Skip to main content

About this book

This book introduces the reader to the latest innovations in fields such as artificial intelligence, systems biology or surgery, and gives advice on what new technologies to consider for becoming a market leader of tomorrow. Companies generally acquire information on these fields from various sources such as market reports, scientific literature or conference events, but find it difficult to distinguish between mere hype and truly valuable innovations. This book offers essential guidance in the form of structured and authoritative contributions by experts in innovative technologies spanning from biology and medicine to augmented reality and smart power grids. The authors identify high-potential fields and demonstrate the impact of their technologies to create economic value in real-world applications. They also offer business leaders advice on whether and how to implement these new technologies and innovations in their companies or businesses.

Table of Contents


Smart Grid, Future Innovation and Investment Opportunities

The electricity industry is going through a massive transformation which is fundamentally changing the way the electrical energy is generated, transmitted, distributed and consumed. This change will bring about challenges and opportunities for the different players in this massive system of supply and demand. The drivers for this transformation are numerous, which include the desire to shift to a more sustainable energy supply, advancement in technology and reduction in cost of renewable energy. Power system operators around the world are dealing with the challenges of operating grids which behave differently compared to originally designed concepts. However, there are vast opportunities for innovation and investments which can benefit from low cost energy. This chapter explores different ideas on how this massive low-cost energy can be harnessed in order to create value.
Dean Sharafi

Quantum Technologies

Many have heard about quantum computing, but very few understand how the technology works and it is common with misunderstandings. Will it make my computer go faster? Will it change how AI works? Will I soon have a quantum computer in my mobile phone? Is there an app for that? Why is it not here already? Will it ever be? This chapter will discuss some of the core concepts of quantum technologies. We will see that quantum is not only about computing and discuss some possible new applications on the horizon.
Daniel Akenine

Security in Intelligent Transportation Telematics

More than 10 years ago, the European Telecommunications Standards Institute (ETSI) began to standardize the communication between vehicles and infrastructure in so-called “Intelligent Transportation Systems (ITS).” This communication is supposed to be self-organized, which means, it has to be operated without the assistance from an access network. However, since most of the communication components are deployed in an inhomogeneous manner by vehicle operators “in the wild,” the security aspects are—for the lack of a better word—challenging at least. We will examine the security of ITS networks by discussing different modes of possible attacks.
Erich H. Franke

Innovation and Future Technology Scenarios in Health Care: Ideas and Studies

Innovations are turning the health care market into a technology-dominated sector. Artificial intelligence (AI), preventive medicine and all variations of upcoming technology will influence the health care market of the future. In the short term, it seems unthinkable in times when all expect higher costs in the future that we will accept that our economies need to lower health care costs by 20% or even more. People are getting older, leading to many additional treatments in the next decades, e.g. knee replacement treatments, cancer therapy treatments, coronary heart disease treatments and many other therapies that will emerge should people reach ages of, on average, 100 or more. The economy can only meet the requirements for successful international economic competition if we stop the upcoming explosion in health care costs, which are mostly financed by health insurance contributions and taxes. However, the reality is that our health care systems in Europe will not be able to deliver the best medicine to all people, especially not in those countries with demographic change, if the costs rise in the next decades as forecasts predict. We would like to present several ideas for and long-term scenarios of a health care revolution as well as present scientific studies, including the acceptance of users and patients, because we think acceptance by users and patients is a key factor for success in the future. Automation, BIG DATA combined with AI and patient cooperation are the requirements for a highly efficient and cost-effective health care system. Another key factor is preventive medicine. Let’s start with the idea of logic automation in health care.
Philipp Plugmann

Unlocking the Power of Artificial Intelligence for Your Business

Every day, we deal dozens of times with artificial intelligence applications such as autonomous cars, spam filters, or voice recognition systems. Often we do so without explicitly knowing that those applications are based on AI because AI technology has become mainstream in the last 10 years. From a business perspective, AI enables us to automate human decision making. We can thus cut costs and waiting times as well as increase revenue and profit margin. However, we have just started to scratch the surface as there are many more AI opportunities for companies to be exploited. This chapter first provides a gentle, intuitive introduction to AI for the interested business decision maker. In the second part, this chapter provides advice and best practices on how to rethink your business in order to become an AI-driven business that prospers in an ever more competitive environment.
Patrick Glauner

Innovation Means: Asking the Right Questions

In your professional career as an employee of a company which is not like the typical start-up, you have probably been facing several “innovation projects” every now and then. Projects which have the goal to reinvent the company, to create new added value to stay ahead of competition. Innovation seems to be the apparent answer to a slowdown of the growth of a company. But how many initiatives were successful in the end? Not many I guess. One of the reasons is the wrong approach that management starts off with. Instead of beginning with a question, it starts with the answer. The answer to what? Learn with how little effort you can increase the success rate of innovation projects significantly by asking the right questions.
Oliver Bludau

