Internet of Everything for Smart City and Smart Healthcare Applications

The economic value of the industrial, smart city, home, and many more transformations by Internet of Things (IoT) across all industries is estimated to be trillions of dollars, and the societal impact on energy efficiency, health, and productivity is enormous. When sensing and intelligence are built into every smart gadget, there is a heightened risk of misuse in addition to any potential benefits. The increased complexity needed to manage IoT devices safely and securely is one of the main issues with their growing quantity. This increased complexity creates new safety, security, privacy, and usability challenges far beyond the difficult challenges individuals face just securing a single device. Herewith, researchers are trying to point out some of the bad trends that smart devices and collections of devices bring about and make the case that problems with security, physical safety, privacy, and usability are intricately intertwined and require simultaneous answers. Tight safety and security standards for individual devices based on existing technology are needed. Likewise, research that identifies the most effective method for people to reliably manage collections of devices must direct the development of such systems in the future.

In the world of rapidly mounting businesses, the focus of business organizations is to gain profit and retain their customers committed to them consistently. In addition, the globalization effects have witnessed a humongous surge in competition among companies. One of the prominent factors that act as a driving force for companies to sustain among competitors is the forecasting of sales based on products and promotions available that help in the effective handling of revenue and inventory. Moreover, it also warrants a minimal loss. Accurate prediction of sales is possible only through the establishment of a strong bond with customers and by an apposite understanding of the market requirement. This study involves the prediction of sales data wherein, initially, the performances of existing linear models are compared with that of the deep learning models based on the available data, which includes regression models, recurrent neural network (RNN), long short-term memory (LSTM), and so on. This work also suggests an improved model that provides more optimized results on the data used than all other compared models.

Blockchain technology enables reliable, secure, traceable, distributed, and fault-tolerant data storage. With the emergence of smart contracts (programs that run above the blockchain), the technology is no longer used only for financial purposes but also for more complex applications. This chapter aims to present the fundamental characteristics of blockchain and how it works. We show the main use cases of blockchain and examples of their use focused on the health area. Also, we discuss the application scenarios and the challenges to be overcome for the implementation and deployment of the technology.

The fifth-generation mobile network (5G) is expected to turn smart cities’ theoretical deployment into reality, offering ultra-reliable and low-latency communications (uRLLC), massive machine-type communications (mMTC), and enhanced mobile broadband (eMBB) [1], thus improving numerous areas of urban life (Khan et al., IEEE Commun Surv Tutor 22:196–248, 2020). Correspondingly, 5G will deliver the advanced technologies of software-defined networking (SDN), network function virtualization (NFV), network slicing (NS), and cloud computing, with the goal of meeting these new performance requirements (Sicari et al., Comput Netw 179, 2020). While these novel technologies improve the ease of deployment when it comes to smart city applications and use cases, they are also responsible for a new set of vulnerabilities on top of already inherited threats and challenges from their predecessors, 4G networks. An expanded and challenging network security surface is thus formed, where threats and accidents can lead to acute repercussions in the ecosystem of suppliers, vendors, operators, and end users (Ericsson, A guide to 5G network security 2.0 (287-01 FBG 101 0955 Rev), 2021; Stallings, Cryptography and network security: principles and practice. Pearson Higher Education, 2020).

Two of the actors that rely on wireless communications are tactical and public safety networks, including the military, the police, and rescue personnel (Larsen et al., Wirel Commun Mob Comput 2018:4860212, 2018). 5G networks are expected to deal with the data sharing and processing of systems that are responsible for public safety and national security, with the aim of providing computational resources through cloud computing and reliable connectivity through new radio access technologies (RATs) (Bastos et al., 2021 international conference on military communication and information systems (ICMCIS), 2021). A hybrid architecture will be deployed, consisting of both tactical network bubbles and commercial network infrastructures, thus making the assurance of the confidentiality, the integrity, and the availability of mission-critical applications and sensitive information challenging as the threat landscape widens (Larsen et al., Wirel Commun Mob Comput 2018:4860212, 2018). Such privacy solutions will also impact 5G applications such as Internet of Things (IoT) healthcare directly. The healthcare industry has recently adopted IoT for its wide capabilities while still managing to stay inexpensive and easily accessible. The development of security mechanisms is crucial in smart health, due to both the sensitivity of the data collected and the danger an attack poses to the patient’s well-being or, even, their life (Liao and Ou, 2020 IEEE international conference on advances in electrical engineering and computer applications (AEECA). 2020).

