Data & Technologies
Smarter Innovators needs to ensure that their leading-edge ideas are able to leverage the massive growth in public and private data-sets. This growth in data is being driven by proliferation of mobile devices, availability of low cost sensor technologies and easier access to data acquisition platforms such as drones and satellites.
The real challenge for innovators is how to make sense of these new data opportunities and to harness them to your innovation to create greater value. In response, the array of technologies capable of making sense of these ever larger volumes of data is also radically improving.
These technologies include:
Internet of Things
Simulation & Visualisation
Whether collected by the public sector or commercial organisations, new data centric technologies are at the forefront of providing cost-effective and real-time insight that informs better decision making about resource use. How we collect, share and manage this data for the benefit of all is a growing concern for technology innovators, researchers and politicians. Innovators must embrace these data and technology advances or risk their ideas being quickly superseded and replaced by those that are harnessing this emerging capability.
Given the proliferation of this technology across many application areas there have been many early ‘wins’. However even greater value can be generated by harnessing the skills and knowledge across a range of disciplines and business sectors. The ability to unlock this untapped innovative potential offered by these new data sets that is driving the need for new forms of collaboration.
Internet of Things
The ‘internet of things’ (IOT) brings together the growing use of low-cost sensor technology and the network of high-speed communications to deliver unprecedented amounts of real-time data. Driven by the continued falling costs of sensors and the IT support systems, the IOT is an emerging trend that will create not only new opportunities, but new business models and markets.
Cognitive computing systems mimic the human brain to solve complex problems at amazing speeds, but without requiring human assistance. Using machine learning programs these systems continually acquire knowledge from the data fed into them to discover patterns. Over time, through self-learning, these systems become more capable of anticipating problems and modelling possible solutions.
High Performance Computing (HPC)
Really big and complex computing models such as those used to solve problems like weather forecasting, simulation of airflow over a wing, bridge design or computer design of a new drug or chemical formulation require large amounts of computing power. This is High Performance Computing (HPC).
Once a set of possible solutions has been highlighted by cognitive computing and modelled on HPC, they need to be communicated. 70% of human brain power is consumed on image processing so it is no surprise that the fastest way that humans can process large volumes of data is through visualisation. Solutions and their comparisons from HPC often use “visualisation” techniques to “show” the options to people to make final choices. This fast modelling and communication can reduce development times, bringing new solutions to market, faster.