Congratulations Chicago, which was this month revealed as America’s smartest city (and the world’s fifth), in an annual global ranking. The index assessed various criteria and sub categories – including government, where Chicago came out on top – but concluded that few single locations were able to excel in every single sector.
Chicago’s wealth of investment in strategy and infrastructure certainly justifies its high-ranking position. We learnt in February, for example, of its Resilience Chicago plan, which aims to ‘build a Chicago that is more resilient and connected, in the pursuit of economic opportunity, safety, equity, and sustainability’, by leveraging and integrating technologies. More recently, the city’s Department of Transportation proposed a $50 million expansion to a bike-sharing scheme, which would help reduce pollution and congestion and create hundreds of new jobs. This is a city we should all keep our eyes on, as many more initiatives will no doubt be announced in the coming months.
However, like many U.S. cities – and urban environments globally – Chicago faces a number of barriers which must be overcome to ensure the continued success of smart city plans. Perhaps number one among these is the sheer volume of data which exists (more often than not) in disparate, disjointed data sets. Open data is often sitting, available but unused, in the IT infrastructure of local government departments such as those overseeing transport, energy, environment, health services, education and statistics, as well as in pockets held by the police, private companies, and the managers/owners of huge numbers of connected IoT end-points and sensors.
Value from volume: Overcoming data deluge
This is an issue smart city stakeholders are increasingly coming up against. Cities are complex, multi-layered systems, and in order to deliver value and benefit for citizens, public service providers, governments and private enterprise, a holistic, data-centric approach must be taken to planning and development. Crucially, for the telco world, this must also involve operators taking centre stage in the smart city theatre. The IoT and 5G (and the exponential growth of data they will bring) present a clear opportunity for the operator community and signal the start of a brand new economy and chance to unlock new revenue streams.
As 5G takes hold and IoT uptake surges, it’s perhaps the cities themselves, rather than their citizens, that will consume and process the most data, via M2M connectivity. Cue a monumental shift away from human-generated big data and toward machine-generated extreme data. This will prove a major opportunity for operators, if the technology is in place that can adequately support the management of petabyte-plus data, and draw actionable conclusions from this.
Database transformation for digital transformation
Cities have transformed over the past 30 years, from purely physical entities whose infrastructure was sometimes actually detrimental to the wider community (think of mega-polluting roads in residential and retail areas, for instance) to urban environments which seamlessly integrate the digital with the physical, with the aim of constantly improving quality of life. Indeed, we’ve reached a point today at which whole new cities are being developed based on connected, digitalised approaches which minimise environmental impact and boost sustainable business. South Saad Al Abdullah city in Kuwait and Songdo International Business District in South Korea are two such examples of this model for creating new, green, urban spaces.
Where transformation has been slow to make its mark, however, is in the database and management systems that are so crucial to driving change. Traditional databases were not built for processing data continuously, and in real time, nor for incorporating this data with information on space and time – which enables visual mapping of data.
Database indexing must be reinvented for M2M networks and the unprecedented rise in connected end points. Platforms must collate data at extreme levels, organise, index, analyse and visualise this, producing root cause analysis to make sense of unstructured information, and transform this into solutions to smart city challenges.
Fortunately, such platforms are now available, leaving the door of opportunity wide open for operators to move away from their outdated roles as dumb data pipes, and to embrace lucrative new positions as intelligent data commoditisers.
The operator opportunity
We’ve already seen a multitude of operators launching IoT propositions or rapidly growing their IoT businesses in recent years. Singapore Telco, for instance, celebrated two partnerships last month: with China Mobile to encourage IoT device adoption, and with Microsoft to launch an AI-supported IoT network on Azure. In another collaboration for the Asian market, China Telecom this week announced a deal with Tata Communications to roll out a service allowing customers in the region to launch and manage connectivity for large-scale IoT fleets.
Provisioning at ‘large scale’ will definitely form a core part of any operators’ remit in the migration to the IoT data business. There were an estimated five quintillion bytes of data produced every day at the end of the last year – a figure we can expect to have risen further since and to continue to climb, with over 30 million devices forecast to be in circulation by 2020.
Mobile operators must embrace this scale, and move away from simply connecting (often low subscription fee-paying) consumers with their smartphones, and towards supporting embedded connectivity in vehicles, buildings, devices, monitors – and all the other end-points which enable the smart city environment. Rather than mere connectors, operators must be data (and asset) managers, with an ability to collate, visualise and analyse the data collected from end points – or sell it to those who do.
Partnerships with infrastructure providers who can assist on this journey will prove crucial: solving peta-byte data solutions is no easy feat! We’ve already seen smart city benefits for the likes of Chicago’s residents, its public services and private providers. But, as the aforementioned index highlights (and as we well know) comprehensive, cohesive blueprints for smart innovation across the entire scope of an urban environment, are more difficult to achieve. Optimising cities and delivering value for operators will entail the adoption of mega-scale data platforms, and the reinvention of roles.
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