Smart Cities

Big Data Puzzle

The world of data is exploding in our “always on” connected culture. “Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone” according to IBM.

The term Big Data is commonplace; many believe that it will transform business and government, but its real meaning remains vague. In a nutshell Big Data refers to both structured data (sensor data, sales data, etc.) and unstructured data (social media, text documents, video, etc.). Often it is real time data offering the Holy Grail for any company looking to predict future trends. Not all of it is new, but data is now available faster, its coverage and scope is wider, and includes new types of observations and measurements that were previously unavailable.

Companies and policymakers are realising the potential of their data; however, making sense of it and finding meaningful and real information that can be used to help us improve our lives and businesses is still a challenge. Imagine a box containing jigsaw puzzle pieces; it’s simply overwhelming: how do you know where to start? You empty the box and space every piece out. A complex algorithm in your brain searches and analyses pieces that fit together. However, finding these pieces and placing them together doesn’t give you the information you need until the picture is complete. With several puzzles mixed together, the information they give you does not become apparent until you finally look at all the images.

90% of the data in the world today has been created in the last two years alone

- IBM

Of course, this is an oversimplification; analysing data can often highlight pieces of information that you would never have thought about, some insights into new trends and potential opportunities. Consider the Google Flu trend a few years back. Google tracked the outbreak by finding a correlation between what people searched for online; it saw the patterns and was able to watch the spread far quicker than medical professionals.

Moving beyond simply tracking the outbreak, imagine being able to predict where it’ll hit next or its potential economic impact. Predictive models created by the ACRC are utilised in critical transactional systems and support decisions and actions in near real time. Planners and managers need to understand how complex environments will work in practice and understand potential problems before they occur. Urban planning, healthcare, train stations and airports all need to understand factors such as pedestrian flow and the impact of unexpected events. By focusing on understanding business challenges and delivering action-orientated solutions, these models can analyse multiple aspects of individual behaviour in differing conditions and scenarios. Analysing multiple instances of a given decision to identify the most effective action to take can provide valuable insights that help reduce cost and risk.

The ACRC specialises in the latest research in data analytics and complex simulation to bring these puzzle pieces together. We combine these technologies to produce powerful predictive models often using supercomputers to provide advanced decision support and analysis. Our state of the art research provides real information and knowledge from data that can be acted upon to maximise opportunities.

Published in the September version of Modern Gov Magazine

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Predictive Systems and Big Data in IoT in Manufacturing

The Internet of Things (IoT) is the general term that covers a world where smart systems, sensors and a large array of devices are connected together to offer business and consumers a more streamlined experience.

Market Researcher Gartner last year predicted in their Hype Cycle 26 billion devices would be connected by 2020, with Morgan Stanley increasing that figure to 75 billion. Others believe that only 50 million devices will be connected, but these are all estimates and no one really knows how many there will be. Do we really need to put a figure on it? We all know that the world will become more connected. The connectivity value in these networks will provide new ways of thinking, opportunities to exploit and act upon information and disrupt business models as well as introduce new security threats.

Take for instance manufacturing, linking up the IoT, sensors, robotics to automate the manufacturing process now let’s throw in Big Data. Across the world manufacturers are starting to look at linking Big Data within their manufacturing processes and IoT to transform and disrupt their manufacturing processes. Big data within the manufacturing process is becoming a game changer. While companies have been producing data for a years, new data tools are enabling real time analysis that provide real time problem solving, machine health monitoring and costs avoidance. Germany initiated an Industry 4.0 Government initiative to encourage its industry sector to realise the potential of this connection. Real time data driven decision support systems for the factory, that link in with logistic providers, other manufacturers of component parts and their clients, a system capable of synchronising all the areas in the supply chain, providing full visibility to all of those involved. The combination of IoT, and Big Data optimisation is bringing about huge opportunities.

These processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to Big Data to inform their decision support. The medical profession with environments such as hospitals where patients are their core component, interlinking with multiple chain events in a system of people orientated processes is possible.

Predictive systems play a key role in the Industrial IoT and supply chains. Intel and Mitsubishi piloted automated systems at the Intel manufacturing facility in Malaysia incorporating big data solutions to focus on improving productivity. By incorporating predictive machine health to reduce component failure the pilot optimised the process to realise savings of $9 million during its course.
To realise the vision of IoT in manufacturing interlinking all aspects of the supply chain, from an IT perspective will be a challenge. Many existing companies operate legacy structures which differ greatly from open architectures and data sharing. Linking data from disparate sources can’t be simply merged. To support the IoT, common data models, standards and architecture that spans the supply chain will need to be brought together. In some industries these standards already exist. Industries such as food and drink, have standards to measure the temperature of containers, track shipments and analyse food contamination, all standard parameters across the supply chain.

The impact of using big data and predictive systems in IoT manufacturing will represent great economic value. Optimised and automated factories will achieve results at a faster rate, reduce energy operating costs with increased efficiency, and processes that react to demand. Incorporating real time data will open up markets for companies to be able to response to changing consumer demand quickly, supply markets faster inline with demand. Future visions will include predictive machine health monitoring potentially not just in the manufacturing process, but also enabling streamlined after sales opportunities for companies to supply their consumers with parts before complete failure. Big data, predictive models and IoT will potentially open up greater markets that would benefit all within the supply chain.

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Discover Magazine

When two leading infrastructure and transport companies – Costain and Thameslink wanted to be sure their designs for major London railway stations would maximise pedestrian flow and passenger comfort, they turned to a team of computer scientists at the University of Sheffield.

An extract from a historic article back in August 2013 in the Universities Discover Magazine.

Professor Mike Holcombe talks about our simulation modelling, smart cities and big data in healthcare. We are indeed still working alongside infrastructure companies to model the behaviour of crowds within environments, enabling designers and decision makers to look at their ideas to help reduce the risk of unwanted situations occurring.

Discover Magazine August 2013

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