Designing Intelligent Data Infrastructures for Smart Cities

Dr. Larissa Suzuki is a Researcher at University College of London, where her innovative research contributes to a growing body of knowledge in smart cities and urban data management, as well as City Data Strategist for the Intelligence Unit at the Greater London Authority. She has designed a comprehensive dynamic business modelsand reference architecture framework for the design and realisation of large scale highly interconnected data infrastructures for smart cities. It gives architects, planners and consortia of design and construction companies the ability to better collaborate on the basis of common, accurate, data to design and build more sustainable and cost effective buildings, transport and other infrastructure. At the RE•WORK Connected City Summit, Larissa will be discussing 'Data Infrastructure for Smart Cities'. I caught up with her ahead of the summit to hear more about her work and her opinions on our future cities.What was the motivation behind getting into data infrastructure research?  The modern city should provide in which information flows securely, safely, rapidly and easily; a platform for both the dissemination and active consumption of innovation to improve the way the city works and the quality of peoples’ lives. The current proliferation of technologies, open data initiatives, and user generated content is already generating a massive amount of data and management cost. It follows that the systems operating cities' physical infrastructure need to become as tightly integrated as they can be, able to draw effectively on a vast supply of cross-domain city data.    Despite the considerable potential of city data, the remaining technical, strategic and organizational issues in the data supply chain make it difficult to capture the full potential of cross-domain city data. Among those issues are data interoperability, limited platform leadership and strategies which enable open and proprietary data providers to co-exist and co-operate, and non-defined policies and regulations which enables users to exploit new business models.  To enter into the new era of data exploitation we need to adopt a more strategic and outcomes-oriented approach. One that will facilitate the publication, management and dissemination of public and proprietary data, while also addressing privacy and trust issues in relation to citizen’s volunteered data. These processes are supported by a data infrastructure. I define data infrastructure as “the basic physical, digital, organisational and governance structures and processes needed for the management of all data that underpins the decision making processes in smart cities”.  My thesis provides support to the process of designing dynamic and intelligent data infrastructures. It provides a dynamic business models framework and a reference architecture framework which gives the decision makers of smart cities with the clarity they need to think strategically about how integrated data can help the city as a whole to function better.   Ultimately, my research gives guidance on a framework of good practices for decision-makers in smart cities to develop, agree and deliver their own data strategies that can make their cities ready to meet future challenges and the increased demand for integrated city data and services.       What do you feel has been essential to the success of the project so far?  My research helps to transform current data management practices and create a ‘city data market’ culture within both public and private sector by developing a philosophy that facilitates the exploitation and management of city data. The two key and unique aspects have made the project successful this far are. First, it emphasises the need to embrace the technology and non-technology components of data infrastructures to ensure that standards are adhered to, interoperability is guaranteed, smart governance is in place, a strong value network of partners are built, and feedback is facilitated. In my research I provide a number of examples highlighting the benefits and opportunities that have been delivered by open, proprietary and citizen’s data. Second, it does not intend to describe a one-size-fits-all model for data infrastructures in smart cities. Rather, the focus is on the enabling processes by which innovative use of technology and data coupled with governance strategies, a strong value network of partners can help deliver the various visions of data strategies for cities in more efficient, aligned and effective ways. Basically, my research focus on guiding cities to: •           Provide an increase range of tailor-made and engaging data and digital services which careful target the needs of users and businesses; •           Move to a more common and aligned set of requirements and innovative business models to design data infrastructures •           Transform data infrastructures in a foundation for widespread exploitation of proprietary, public and volunteered citizens’ data •           Integrate technology and non-technology components together to allow existing data platforms to respond to the market demand for a more integrated city data.  City data is an incredibly important asset and is the foundation upon which smart cities vision will be built. Providing efficient access to public and private sector and citizen’s data has the potential to enhance and transform both government and businesses services, as well as stimulate innovation in city services to the benefit of everyone.      What in your opinion are the most pressing issues within smart cities?  I think that integrating urban platforms and heterogeneous infrastructures services is a tough challenge, in particular if the platform need to be responsive enough to accommodate new emerging services. One of the most difficult technical hurdles to be tackled is to make existing infrastructures that interoperate only on their own setting and make them and their processes to be part of an integrated whole. They often lack standards for expressing the syntax and semantics of the data, and as a consequence, they produce non-interoperable data that is hard to integrate across different systems and stakeholders. This data integration problem is further exacerbated due to disagreements in standards for expressing the syntax and semantics of the data. Currently, the upgrade of such complex environment is onerous and highly expensive due to the use of proprietary and legacy systems. Besides integrating machines, smart cities must value the rich pool of data provided by citizens. Humans are very powerful devices in themselves and in most cases have sensing, actuating, and computing capabilities that go well beyond pervasive devices currently available yet to be invented.  There is an urgent need to create agreements with regards technological approaches, personal data protection, data standards and policies to integrate infrastructures and processes at the system-of-systems level. I think it is about time that cities implement and explore business models which are made possible by increased access to data and closer integration between horizontal infrastructure and processes. New business models will offer opportunities that will enable smart cities entrepreneur to design innovative intelligent solutions that will provide citizens with a high quality of life while meeting its ambitious sustainability agenda.     What challenges in our cities can be solved with emerging technology?  Modern digital technologies offer the chance to create a balance between social, environmental, and economic opportunities that will be delivered through smart city planning, design, and construction. Many cities and organizations have already done work to link smart cities solutions to policy goals and initiatives.  Examples of such solutions are: management and cooperation of heterogeneous sensors for public spaces monitoring; centralized operational central of smart buildings for energy efficiency and security; efficient use of electricity within smart infrastructure and data centres, real-time applications for disaster management in urban spaces based on information collected from various entities (e.g. crowd sourcing, homes, vehicles); physical and technical countermeasures against the security threats, use of augmented reality to optimise asset management, and the optimisation of spaces using the Internet of Things (e.g. hot desking and self-configuring rooms in smart buildings); air quality monitoring[1], intelligent road crossings[2].  It is important to highlight that such emerging technologies will increasingly be powered by integrated cross domain city data. Actuators, sensors, mobile phones, smart cards, smart meters, open government data and social media generate vast amounts of structured and unstructured data. Within all this information lie many potentially profitable insights regarding modelling city services performance, spatial aspects of the city, land usage, citizens’ mobility and travel behaviours, and trends.           What advancements would you like to see in this field, by 2050? Definitely by 2050 I would like to see electric avenues and smart cars across the world, affordable applications and wearable in smart health such as miniaturised medical equipment for test, diagnose, automatic reporting of patients’ health problems, and even attack diseases; and the replacement of screens from phones, computers, TVs and by augmented reality eyewear and immersive user interfaces.Larissa Suzuki will be speaking at the 3rd annual RE•WORK Connected City Summit in London on 16-17 March 2016. Other speakers include Julie Alexander, Siemens; Paul Wilson, Bristol is Open; Laurence Kemball-Cook, Pavegen; Kevin Menice, BigBelly and more.Tickets are limited for this event, for more information and to register please visit the event page here.