Innovative Technologies in the Ageing Population: Breaking the Boundaries

In the coming years, the generation of senior citizens will be able to benefit from the possibilities offered by digitalisation and artificial intelligence to a considerable extent. A decisive factor for the success of the use of new technologies in old age is the attainment of digital independence. Key areas of application for digital innovations include improving care and mobility for the elderly, personalised medicine and social exchange. New challenges in the context of demographic change and the remoteness of rural and economically weak regions can thus be mitigated.
Guido Lerzynski

Using Augmented Reality and Machine Learning in Radiology

Surgeries are one of the main cost factors of health care systems. To reduce the costs related to diagnoses and surgeries, we propose a system for automated segmentation of medical images in order to segment body parts like liver or lesions. The model is based on convolutional neural networks, for which we show promising results on real computed tomography scans. The deep learning algorithm is part of a larger system that aims to support doctors by visualizing the segments in a Microsoft HoloLens, an augmented reality device. Our approach allows doctors to intuitively look at and interact with the holographic data rather than using 2D screens, enabling them to provide better health care. Both the machine learning algorithm and the visualization utilize high-performance GPUs in order to enable doctors to interact efficiently with our system.
Lucian Trestioreanu, Patrick Glauner, Jorge Augusto Meira, Max Gindt, Radu State

Digitalization in Mechanical Engineering

A high level of industrial automation of repetitive tasks allows companies to efficiently produce products at large scale. Digitalization is the subsequent step of industrial automation and aims to further reduce costs and waiting times. Digitalization also aims to automate individual decision making. Key to both goals is to transform business processes from the analog to the digital world and then to analyze and thus to take advantage of digitized information. In this chapter, we provide an intuitive introduction to digitalization in mechanical engineering. We then present various business opportunities and discuss the related challenges. Next, we propose how mechanical engineering companies need to align their mindset with the digital transformation. Last, we present some of our works on digitalization in mechanical engineering and share a number of best practices. As an outcome, you will be able to employ digitalization in order to create real value in your business. That increase of efficiency will allow you to remain competitive in an environment that keeps becoming more and more competitive.
Michael Thurner, Patrick Glauner

Lean Launch Data Engineering Projects with Super Type Power

Data is ubiquitous. Many modern software and data analytics applications rely on robust and quality datasets. Data engineering becomes a common pipeline in systems running in start-up and enterprise businesses. Data engineering projects in the past were perceived as a set of programming scripts which were typically in a “build-then-scrap” cycle. As the data analytics applications became parts of the main trends, such projects require a serious planning and development to minimize the overhead of integration and maintenance due to scaling up. In this article, we discuss how to use type systems and formal methods to reduce these overheads.
Kenny Zhuo Ming Lu

Ubiquitous Computing: From 5G to the Edge and Beyond

This is an invitation to a journey from our communication technology’s past to the technological borders of today and beyond to the unknown. We will jump back in time for about three generations to become aware of the major steps of progress we have achieved in the past 50 years. From there we will move forward in three main paths, covering the invention of the (inter-networking) network, the development of hard- and software, and the advance of mobile communications. We will have a look at how these three streams of development eventually merged into one and how it led us to the technological reality of today. If you have been part of this story yourself, or if you already know all about it, you may want to read it anyway with a smile of remembrance. If you do not want to repeat this part, please feel free to jump ahead a couple of pages to Sect. 4.
André Panné

Autonomous Driving on the Thin Trail of Great Opportunities and Dangerous Trust

Achieving fully autonomous driving cars is a considerable technological milestone that will have significant impact on many lives and the adaption of new technologies. The question of when this milestone will be achieved is currently being debated and contradictory forecasts are increasingly being made. In this chapter, the most important components of self-driving cars are presented and different approaches are discussed. We show what makes autonomous driving so challenging and what misjudgments have been made in the past. In particular, the role of artificial intelligence will be illuminated to give a clear picture of what progress is realistic in the coming years. Next, we discuss related challenges that need to be solved in the coming years. Based on our own research, we will also show how hard it is to interpret models, like neural networks, i.e., understanding why they make the decisions they make in the context of self-driving.
Sandro Mund, Patrick Glauner

Analytic Philosophy for Biomedical Research: The Imperative of Applying Yesterday’s Timeless Messages to Today’s Impasses

The mantra that “the best way to predict the future is to invent it” (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word “theory”) as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined.
Sepehr Ehsani