This work is organized as follows. Firstly, the privacy and security issues that stem from 5G’s novel technologies and affect critical networks will be briefly presented. An introduction to next-generation security architectures and technologies that will fulfill the security and privacy requirements of public safety and smart health systems will also be provided. Proceeding, a thorough review of the main vulnerabilities and proposed solutions for secure military communications is presented. Adversaries and attack vectors of commercial and tactical 5G networks will be categorized, and solutions are surveyed. Finally, a smart health architecture is presented to protect against a variety of security and privacy concerns, taking into consideration its scalability as well as ease of applicability.

The process of the development of smart cities is already progressing. Smart city development can be divided into several classifications, such as smart parking, smart rendezvous points, smart healthcare facilities, smart traffic control, smart communications, smart crime control, etc. Smart traffic control and smart communication are the target areas of discussion for this chapter. These two areas together form a network of vehicles and other transportation units, along with infrastructure units, to not only provide safety on the roads but also take care of the infotainment services. As the traffic on roads is increasing rapidly, the need to use intelligent solutions from Industry 3.0 became a must. One major solution is to let the vehicles communicate with each other. Researchers have been working on vehicular ad hoc networks for over a decade. In the recent past, researchers released Release 16, which focused on the development of Fifth-Generation New Radio Vehicle-to-Everything Communication (5G NR V2X). The goal is to use the resources in such a way that the advantages of millimeter-wave communication are fully exploited. This chapter describes vehicular ad hoc networks, LTE-V2X communications, and 5G NR V2X communication, among other topics. Some problems are there with the 5G NR V2X communications, such as the initial access problem, higher attenuation of millimeter waves, non-line-of-sight communication, etc. This chapter presents a detailed description of these problems and their probable solutions. Further, with the recent Industry 4.0 advancements in the areas of artificial intelligence and machine learning, optimal solutions to the above problems can be found. This chapter also discusses the methods of machine learning that are used or can be used in the solutions to the problems of 5G NR V2X communications. Each issue of 5G NR V2X communication is discussed in detail, along with the probable solutions with or without the use of machine learning algorithms.

The exponential increase in population, urbanisation, climate change and other artificial issues has led to the prospective demand and growth of smart cities. This exponential growth has attracted the attention of multiple researchers, and various kinds of research have been conducted to ascertain the feasibility, challenges and opportunities presented by smart cities. In this chapter, a holistic analysis was made to bring forth the opportunities brought about by smart cities, the challenges faced while developing them and the issues faced by the residents with a clear focus on design, implementation, policies, systems and services. The problems are categorised in terms of data (security, policies, storage and usage), residents (infrastructure, governance, environment and migration) and design (implementation, systems and services). It was noted that there is a need to maximise the use of renewable energy, implement policies that adhere to the standard quality of life, increase public-private partnerships and ensure that right to information is truly available. It was also recommended that future researchers adopt a multidisciplinary approach to analysing smart cities and adopt the latest tool and technologies.

Smart city also an intellectual city has transformed the quality of life of the people. Due to rapid urbanization, the balance between supply and demand got changed. Smart solutions to ease the way of finding between the various applications like transport, energy, environment, warehouse, water management, and waste management have proved to be beneficial for human wellbeing. The relationship between sensors and applications through the Internet of Things (IoT) has proved that human efforts can be minimized. Various physical, chemical, biological, and biomedical sensors have a vital role to play in data collection. The sensors’ data is collected, stored, and analyzed in the cloud. This chapter focuses on the applications of the smart city.

In existing bus operation systems, the on-board passenger delay is always neglected. With the aim to make the trade-off between stop passengers and on-board passengers, a bi-objective study on a bus operation system is carried out to minimize the stop passenger delay as well as the on-board passenger delay for smart cities. The bus operating system is formulated as a mixed logical optimization model incorporating both speed control and holding time control and is transformed into a mixed-integer nonlinear programming (MINLP) problem, which is analyzed by comparing the corresponding bus movement characteristics under two different objectives. On the other hand, to satisfy a compromise between two types of passengers, a bi-objective bus operation problem is proposed and solved by the non-dominated sorting genetic algorithm II (NSGA-II) and non-dominated sorting harmony search (NSHS) algorithm, respectively. The comparison of two algorithms is conducted in the simulation to illustrate associated efficiencies.

