Innovation opportunities are arising from the emergence of more `intelligent´ digital systems assisting or replacing human judgment or decisions.


The term digitalization refers to the effect on society achieved through integration of digital technologies into everyday life.

These effects include the restructuring of social domains around digital communication and infrastructures, changes to business models and operations, and how value for customers and stakeholders is generated and delivered.

Digitization – the conversion of analogue streams of information into digital bits – is a sub-set of digitalization, which is fueling technology innovation across industry sectors: helping society do things cheaper, faster and better; allowing individuals and businesses to obtain more control and influence; and pushing the boundaries of current technology frontiers.

Digital technologies allow global interconnectedness 24/7 and offer the ability to combine, analyze and generate actionable knowledge from large and complex data streams in real time.



The IoT refers to the network of “all” physical objects (hardware) that can be connected to the internet or a local web. Software is an instrumental enabler through provision of data aggregation and data analytics functionalities. Examples of IoT-enabled applications are remote monitoring and control of homes, and personal health and fitness tracking.

By 2025, the Internet of Things is expected to encompass 0.5-1 trillion devices – with a potential economic impact of 2.7-6.2 trillion USD annually


Over the next decade we expect to see satellite communication speeds of up to 50 Mbps, and low orbit nano-satellites weighing less than 10 kg, bringing dramatic costs reductions. Low-cost, WLAN-connectable satellites will provide near-global coverage 24/7, allowing real-time high-definition video streaming and detailed AIS tracking. Cheaper satellite communication subscriptions will be balanced by the need for higher bandwidth.



Integrated circuits will increasingly be embedded into micro electro mechanical systems offering sensing and processing capability at the point of data collection. Future chips containing hundreds of sensors will spur a wave of automation across industries, and a revolution within personal monitoring. Some simple analytical tasks, such as measurement of blood glucose levels, identification of foodborne pathogens, and water quality testing, are already being done on a microchip.



The next generation 5G network is expected to be rolled out by 2020 to meet increased demands, such as a data transfer rate faster than 1 Gbps. The network will have to cater for new use-cases enabled by the IoT and fulfil the demand of multimedia broadcasts. 5G network functionality will also enable individual devices to communicate directly with each other rather than relying on network operators' base stations.


Energy to power low-energy electronics can be harvested from the surrounding environment. Energy sources can be RF signals, waste heat, solar energy, vibrations, and so on. Energy harvesting is driven by an increased demand for wireless connection, and the desire to avoid battery solutions. Examples of energy harvesting devices are piezo elements transforming pressure variations in shoes into electricity usable for wearable devices, or thermal elements powering implantable medical devices with electricity.

Energy harvesting: Piezo elements transform pressure variations in shoes into electricity for wearable; thermal elements power implantable medical devices with electricity


Software companies are gaining ascendance in many traditional industry sectors. Digitalization, digitization and eCommerce are enabling software companies to penetrate markets across industries, often with disruptive network-based business models. The world's largest bookseller, largest video service, most dominant music companies, fastest growing telecom company, best new film production company and fastest-growing recruiting company are all software-based companies.


In recent years, the sophistication of automated systems has increased immensely, driven by advances in sensors, software and computing hardware. The ongoing transition from automated to autonomous systems will result in increasingly complex systems over the next decade. Where an automated system tends to be specialized in one task, an autonomous system is a situation-aware, self-governing system capable of completing loosely defined goals using complex reasoning.


Open source software and communities are central to the so-called big data phenomenon. Key examples of open-source software are Linux and Hadoop. The Android operating system for smartphones, for instance, is built on top of the Linux kernel. Hadoop is a fast-developing eco-system of free software tools for handling and analysing large datasets and data streams based on large clusters of commodity (cheap) hardware.


Semantic technology uses ontologies to encode meanings separately from data and content files, and separately from application code. Ontologies are explicit formal specifications of the terms in a domain and relationships among them. In this way it enables the computer to understand the meaning and context behind words, sentences and ultimately data. It is expected that by 2025 most search engines will rely heavily on semantic technologies for human-computer interaction.



Human cognitive ability and perception is generally too limited to extract useful information from large amounts of data. The task is far better performed by sophisticated computer programs that find patterns in data, predict future dynamics, or extract valuable information from unstructured textual data sets. Machine learning is still considered to be in its infancy, but the potential of cognitive technologies are already clear. An example of an early development is Watson, IBM’s cognitive computing platform.


Cloud computing devices are connected via the Internet to servers where the data is hosted and the actual computation is done. Cloud solutions offer device and location independence, scalability on demand, low upfront investments, and low maintenance cost. Examples of cloud computing concepts are Software as a Service (Google Gmail, DropBox), Infrastructure as a Service (Amazon Web Services, Open Stack) and Platform as a Service (Thingworx, IBM Blue Mix, Google App Engine, GE Predix).


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