Ethical and Social Aspects of Self-Driving Cars

As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.Comment: 11 pages, 3 figures, 2 table

Aggregate Farming in the Cloud: The AFarCloud ECSEL project

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques.publishedVersio

Building a Simple Smart Factory

This thesis describes (a) the search and findings of smart factories and their enabling technologies (b) the methodology to build or retrofit a smart factory and (c) the building and operation of a simple smart factory using the methodology. A factory is an industrial site with large buildings and collection of machines, which are operated by persons to manufacture goods and services. These factories are made smart by incorporating sensing, processing, and autonomous responding capabilities. Developments in four main areas (a) sensor capabilities (b) communication capabilities (c) storing and processing huge amount of data and (d) better utilization of technology in management and further development have contributed significantly for this incorporation of smartness to factories. There is a flurry of literature in each of the above four topics and their combinations. The findings from the literature can be summarized in the following way. Sensors detect or measure a physical property and records, indicates, or otherwise responds to it. In real-time, they can make a very large amount of observations. Internet is a global computer network providing a variety of information and communication facilities and the internet of things, IoT, is the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data. Big data handling and the provision of data services are achieved through cloud computing. Due to the availability of computing power, big data can be handled and analyzed under different classifications using several different analytics. The results from these analytics can be used to trigger autonomous responsive actions that make the factory smart. Having thus comprehended the literature, a seven stepped methodology for building or retrofitting a smart factory was established. The seven steps are (a) situation analysis where the condition of the current technology is studied (b) breakdown prevention analysis (c) sensor selection (d) data transmission and storage selection (e) data processing and analytics (f) autonomous action network and (g) integration with the plant units. Experience in a cement factory highlighted the wear in a journal bearing causes plant stoppages and thus warrant a smart system to monitor and make decisions. The experience was used to develop a laboratory-scale smart factory monitoring the wear of a half-journal bearing. To mimic a plant unit a load-carrying shaft supported by two half-journal bearings were chosen and to mimic a factory with two plant units, two such shafts were chosen. Thus, there were four half-journal bearings to monitor. USB Logitech C920 webcam that operates in full-HD 1080 pixels was used to take pictures at specified intervals. These pictures are then analyzed to study the wear at these intervals. After the preliminary analysis wear versus time data for all four bearings are available. Now the ‘making smart activity’ begins. Autonomous activities are based on various analyses. The wear time data are analyzed under different classifications. Remaining life, wear coefficient specific to the bearings, weekly variation in wear and condition of adjacent bearings are some of the characteristics that can be obtained from the analytics. These can then be used to send a message to the maintenance and supplies division alerting them on the need for a replacement shortly. They can also be alerted about other bearings reaching their maturity to plan a major overhaul if needed

Industry 4.0

This book shows a vision of the present and future of Industry 4.0 and identifies and examines the most pressing research issue in Industry 4.0. Containing the contributions of leading researchers and academics, this book includes recent publications in key areas of interest, for example: a review on the Industry 4.0: What is the Industry 4.0, the pillars of Industry 4.0, current and future trends, technologies, taxonomy, and some case studies (A.U.T.O 4.0, stabilization of digitized process). This book also provides an essential tool in the process of migration to Industry 4.0. The book is suitable as a text for graduate students and professionals in the industrial sector and general engineering areas. The book is organized into two sections: 1. Reviews 2. Case Studies Industry 4.0 is likely to play an important role in the future society. This book is a good reference on Industry 4.0 and includes some case studies. Each chapter is written by expert researchers in the sector, and the topics are broad; from the concept or definition of Industry 4.0 to a future society 5.0

Industry 4.0

This book shows a vision of the present and future of Industry 4.0 and identifies and examines the most pressing research issue in Industry 4.0. Containing the contributions of leading researchers and academics, this book includes recent publications in key areas of interest, for example: a review on the Industry 4.0: What is the Industry 4.0, the pillars of Industry 4.0, current and future trends, technologies, taxonomy, and some case studies (A.U.T.O 4.0, stabilization of digitized process). This book also provides an essential tool in the process of migration to Industry 4.0. The book is suitable as a text for graduate students and professionals in the industrial sector and general engineering areas. The book is organized into two sections: 1. Reviews 2. Case Studies Industry 4.0 is likely to play an important role in the future society. This book is a good reference on Industry 4.0 and includes some case studies. Each chapter is written by expert researchers in the sector, and the topics are broad; from the concept or definition of Industry 4.0 to a future society 5.0

Quantum Economic Theory of Intelligence

The Quantum Economics Intelligence Initiative, spearheaded by Quantum Economist PhDs. Kaiola M Liu integrates insights from seminal thinkers like Einstein, Archimedes, Adam Smith, Nick Land, and Sun Tzu. By applying principles of quantum mechanics, this forward-looking project aims to redefine economic modeling, exploring real-world applications and potential benefits. The initiative encompasses foundational studies, economic model applications, incorporation of quantum computing, and analysis of contemporary economic philosophies. Keywords - Quantum Mechanics, Economics, Technological Advancements, Philosophy

Perspectives on Digital Humanism

This open access book aims to set an agenda for research and action in the field of Digital Humanism through short essays written by selected thinkers from a variety of disciplines, including computer science, philosophy, education, law, economics, history, anthropology, political science, and sociology. This initiative emerged from the Vienna Manifesto on Digital Humanism and the associated lecture series. Digital Humanism deals with the complex relationships between people and machines in digital times. It acknowledges the potential of information technology. At the same time, it points to societal threats such as privacy violations and ethical concerns around artificial intelligence, automation and loss of jobs, ongoing monopolization on the Web, and sovereignty. Digital Humanism aims to address these topics with a sense of urgency but with a constructive mindset. The book argues for a Digital Humanism that analyses and, most importantly, influences the complex interplay of technology and humankind toward a better society and life while fully respecting universal human rights. It is a call to shaping technologies in accordance with human values and needs

Industry 4.0

This book shows a vision of the present and future of Industry 4.0 and identifies and examines the most pressing research issue in Industry 4.0. Containing the contributions of leading researchers and academics, this book includes recent publications in key areas of interest, for example: a review on the Industry 4.0: What is the Industry 4.0, the pillars of Industry 4.0, current and future trends, technologies, taxonomy, and some case studies (A.U.T.O 4.0, stabilization of digitized process). This book also provides an essential tool in the process of migration to Industry 4.0. The book is suitable as a text for graduate students and professionals in the industrial sector and general engineering areas. The book is organized into two sections: 1. Reviews 2. Case Studies Industry 4.0 is likely to play an important role in the future society. This book is a good reference on Industry 4.0 and includes some case studies. Each chapter is written by expert researchers in the sector, and the topics are broad; from the concept or definition of Industry 4.0 to a future society 5.0

Avoiding the Intrinsic Unfairness of the Trolley Problem

As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethical aspects. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems have up to now being presented in the form of an idealized unsolvable decision-making problem, the so-called "trolley problem", which is built on the assumptions that are neither technically nor ethically justifiable. The intrinsic unfairness of the trolley problem comes from the assumption that lives of different people have different values.In this paper, techno-social arguments are used to show the infeasibility of the trolley problem when addressing the ethics of self-driving cars. We argue that different components can contribute to an "unfair" behaviour and features, which requires ethical analysis on multiple levels and stages of the development process. Instead of an idealized and intrinsically unfair thought experiment, we present real-life techno-social challenges relevant for the domain of software fairness in the context of self-driving cars