Traffic accidents are a major cause of death around the world. Traffic accidents lead to traffic congestion and occur frequently in urban scenarios. In this, traffic accidents are one of the most common causes of death all around the world. A quick response to traffic accidents is crucial to saving a life. With connected vehicle technology, vehicles generate data such as velocity, acceleration, position, etc. which can be periodical. These data can be collected using connected vehicle technology such as cellular, 802.11p, etc. In this chapter, with the growing popularity of smart cities, we focus on the detection of traffic accidents using connected vehicle data under various constraints. After accident detection, steps to send an ambulance, tow trucks, etc. can be taken to save lives and clear roads for traffic flow. The collected data is aggregated to detect accidents in a time- and resource-efficient manner. Here, two approaches are utilized: (i) time aggregation and (ii) position and time aggregation. In time aggregation, the vehicle data for 10 s is aggregated, whereas, in position and time aggregation, all vehicle data within the 50 m range for 10 s is aggregated. In this work, classification modeling algorithms such as support vector machine (SVM), linear and nonlinear kernels, and gradient tree boosting (GTB) are used to detect accidents. Various data features such as vehicle ID number, vehicle type, position, speed, accelerations, and lane change information of vehicles are considered to detect accidents on the road. Finally, comparative results are demonstrated in terms of accuracy, precision, recall, and F-score parameters to validate the performance of the models.

A growing movement called the Internet of Things will give the current healthcare industry a new dimension. The advantage over the currently employed conventional approaches in the healthcare industry will be provided by IoT-based e-health solutions like smart infusion pumps, smart monitoring, and health TV. The e-health solutions provided by IoT devices are more precise and responsible in the context of the IoT environment, which offers a number of difficulties along with great possibilities in the field. In the healthcare industry, social and financial considerations are equally crucial in addition to accessibility, cost, and quality. As a result, several companies have developed various business models for altering healthcare systems in order to have an immediate impact on users, especially patients, their families, and the communities in which they reside. Profit generating is the basic goal of every business plan. It is nothing more than a well-organized framework that allows a company to understand its main customers, partners, suppliers, revenue streams, and cost structure. This in turn provides a picture of a company’s identity, strategy, competitors, etc. A more accurate representation of the business’ capabilities, competencies, and customer and client response would be shown.

Population ageing is occurring at a very fast pace all over the world, which has a significant impact on all aspects of society. It is imperative to ensure that every human being lives with dignity and equality in a healthy environment; this requires an inclusive, comprehensive and prevention-oriented response.

According to this thinking, there are challenges and opportunities related to these demographic changes that require forward-looking policies. These policies are necessary to ensure inclusive and active ageing and active life strategies, quality and well-being and should also focus on contributing to a high quality of life. Every person – in every country in the world – should have the opportunity to live a long and healthy life.

In this context, the role of technology has proven fundamental in the development of solutions to promote medical health, provide wellness care and help caregivers. There are several technologies that have proven promising, such as virtual reality, augmented reality, mixed reality and machine learning.

This chapter presents work aimed at the elderly population, prototyping technology-based solutions for creating mechanisms for measuring and promoting well-being. In addition, it presents support mechanisms for the activities of caregivers in nursing homes, as a way to empower caregivers and ensure better health and well-being.

The Fifth-Generation Mobile Networks (5G) contribute to the growth of mobile applications and services and the increase of connected Internet of Things (IoT) devices by providing an infrastructure for upcoming necessities. One of the crucial scenarios in 5G and IoT is the Internet of Healthcare Things (IoHT), where many unexplored services emerge to improve the patient’s quality of life. However, there are challenges for infrastructure requirements to support data traffic growth while promoting a reduction in energy usage. Edge Computing (EC) and Network Slicing (NS) are two supporting paradigms for data-intensive and low-latency applications that enable the host of virtualized resources in 5G. However, the arrangement of computing resources in different levels and nodes is a critical challenge, followed by constraints, requirements, and performance goals. Furthermore, since IoHT applications present demanding necessities regarding latency and throughput, such as high-quality video streaming, virtual and augmented reality, computer vision, and intelligent signal processing, the adoption of application placement strategies is essential to improve the performance of these services. This chapter presents a review of EC and NS in the context of IoHT for 5G.

5G technology provides a greater presence and ubiquitous use of artificial intelligence that transforms all daily routines and, consequently, people’s lives. With the increasing use of IoT in all environments, which include each one’s homes, it requires citizens to have digital skills to be able to enjoy all these potentialities. The problem will be for info-excluded citizens who do not have digital skills and, as such, will not be able to have a better quality of life and health. In this context, the elderly constitutes the most info-excluded range of citizens. In this sense, it is important to reflect and find measures and proposals so that the elderly can have a better quality of health and life with the use of emerging technologies and artificial intelligence that the IoT makes available.