The planning process is largely a labour intensive process that requires the evaluation of large amounts of information including planning policy, legislation, community engagement and environmental/design considerations. It is becoming clear that certain technologies can aid in the planning system to speed up and even replace some of the manual and repetitive jobs that are involved in planning. The term “PlanTech” has been coined to encompass the various ways in which emerging technology can help in the way we plan and design cities.
Artificial Intelligence or AI, is a commonly discussed aspect of PlanTech. It is a computer system that can demonstrate behaviours associated with human intelligence such as learning, reasoning, problem solving and knowledge representation. We now see AI technology in many day-to-day activities from smart speakers to social media to spam filters for emails. AI technology is also being utilised in the workplace to replace repetitive tasks, aiding in recruitment processes, organising meetings, and it can even be used to offer an online chat services for general enquiries. In short, AI is used seamlessly by organisations and individual consumers with most people benefiting from AI systems on a daily basis without even realising it. Inevitably, AI will be used in most services, including in the planning system. This blog post will explore the various uses for AI in planning and ‘PlanTech’ in general.
Speeding up the Planning Process
Milton Keynes Council are trialling the implementation of AI in the planning system. Their website includes a “Planning Chat Bot” that can be used for general planning enquires, to check the status of applications and to organise meetings with planning officers. The Chat Bot is self-learning and will improve over time.
Milton Keynes are also trialling AI technology to aid with the validation of planning applications. The system can recognise whether the application complies with the validation checklist and can save time for technical support staff. Likewise Milton Keynes are also implementing an AI system to aid in the determination of applications that relate to permitted development rights by checking that the application proposals comply with the relevant statutory regulations.
Technology is changing the way that evidence can be presented in planning applications and appeals. A recent Inspector’s site visit in London involved a proposal for a new high-rise apartment block; the site was close to a number of other sites with extant permissions also for high-rise buildings, although many were yet to reach completion. To aid the Inspector’s appreciation of the future outlook at the site, the appellant provided a virtual reality headset which allowed the Inspector to view the proposed high-rise building in context, with the extant permissions at completion.
The increased availability of CGI images and 3D modelling of cities can help in the determination of planning applications by allowing a better visual image of the impact of proposed developments on the surrounding area. Southwark Authority in London now require all major applications to submit a 3D CGI model in order to aid understanding of the proposals.
These ‘PlanTech’ applications are not just limited to the capital. A team at Lancaster University is currently creating a 3D model of Lancaster, Morecambe and Heysham which will be available as an opensource web-based application this year. This will provide a useful tool for both applicants and planning officers in the preparation and determination of future planning applications by showing the impact of the development in the context of the surrounding built form. The availability of this data reveals an exciting glimpse of how Plan Tech will aid the determination of planning applications in the future.
Example Image of Castle Hill, Lancaster from the forthcoming 3D model by researchers at Lancaster University
‘Plan Tech’ can also be implemented at a strategic level to aid in the local plan process. For example, the ‘call for sites’ stage – when developers submit sites and information – is very labour-intensive. Currently, it involves an extensive exercise where planners must decide which sites should be considered for allocation. It has been suggested that AI could aid planners with the initial assessment of sites which would save time and expense at this stage of the local plan.
Likewise, collating data to inform the evidence base for a new local plan is often time-consuming. With the help of AI technology, the evidence base for local plans could be updated more regularly (or even constantly) and more quickly. This would mean the information was always up to date, reducing disagreement between authorities and developers on current housing need figures.
 The Lancaster City Information Model (LCIM) Credit to Paul Cureton (Lancaster University) and Elliot Hartley (Garsdale Design), also supported by Bluesky International, ESRI UK, and CyberCity 3D.