Edge computing could be a solution for smart cities wanting to process large amounts of data, writes Ciaran Dynes, SVP of Products at Talend
Urban transition is now a global reality. Cities are home to more than half of the world’s population – consuming 75 per cent of the energy produced and generating 80 per cent of global CO2 emissions. As more and more people become city dwellers, the impact on transportation, housing, health, work and safety need to be considered.
With this transition happening at an exponential rate, those responsible for city planning and coordination need to take a forward-looking approach to design and maintenance. If neglected, it could mean a lower quality of life for a large proportion of citizens, especially when coupled with other arising issues including increased flooding and air pollution. In fact, the most recent data from London Atmospheric Emission Inventory shows that the majority of people in London are being exposed to an illegal level of air pollution. As the London population grows, the number of automobiles increases with the knock-on effect of rising CO2 emissions.
The good news is, technology and more importantly data are presenting city leaders with an opportunity to support a more sustainable urban transition – addressing the environmental impact of human and resource management as well as the availability of needs. In other words, a smart city.
Building a smart city aims to optimise transportation, energy distribution and services provided to residents, by installing sensors in parking lots, public transportation stations, rubbish trucks, the urban lighting system etc, by collecting data which will assist cities in decision-making. The sheer volume of data generated across a city provides vast amounts of information on its inhabitants’ behaviours, habits and needs.
At the heart of all smart cities are the digital technologies that offer important potential for transformation. In recent years, edge computing has created buzz within this space due to the many IoT-based use cases it enables. Unlike the centralised vision before it, edge computing presents a new decentralised way of seizing the opportunities and tackling the hazards brought about by urban transition. Edge computing allows large amounts of complex data to be processed and analysed instantaneously on the devices themselves, rather than at large data centres.
A great example of how smart cities are harnessing edge computing is with traffic management. Connected car start-ups, like wejo, are using the edge to offer critical information to relevant organisations across a city who are looking for real-time analysis of automotive data. This means better real-time predictions and accuracy on routings, helping to reduce congestion by re-routing away from areas of high traffic. This rich data supply can also be used to help urban planners design roads and cities based upon movement.
As cities become increasingly “intelligent”, e-mobility will continue to evolve. Edge computing will play a critical role in making e-mobility services possible within smart cities. For example, in the event of a serious car accident, edge computing can process the vehicle data and alert local services to an incident. This ability has, in fact, become a requirement of new cars within the European Union.
However, the growing amount of data created in devices is creating problems because data-centre infrastructures are not equipped to handle this volume. As connected devices and services grow, we run the risk of congestion across the network. Cities can work to mitigate these issues by hosting edge computing nodes closer to the points where data is generated, something which an increasing number of urban planners are incorporating into their designs. This allows greater amounts of data to be processed at the edge itself, removing barriers to autonomous driving.
Planners and city designers also need to build an extendable, scalable and secure architecture in the cloud to ensure security, data quality and effective data management. In this way edge systems can perform the initial processing and analysing of data, with further analysis happening at data centres or the cloud, where sufficient processor and storage capacity are available.
Cities must commit to a big data strategy in order to become sustainably smart. Using the volumes of data generated can not only lead to a better understanding of how cities work and how their inhabitants behave, but also support in removing the barriers between the various players and operators and creating new services which are better suited to new uses.
But generating data itself is not enough; data must be accessible for planners and organisations and it must be accurate and trusted. With that said, the digital platforms deployed need to be able to collect data at scale and create a single point of trust where the data can be quality-proofed, categorised, and protected. Not only this, but they must support integration, sharing, discovery, and governance so that planners can track and trace their data. Data is set to become one of the most valuable commodities and, if a smart city is designed effectively, a large bank of rich and applicable data will be generated, but this will only be beneficial to planners if there is data integrity.
Faced with the potentially problematic consequences of urban transition with regard to city resources, we urgently need to look to smart solutions. Ensuring a strong data strategy within city planning and taking full advantage of the edge are effective methods to help mitigate the various effects of transition. Taking inspiration from other cities paving the way in a digital era, we need to deploy smart solutions in order to negate the environmental impact of human activity and manage resources effectively for a growing population. Data integrity, data speed and data trust are all the cornerstone foundations which allow the data generated at the edge to support and develop the smart cities of the future.