Is information management the key to more efficient cities, ask Richard Shennan and Colum Crawford
The conversation about making cities more efficient is often centred on the design, construction and operation of the physical infrastructure and services, and indeed it is essential to get this right, particularly for those cities where there is a significant element of new expansion.
However the key to realising the potential benefits in social, environmental and economic terms is the performance of the infrastructure and services as an integrated system and the behaviour of the people that interact with it. Information management is central to this.
Data, Data, Data
The management and maintenance of city assets is all too often a headache for those charged with keeping our cities going. But asset information modelling and management has emerged as a potential agent to help put right much that is currently wrong with cities around the world. The potential benefits to individual asset owners in delivering better performance while reducing cost and Carbon have been widely discussed, albeit that owners are only in the early stages of understanding what this means. The rapid development of technologies provides the opportunity, but focus on modelling technology alone will not deliver the results that are so urgently needed. At a city level, the key elements are:
- long-term vision;
- integration of information across systems and sectors;
- understanding the way in which people access and respond to information (both at professional and citizen levels); and
- sharing knowledge across boundaries.
As a vision for future cities, one can imagine city-wide information models, based on the principles of a common data environment and open data transfer between different technologies: the same principles that have been identified by the UK Government’s Building Information Modelling (BIM) task group which has made such a big impact over the last few years, together with the DfT’s earlier work on Urban Traffic Management and Control (UTMC) a decade and more ago. Now is the time to start taking this forward with a strategic plan that can transcend the political cycle. The large amount of data across all sectors that would need to be organised is daunting, but technologies to host data are developing faster than ever, and in any case a single version of the truth is likely to end up with less total data than the distributed, duplicated or plain out-of-date data that is the alternative. With a strategy and a plan for data management in place, well organised information generated by new or upgraded infrastructure projects and services across cites could feed in like pieces of a jigsaw, so that over an extended period the city information map would build up.
An example of organised data generation, as part of urban infrastructure works, is the generic three stage process Mott MacDonald has followed putting an asset model together.
- As with any complex project in an existing city, step one was to gather information about existing assets – often inconsistent, out of date or incomplete.
- All gathered information is then inserted into a model – and where provenance or accuracy is uncertain the features are tagged and conventional discovery takes place as the works got under way.
- As the works progress, the models are then updated to reflect what is actually there, which when combined with the integrated models of the new works leads to a reliable legacy model of everything.
Imagine now that this is fitted into a space in a city information map framework, and that all other new or upgraded infrastructure works are required to produce the same standard of information in an agreed format; the pieces would start to join up over the years, with dramatic consequences for efficiency of operation, maintenance and disruptions to city life.
Integration across systems can bring another level of benefits, in planning, execution and through-life performance of city assets. Just as has been seen in the world of buildings – where collaboration has been identified as a key requirement by three generations of major UK industry reviews dating back over 20 years and ‘silos’ has become the goto term to describe the demon – the ability to access and make decisions based on reliable common data across all aspects of city planning is an objective that is now coming within our grasp. Imagine a model that would enable optimisation of planning and development decisions, for new cities and neighbourhoods or major upgrades, to be taken on the basis of weighted assessment across systems ranging from energy, water and transportation, to environment, health and education. Many of these are intrinsically inter-related, with opportunities for synergy at almost every interface.
An example of a common data environment at a wide scale is the application of GIS at Mott MacDonald. Organised data with map interface can be used to deliver economic, social and environmental benefits. For example, within the West Midlands context:
- The transport model built for Birmingham Box Managed Motorway scheme accumulated and generated data that has lots of other potential uses beyond just that particular scheme.
- The PRISM transport model built for the West Midlands, integrates data from a wide range of local, national and derived sources.
- Local data, such as planning statistics, public and private transport surveys, are collated through partnership with local stakeholders and the Highways Agency.
- In-depth market research is used to reflect the behaviours of the local population supported by innovative data sources such as environmental and social factors.
- National datasets, such as the national PLANET rail and National Trip End Model, contain a vast amount of local and regional transport network data such as road characteristics, signal plans and public transport services.
If integrated, these data sets could offer significant long-term value for other regional projects.
Building on this, both the Apollo system in UK, and the FieldBook in USA, bring together data that is used for multiple purposes ranging from land ownership to utility usage patterns, and through simple apps make it information available to all, when they need it and where they need it. By adding a layer of analytics, multiple options can be assessed across different classes of infrastructure to get much closer to optimised outcomes.