Preface

Today, 5G communication, cloud computing, the internet of things (IoT), robotics, and the feasibility of artificial intelligence (AI) computing algorithms are contributing to redefining ubiquitous and pervasive computing. We live in an age of digital transformation where connectivity is more and more visible to end users. We are also experiencing new business models, transformations in industry, and the adoption of new applications and computing frameworks, with both hardware and software in a process of continuous redefinition.

The aim of *Ubiquitous and Pervasive Computing – New Trends and Opportunities* is to outline the novel and interdisciplinary concepts in this research area that we can expect to see during the next ten years, with their associated challenges. The chapters focus on data science, the internet of things, big data, Industry 4.0, high-performance computing, cybersecurity, intelligent applications, and cloud computing environments. A collection of old and new topics relevant to ubiquitous and pervasive computing are discussed throughout the book. Sometimes, old issues are revisited with a new vision. For example, the internet is being redefined with 5G mobile communication and IoT protocols. We are confident that we are passing through a revolution that is in its infancy. In the next ten years, the internet, connectivity, and AI services will be increasingly present in our daily lives in a totally transparent way. It is essential to tackle the security, and specifically privacy, concerns that follow from this revolution. In this context, the move towards implementation of GDPR (General Data Protection Regulation) rules is a very positive one.

The book is divided into two sections: "New Algorithms and Frameworks" and "Smart Environments". The first section opens with a discussion of resource allocation in a distributed system, and explores novel topics such as quality of experience, quality of context and user satisfaction, and their relevance to the success of scheduling algorithms. The aim should be a satisfactory trade-off between (i) optimization, risk minimization and enhancement of income, and (ii) user satisfaction, quality of experience and quality of the offered context. Chapter 2 introduces a novel hybrid genetic optimization algorithm to analyze differential evolution in populations. Chapter 3 considers the increasing use by companies of big-data frameworks for decisionmaking, detailing the use of artificial intelligence and machine learning algorithms that employ the Hadoop MapReduce computing style for niche applications.

The second section presents three chapters that explore intelligent cities and the smart transformation of living environments. Chapter 4 connects Industry 4.0, the internet of things, and cybersecurity through a study of the use of IoT in a smart home, detailing aspects such as stakeholders in security solutions and privacy concerns. Chapter 5 introduces an edge‒fog‒cloud architecture for health services. The proposed architecture captures vital signs relevant to long Covid across the entire population and brings this data to the edge. Health services are executed in the fog, detecting health problems in individuals or groups through the use of serverless computing and federated

learning. Chapter 6 addresses the mapping of social functions in an intelligent city. From a computational social science perspective, land-use details can be obtained through mobile phone data. Classification engines are used by machine-learning algorithms use to gain insights into the field of urban computing.

I would like to thank Author Service Manager Nika Karamatic for her hard work and excellent support. Also, I thank all the authors for their contributions, which will be useful for ubiquitous computing lectures and research purposes.

> **Rodrigo da Rosa Righi, Ph.D.** Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos – Unisinos, São Leopoldo, RS, Brazil

> > Section 1

New Algorithms and

Frameworks

Section 1
