Preface

This book focuses on recent advances, roles and benefits of fog, edge, and pervasive computing for intelligent and smart Internet of Things (IoT) enabled applications, aimed at narrowing the increasing gap. This book aims to describe the different techniques of intelligent systems from a practical point of view: solving common life problems. But this book also brings a valuable point of view to engineers and businessmen, trying to solve practical, economical, or technical problems in the field of their company activities or expertise. The purely practical approach helps to transmit the idea and the aim of the author is to communicate the way to approach and to cope with problems that would be intractable in any other way. This book solicits contributions which include theory, applications, and design methods of intelligent systems, Ubiquitous techniques, trends of fog, edge, and cloud applications as embedded in the fields of engineering, computer science, mathematics, and life sciences, as well as the methodologies behind them.

Book Objectives

With the rapid growth and emerging development in artificial technology, novel hybrid and intelligent IoT, edge, fog driven, and pervasive computing techniques are an important part of our daily lives. These technologies are utilized in various engineering, industrial, smart farming, video security surveillance, VANETs and vision augmented driven applications. These applications required real time processing of associated data and work on the principle of computational resource oriented meta heuristic and machine learning algorithms. Due to physical size limitations, small computing IoT and mobile devices are having resource limited constraints with low computing power and are unable to manage good quality of service and related parameters for distinguished applications. To overcome the limitations of such mobile devices edge/fog and pervasive computing have been proposed as a promising research area to carry out high end infrastructure usage and provide computation, storage and task execution effectively for end device users. As edge/fog computing is implemented at network edges, it promises low latency as well as agile computation augmenting services for device users. To successfully support intelligent IoT applications, therefore, there is a significant need for (1) exploring the efficient deployment of edge/fog/pervasive computing services at the network nodes level, (2) identifying the novel algorithm related to fog/edge/pervasive computing for resource allocation with low constraint and power usage, and (3) designing collaborative and distributed architectures specialized for edge/fog/pervasive computing.

Target Audience

The target audience of book is professionals and practitioners in the field of intelligent system, edge computing and cloud enabled applications and ubiquitous computing science paradigm may benefit directly from others' experiences. Graduate and master students of final projects and particular courses in intelligent system, edge and fog based real-life applications or medical domain can take advantage, making the book interesting for engineering and medical university teaching purposes. The research community of intelligent systems, sensor applications and intelligent sensor-based applications, consisting of many conferences, workshops, journals and other books, will take this as a reference book.

Organization

Chapter 1 describes the Internet of Things, fog, edge and pervasive computing are emerging technologies, having several promising applications including healthcare. These technologies are witnessing a paradigm shift in the healthcare sector moving out from traditional ways of visiting hospitals. It connects the doctors, patients, and nurses through smart intelligent sensor devices at low cost with high bandwidth network. In this chapter, authors discussed new computing paradigms precisely and present their applications in ubiquitous healthcare. This chapter also covers various problems and challenges that have been faced by the practitioners in the last few years in the field of cloud computing and IoT that has been solved by fog, edge and pervasive computing.

Chapter 2 discusses difficulties and future headings to investigate the role of fog, edge and pervasive computing. Studies have revealed that fog/edge computing (FEC) based organizations can expect an essential activity in expanding the cloud by means of finishing go-between organizations at the edge of the framework. Dimness/edge computing-based IoT's (FECIoT) appropriated configuration overhauls organization provisioning along the cloud-to-things continuum, thus making it sensible for key applications. Edge and fog registering are firmly related - both allude to the capacity to process information closer to the requester/buyer to lessen idleness cost and increment client experience. Both can channel information before it "hits" a major information lake for further utilization, lessening the measure of information that should be handled.

Chapter 3 addresses the technique selection issue encountered during the requirements elicitation stage, through a proposed machine learning model to transfer the experts' knowledge of elicitation technique selection to the less experienced. Based on the system analysts, stakeholders automate various techniques to provide the best optimization technique nomination.

Chapter 4 covers the advantages and disadvantages of using machine learning in edge/fog/pervasive computing. The various studies carried out by researchers is also covered. Every field has numerous applications, and in this chapter we discuss a few possible applications in this fog era using machine learning techniques. By the end of the chapter you should know about ML frameworks and the various machine learning algorithms used for fog/edge computing.

Chapter 5 provides a description of the software which has three modules: student, librarian and admin. These modules have unique features for searching for library books with the title, author's name, subject, ISBN/ISSN, etc. Within the chapter the interfaces of the software are shown as images which is an abstraction that may be developed on available mobile operating system like iOS, Android, etc. The interfaces are designed bearing in mind that it will be used on cross platform environments fulfilling minimum requirements using the IoT available in the market. Furthermore, overall information is preserved with the help of cloud storage while keeping parallel options for physical storage on the destination master computer. The cloud-based system has given library management a new dimension while giving a new feature referred as "management on the go" as a web or abstract GUI.

Chapter 6 describes a systematic review that was conducted to determine work done by various publishers on kidney cancer and to spot the research gaps between the studies so far. The outcome of this study permitted the effective diagnose of kidney cancer or renal cancer carried out using an adaptive neuro fuzzy method with 94% accuracy. Although, many data mining techniques were applied by researchers, the accuracy of these methods was less than the adaptive neuro fuzzy method. This method is worthwhile to identify the diagnosis of renal cancer better and more rigorously.

Chapter 7 explains a proposed approach to use edge computing in a transportation and route-finding process in order to handle performance issues. Huge demand for centralized cloud computing poses severe challenges such as degraded spectral efficiency, high latency, poor connection, and security issues. To handle these issues, fog computing and edge computing has come into existence. One application of cloud computing is location based services (LBS). Intelligent transport systems being the important application of LBS rely on GPS, sensors, and spatial databases for convenient transport facilities. These location-based applications are highly dependent on external systems like GPS devices and map API's (cloud support) for the spatial data and location information. These applications acquire spatial data using API's from different proprietary service providers. The dependency on the API's and GPS devices, create challenges for effective fleet management and routing process in dead zones. Dead zones are areas where no cellular coverage exists.

Chapter 8 describes the simulation and design of an optimized low-cost comb drive based acoustic MEMS sensor. These sensors would be useful for condition monitoring of automobiles on the basis of changes in sound waves emerging from malfunctioning or defective parts of automobiles. These sensors can be developed from silicon substrates. Simulation is done using COMSOL Multiphysics simulation software based on finite element analysis. This optimized sensor is sensitive for the frequency range of 30-300?Hz. This frequency range was obtained after the FFT analysis of various signals received from engines using MATLAB software.

Chapter 9 offers an outline of developing the Internet of Things (IoT) technology in the area of healthcare as a flourishing research and experimental trend at the present time. The main advantages and benefits are considered in this chapter. In recent times, several studies in the healthcare information system proposed that the disintegration of health information is one of the most significant challenges in the arrangement of patient medical records. As a result, in this chapter, we provide an detailed design...