Meet the editor

Fausto Pedro García Márquez has been a full professor at the University of Castilla–La Mancha (UCLM), Spain, since 2013. He is an honorary senior research fellow at Birmingham University, UK, and a lecturer at the Postgraduate European Institute. From 2013 to 2014, Dr. Márquez was a senior manager at Accenture. He obtained his European Ph.D. with a maximum distinction. He has been awarded several prizes, including the Runner

(2020) and Advancement Prizes (2018) for Management Science and Engineering Management; First International Business Ideas Competition Award (2017); Runner (2015), Advancement (2013), and Silver (2012) Prizes from the International Society of Management Science and Engineering Management (ICMSEM); and Best Paper Award, *Renewable Energy* (2015). He has published more than 150 papers in reputable journals. He is the author and editor of thirty-one books and five patents. He is an editor for five international journals and a committee member of more than forty international conferences. He has been the principal investigator for four European projects, six national projects, and more than 150 projects for universities and companies. His main interests are artificial intelligence, maintenance, management, renewable energy, transport, advanced analytics, and data science. He is an expert in the European Union in AI4People (EISMD), and ESF. He is also the director of the Ingenium Research Group.

Contents

Introductory Chapter: Internet of Things

The Internet of Things Space Infrastructure. Current State

*by Mikhail Ilchenko, Teodor Narytnyk, Vladimir Prisyazhny,* 

An IoT Based Cloud Deployment Framework for Effective

Compound Cryptography for Internet of Things Based Industrial

Smart Home Monitoring System Using ESP32 Microcontrollers

*by Fausto Pedro García Márquez*

and Development Prospects

*by Ahmad J. Showail*

Automation *by J.S. Prasath*

*Segii Kapshtyk and Sergey Matvienko*

Internet of Things Security and Privacy

Classification of Machine Conditions *by Ganga Dhandapani and V. Ramachandran*

*by Marek Babiuch and Jiri Postulka*

**Preface XI**

**Chapter 1 1**

**Chapter 2 5**

**Chapter 3 25**

**Chapter 4 39**

**Chapter 5 63**

**Chapter 6 81**

## Contents


Preface

This book provides relevant theoretical frameworks and the latest empirical research findings in the Internet of Things (IoT). It is written for professionals who want to improve their understanding of the strategic role of the IoT at the global economy level, at networks and organizations, in teams and work groups, in information systems, and at the level of individuals as players in networked

The IoT is a closed-loop system in which a set of sensors is connected to servers via a network. The data from sensors are stored in a database and then analysed by IoT analytics. The results are usually employed by either humans, machines, or software to make decisions to the operation of the system. The system is a general one that uses different types of sensors that monitor things such as weather conditions,

New data science techniques have appeared in the last few years to solve the complex and robust problems generated in the IoT. The volume, variety, velocity, complexity, and so on of the data obtained by the IoT require new approaches to solve problems in which quality and computational cost are the main variables. Some problems to be addressed by the IoT are maintenance, management, optimization, planning, decision-making, operations management/research, safety, and security in fields such as transportation, energy, banking/finance, social science, media, and marketing. IoT is related to the concept of "smart" technology, such as smart cars, smart homes,

Simulation methods are employed to determine the design of a future IoT system, therefore, an anticipated load generated by its sensors. The results can be compared

Statistics and machine learning are methods applied to IoT analytics. These include multivariable linear regression, time series forecasting, dimensionality reduction, clustering, classification, artificial neural networks, support vector machines, and hidden Markov models. These types of methods can be used individually or in

Performance evaluation and modeling are operations research techniques. They are employed mainly to study the computing facilities used in fog computing and high-layer server(s). They are also applied to the supporting IP network that provides connectivity between sensors, actuators, fog computing devices, and higher-layer servers. These techniques can also be utilized in sensors and actuators to set the capacity of any IoT system or any of its layers. Performance evaluation is also considered for the computational time employed for the IoT, mainly due to the end-to-end response time. It is applied to working IoT, but it cannot be employed to design IoT because of many unknown parameters. In this case, it is employed as a prototype or a model, the former being the most expensive and the latter being the

smart cities, smart manufacturing, smart banking, and more.

environments.

images, velocity, and more.

with real ones, leading to conclusions.

combination.

the most utilised.