Proposal-Based Innovation: A New Approach to Opening Up the Innovation Process

A basic principle of innovation is synthesis, a recombination of previously unconnected concepts. A known framework in this regard is Open Innovation (OI), which is widespread in nonmanufacturing industries such as software. In manufacturing, however, OI is largely rejected mainly due to high intellectual property (IP) protection requirements. This chapter describes an approach that can break through this aversion of manufacturers. The first step is to make the innovation activities of manufacturers transparent in a wide variety of industries and in a structured way, based on facts freely available on the Internet. The concern is only with WHAT companies do, have achieved, or intend to do, and not their intellectual property, i.e., HOW they do it. Remote locations (worldwide) and outside industries are particularly important because the information deficit is greatest in these axes, not least because search engines offer only limited and inefficient help when carrying out research in this regard. The second step is to use artificial intelligence (AI) to turn the extracted structured facts into concrete creative proposals for innovation and cooperation between different manufacturers (regardless of location and industry) in order to stimulate the innovation process in new ways. This principle is what Karl H. Ohlberg calls Proposal-based Innovation (PBI). The advantage lies in the fact that sign up, be a member, share your ideas, the idea of the Web 2.0 and Open Innovation from the end of the last millennium, is replaced by the use of the immense amount of data that has accumulated over the past 20 years. Discussions with manufacturers reveal there is great interest in this principle, so that the goal is to develop a cross-national prototype.
Karl H. Ohlberg, Jose L. Salmeron

Technologies and Innovations for the Plastics Industry: Polymer 2030

The plastics industry is changing. Not only are global influences leading to greater competition; a number of sectors that rely heavily on the plastics industry are also undergoing radical transformations. Consider the automotive industry: in this sector, a radical process of transformation and change is underway as new, more environmentally friendly drive systems are being developed—in particular, the move to electric vehicles. The CEO of Volkswagen AG has set out a clear position on electric cars, thereby triggering a dramatic upheaval. This issue has been given additional impetus through to the “Fridays for Future” movement and the diesel emissions scandal.
Michael Krause

How Do Innovative Business Concepts Enable Investment Opportunities in the Complete Construction Value Chain?

Our world is changing and the world population is growing rapidly. For all people we need buildings to live, to shop, to work and to enjoy to feel safe and protected. We need a reliable infrastructure to travel, to connect people with people. One of the consequences of growing population is that major cities are incrementally getting bigger. The way we are building needs to change. Conventional infrastructure and living environments are emerging and creating the need for faster, smarter, and lower cost setups. Concepts for Smart Cities and modular housing are born. In most of the local ecosystems, the construction industry is the key driver of growth, wealth, and security. Compared to other industry sectors, the fragmented traditional building industry participants are decades behind adapting to process and lean factory production driven manufacturers. New digital innovative technologies through the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR), roboting, automatization, and new materials can help to make the required changes. Pioneers, Innovation, Software and Technology are reinventing our construction world. It is time to be the change to come. It is time to change the way the world is building. There are significant investment opportunities in the complete construction value chain through innovative start-up companies. These entrepreneurs and start-up founders will use technology, data, and engaged people to drive the change in the global construction market.
Christoph Jacob

Motivation, Employees, and Communication in the Start-Up Phase

A challenging task for a start-up is the development of employees. Finding people who are interested in unpredictable overtime and bad pay sounds bad in any job description. Economically, there is no reason to refuse a job with a secure, successful company. There is also no economically understandable reason to give up a permanent position unless there is a better paid one. And there is no economic reason to change the last years of one’s professional life into the uncertainty of self-employment, at least not voluntarily. Nevertheless, there are thousands of examples that refute exactly that. For a reason that cannot be measured in figures.
Achim Denkel

AI to Solve the Data Deluge: AI-Based Data Compression

The massive amounts of data, growing as we speak, are one of the, if not the, most accountable reasons of today’s AI systems which on many tasks exhibit human grade performance. Thanks to the enormous amounts of image data that machines can be trained to recognize scenes and steer cars. Quantities of medical imagery lead to machine provided diagnostics, sensor data allows us to detect natural disasters before they occur, and to prepare for them. Times are exciting since researchers find new applications to AI at astonishing pace. However, there is a small concern. How will we handle the ever-growing amounts of data? The consensus is that storage is cheap, yet with load of data it is expensive and unsustainable. The amount of live streamed data is also increasing. In other words, we are well advised to consider data compression again. In this chapter, we will introduce traditional compression terminology and techniques, before surveying novel approaches proposed by industry and academia. It sounds contradictory, but AI may just as well help us to address this problem.
Eric Falk

Digital Transformation in Plastics Industry: From Digitization Toward Virtual Material

Digital transformation occurs by digitalization or digitization, simply meaning the conversion of information into a digital data format. Up to 90% of all the digital data available today is estimated to been generated just over the past 2 years! At the same time, the processing power of computers is increasing exponentially, with the result that existing data can be processed in entirely new ways. Computational power increases further with development of new technologies, e.g., quantum computing. Today we are talking about the digital revolution or digital era, also in the sense of a technological paradigm that fuels innovation and affects society and economy, leading to digital transformation in all sectors. The chapter intends to first give some insights on the impact of digital transformation and the rising opportunities in the plastics industry, using partially the example of Covestro as a global supplier of plastic material and chemicals. It furthermore relates to the increasingly relevant topic of virtual materials. In the second part, this chapter provides some suggestion in how to explore, exploit, and experiment, proactively taking part in the digital transformation, again using Covestro as an example.
Christopher Stillings
Additional information

Premium Partner

    Image Credits