How four new technologies are set to change planning

Technological innovations that are already having a dramatic impact on our daily lives are set to have a major effect on planning, says Euan Mills.

Augmented reality: experts are exploring how development proposals can be visualised in-situ via tablets and smartphones
Augmented reality: experts are exploring how development proposals can be visualised in-situ via tablets and smartphones

From long, impenetrable planning documents to consultation via notices on lampposts, planning is not a process often associated with being forward-thinking or innovative. However, new and emerging technologies are set to play an increasing part in planners' working lives. Here are four emerging technologies of which planners need to be aware.


The rapid miniaturisation of technology, accompanied by its increased affordability, has resulted in the ability to embed processors and sensors in almost everything, from lamp posts to cars and from parking spaces to rubbish bins. Many of these sensors are now connected and communicating with each other via the internet, creating a mesh of nearly 40 billion devices worldwide, which is known as the 'internet of things'.

The affordability and diminutive size of this technology allows sensors to be embedded throughout the built environment to collect data on how people are using cities. These devices can also incorporate live feedback mechanisms that respond to the urban setting in a way that has never been done before. In relation to planning, these kinds of advances mean that collecting evidence for local plans or impact assessments for development proposals can become significantly more granular and up-to-date than it has ever been previously. Real-time data on how homes are occupied, the extent of street overcrowding, parking space usage, or the popularity of parks, can all be quantified and measured and used to inform the policies that planners and other built environment professionals write.

By identifying the most useful data, planners can assess the impact of existing spatial plans and build an evidence base for better policies. Data can come from simple household devices, such as smart electricity meters, a new kind of meter that can digitally send readings straight to energy suppliers. These devices can provide data to planners about when properties are occupied or vacant and the number of people occupying them.

Existing planning processes make this real-time understanding of our cities impossible due to the lengthy and cumbersome plan-making process, which means policies are often out of date by the time they are adopted. But the potential to fine-tune, test and iterate policies based on real-time measurable outcomes is just a small step away.


Worldwide, we send 2.9 million emails per second, upload 20 hours of videos to YouTube per minute and publish 50 million tweets per day. Despite the numerous new sources of data we create through new technologies, local authorities and developers continue to pay consultants for expensive and time-consuming surveys and studies. Such data is used to build the evidence base for new development plans or for planning application impact assessments. Planners have already started using new datasets, by consulting satellite imagery and Google Street View when assessing applications. However, they also need to make better use of datasets from other sources such as social media, mobile telecoms, internet usage, and property transactions, amongst many others. This could dramatically improve how we monitor and evidence local plans, consult the public, and measure the impact of new development.

But collecting data is only half the story. The benefits of data depends on how it can be accessed, used and linked together. For example, planners could benefit from connecting information from planning applications, viability assessments, strategic housing land availability assessments (SHLAAs) and infrastructure development plans. Such a combination could provide estimated residual land values for individual sites, social and physical infrastructure capacity estimations and the ability to iteratively test the impact of the community infrastructure levy (CIL), affordable housing and density policies on site viability.


With the huge growth in computer processing power combined with the availability of vast amounts of data, we are seeing what many call the dawning of artificial intelligence. Such technologies are already being used to enable driverless cars and image and speech recognition, assist with legal advice and even identify some forms of cancer more successfully than clinical pathologists.

Highly complex neural networks in computers could give us the opportunity to free planners from the many time-consuming, laborious tasks they still have to do. This would allow them to spend more time on proactive planning and complex decision-making.

From the simple automation of basic tasks, such as validating applications, to more complex screening of developments prior to case officer assessments, the potential for this new technology is huge.

Local authorities are already taking part in experiments involving automated screening of household planning applications. One authority, which refuses or returns half of the 800 household applications it receives per year, estimates it could save at least 800 hours of processing time through an automated screening process.

Meanwhile, Milton Keynes Council has taken part in a project trialling the use of satellite imagery recognition to help with planning enforcement. The technology can detect potentially unlawful changes in the urban environment, such as changes of use or extensions. Planners could also use such image recognition to identify development sites for SHLAAs and brownfield land registers.

While transport modelling is already well used in the preparation of development proposals or plans, new and more sophisticated modelling technology is giving us the ability to create much more complex models. Multiple layers of information such as population demographics, land market statistics, transport and social infrastructure data and even factors relating to cultural trends, can all be modelled simultaneously. Predictive analysis of traffic has moved from transport departments to hand-held devices. We're even seeing experiments in models that predict which urban areas are likely to suffer from high crime rates and gentrification.


Virtual reality and the related technology of augmented reality have only recently become accessible and part of mainstream culture. The use of augmented reality, such as the Pokemon Go game and Snapchat filters, and virtual reality, such as the new Google Cardboard platform, provides us with new ways of visualising and experiencing the built environment.

The increasing accessibility and affordability of digital modelling and mapping of the built environment, through advances in satellite imagery, drones and photogrammetry (the process of making surveys and maps through the use of photographs, especially aerial photographs), means we can easily build virtual reality models of our cities. These models can be used to explore the cumulative impacts of development on our skylines, to visualise their effect on daylight and sunlight and to experience the design of our streets and spaces. This allows us to easily iterate and optimise the built form before anything is built.

For example, tech visuals firm Linknode is exploring how the use of augmented reality via tablets and smartphones can be used to experience and visualise development proposals in-situ at public consultations. So alongside the much-maligned planning notice on the lamppost, people could soon be able to see simulations of proposals as if they were already built.


The technological trends above are having a dramatic impact on the way we live, so it is just a matter of time before they fully infiltrate how we plan.

While much of it may feel distant, change is inevitable. However, this change needs to happen incrementally, and planning authorities should be wary of entering into lengthy and potentially costly contracts with large technology companies.

They should focus instead on small and incremental improvements, such as collecting and storing all the data they process, and ensuring that their reports and policy documents are in a 'machine-readable' format, which means computers will be able to process the data in the inevitable near future.

Euan Mills is urban design and planning lead at urban innovation centre Future Cities Catapult. 

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