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The road to smart cities starts with data – Part One

The largest ant colonies in the world contain over 300 million individuals and cover areas that are several kilometres wide. Ants mostly rely on tactile and chemical means of communication to keep these huge systems in order. Luckily, as humans, we have additional tools at our disposal to make our homes and cities more efficient, more organised and, to put it simply, better places to live in.

Here, Johannes Petrowisch, a partner account manager at industrial automation software expert COPA-DATA, discusses the role of data collection and analysis in the smart cities of tomorrow.

The essence of the smart city

Smart cities use technology to enhance the quality and performance of urban services, to reduce costs, decrease resource consumption and to engage their citizens more effectively. Through information technology, smart cities enhance physical infrastructure like roads, public transport, buildings, the energy grid and more.

Smart cities allow local people to participate in decision-making through e-governance and open data resources. Smart cities can learn, adapt and innovate quickly, which allows them to respond promptly to anything from high levels of traffic or a burst in energy consumption, to a rapid increase in population or crisis situations like natural disasters.

Essentially, smart cities use technology to become safer, more sustainable ecosystems and help their inhabitants live healthier, happier lives. It might sound like a fairytale to some, but certain aspects of the story are already a reality.

For example, smart grids that integrate a variety of energy sources, such as renewables, have already been implemented around the world; Jeju Island in South Korea is a good example. Intelligent public transport systems – already live in London – can predict how busy underground trains are going to be and automatically adapt the number of vehicles in use at any given time. Similarly, in Barcelona, waste facilities are equipped with sensors that communicate with a central control system when they need emptying. The collected data also helps determine the shortest driving routes when emptying rubbish containers, which saves local authorities time and money.

Technology leading the way

The Internet of Things (IoT) is an industry concept that will play a central role in the smart city. Unless you’ve been living reclusively for the last few years, you’ll know IoT refers to the interconnection of uniquely identifiable embedded computing, like devices within the existing internet infrastructure and beyond. IoT allows the interlinking of networks, devices and data that have never been connected before in history. It is expected to go beyond traditional machine-to-machine communications (M2M) and cover a variety of protocols, domains and applications.

The interconnection of embedded devices in the smart city will encourage automation in nearly all fields and enable advanced applications like smart grids. IoT is expected to gently ease us into the world of the smart city. In fact, some IoT applications are already commonplace. Traffic light systems, number plate recognition technology and CCTV are just a few examples.

The expectation is that in years to come, IoT applications will increase in scale and complexity. Streetlights that can automatically adjust to environmental conditions and traffic levels or water distribution systems that can identify leaks instantaneously and shut off pipes automatically are only a few of the IoT marvels we can expect to see more of in our cities.

The data deluge

Another industry concept that sits at the foundation of any smart city is big data. As a “system of systems”, the smart city can generate vast amounts of data, especially as more sensors are integrated to traditional infrastructure and connect a growing number of devices. But a smart city needs to do more than just be able to collect data. It needs to manage and analyse vast sets of information, to unlock new sources of economic value and provide brand new insights.

One thing many people avoid when discussing big data is just how big and diverse it really is. Traditional data processing approaches simply can’t handle such vast amounts of information in such a wide range of formats. The challenges include data capture, curation, storage, search, sharing, transfer, analysis and visualisation.

The latest generation of industrial automation software is designed to deal with these problems and relies on rapidly evolving analytics techniques that can be employed across a multitude of data sources. Predictive capabilities are already being used in industry and could be implemented in smart cities to help spot business trends, combat crime, determine real-time roadway traffic conditions and much more.

The second part of Johannes’ blog will publish on www.iotglobalnetwork.com shortly.