By Niall Cunningham, WSP | Parsons Brinckerhoff Principal Development Management
At smart city forums across the globe we are discussing topics that are impacting on us all; ‘disruption’, ‘big data’, ‘sensors’, and ‘the internet of things’.
In our industry we spend inordinate amounts of time talking about how we might go about solving our cities’ challenges by using technology, but we ought to take a step back to first identify what these challenges actually are.
Cramming our cities with technology just for technology’s sake, will not help us to create smarter or more efficient cities to support our growing population. We first need to understand the challenges that our cities face, before we can confidently identify the technology needed to help solves those challenges.
But is that easy?
Technology is already allowing us to collect enormous amounts of data. Deloitte’s 2015 Mobile Consumer Survey found that almost 80% of all Australians now own a smartphone. Most, if not all of these devices collect and share data to some degree. In addition, a host of federal, state and local authorities collect and share all types of data, all of the time, with this list expanding on a daily basis. Add to these private operators such as Cisco or IBM, and we get some inkling of the sheer volume of data that exists.
If we already have all of this data, and we know that data is critical to unlocking smart cities, why haven’t we already solved our city challenges?
Access for all
It is absolutely appropriate that sensitive data should not be made publicly available. With that said, the sensitive aspect of data can easily be scrubbed to alleviate security and privacy concerns, making it fit for public consumption. Attempts from private enterprise to control and restrict certain data for commercial gain has similarly prevented data from being openly accessible and free to use. This stifles innovation in the smart city space.
So how do we go about addressing this issue?Our planning system is designed to preserve what’s best of our heritage and improve our built environment which we depend on for a civilised existence. As architects, engineers, designers and developers we all accept the planning system as a societal norm which is essential to achieve good city planning outcomes.
This planning framework has always, and will continue to evolve, to meet the changing needs of communities in our cities. If the ultimate purpose of smart cities is to improve the quality of life in our cities, we need to adopt a similar approach, setting a series of guidelines around how we collect, share and use data.
Policy planners can play a central role in defining this smart city framework. It is reasonable that companies and individuals who want to collect and use data in our cities should be required to operate within this framework. As with our planning system, we can adapt and refine these guidelines over time.
Frameworks can be tailored to specific cities or geographies in a similar fashion to that of our planning system. This system will need to be flexible to support innovation rather than becoming yet another layer of bureaucracy that impedes our smart city aspirations.
The ‘people’ test
Smart Cities in Australia are in their infancy and we are still learning what ‘smart’ might mean for our cities and communities. We need to critically examine and build robust solutions to support our city dwellers with quality data at its core.
One of the most effective ways to quality-check our data is to let our communities decide whether data is sufficiently accessible, accurate and usable. Giving the general public access is both a time and cost-effective way to scrutinise data.
A number of our city councils have stepped up to the plate and have released their data - regardless of their concerns around quality. This has allowed our city dwellers to assess all data – the good, the bad and the ugly. These councils are now actively working to refine how and where they collect their data, with many updating their data acquisition infrastructure, based on the feedback they have received.
This is crowd-sourced data auditing at its best. Once we understand the quality of our data, how we collect it and ultimately how it can be used to meaningfully improve the quality of life in our cities, we can refine how we gather it and share it. This will be an iterative learning process but one where the more accessible the data is, the quicker the transition will be out of this initial phase.
Tapping into meaningful data
So what can data help us to achieve?One of the most significant medical studies ever undertaken, the Dunedin Study, has followed the lives of 1,000 babies born in the early 1970s in Dunedin in New Zealand. Participants (who remain anonymous) have been regularly assessed with the resulting data being used to correlate trends patterns, behaviours, sociocultural similarities etc.
The study, which is now in its fifth decade, has supported over 1,150 publications and reports and has identified linkages between issues like heavy alcohol use and poor reproductive health, and poor credit ratings and cardiovascular health. This empirical data has, and continues to influence, policy-makers and medical professionals both here and overseas.
Imagine what we would uncover if we conducted a similar piece of research at a city, state or national level? We could learn more about how we interact with each other and with our cities – how we live, travel, relax, socialise and how this changes over time, particularly during periods of significant population expansion.
If we can better understand our relationship with our urban environment and our interaction as communities within this urban environment, we can tailor how we plan, build and operate our cities to better respond to our needs. And this is an imperative given cities are predicted to hold over two-thirds of our global population by 2050 according to a 2014 World Bank report.
In Australia this urbanisation is expected to be even more pronounced with the Department of Infrastructure and Regional Development predicting that by 2061, 80% of Australia’s population will be living in our cities.
And so finally, how do we decipher all this data and analyse it usefully? This is no easy task. Einstein once said that the definition of genius is taking the complex and making it simple.
So in our data rich eco-system, the real question for smart cities is; how do we isolate quality data sets and correlate them in a meaningful way to solve our city challenges? Artificial intelligence (AI) is beginning to support us in our quest and will have a significant impact on data analytics and the speed with which we can intelligently assess and correlate data.
We are at an early stage in our smart city evolution and there will certainly be growing pains but there’s no question that these are exciting times indeed.
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