IoT application into healthcare domain includes generation of irrelevant huge amount of data, issues of security and privacy of patient information and high cost of IoT adoption. Furthermore, the future research trends in adoption of IoT to improve healthcare domain includes stroke and epileptic seizure predictions and prosthetic sensors which is used to retrieve relevant data or information to aid the treatment of a patient in real-time.