To explore these in more depth we commissioned research by Connected Places Catapult to provide more detail on the technologies and also their possible applications to the planning system.
We also used this research as the basis for further exploration of the digital landscape, where we looked at data, planning technology and the IT landscape within local authorities.
At this time any potential use cases of the technologies highlighted below are either theoretical or examples of best practice elsewhere - their inclusion below does not necessarily signify inclusion in the digital transformation programme.
Machine learning is the concept of programming a system to learn from data, identify patterns and make decisions for itself. The more data that it gathers and analyses, the better its decision making becomes.
Machine learning has the potential to help identify land for development as part of Housing Land Audits. The application would identify and monitor developable land against key data sets and try and predict when land is likely to be developed.
Augmented reality is a technology, which adds layers of digital information, such as sound, video and graphics, onto a live environment.
Much of planning is about understanding the impact of future developments. AR provides a way to superimpose a model of a proposed development onto the existing site to visualise the impact it would have ahead of time.
The Internet of Things (IoT) describes devices, such as smartphones, home appliances and wearables, which are connected together via the internet and, therefore, able to share data with one another.
IoT could allow the planning sector to collect more granular and timely data about the places we inhabit and the impact of new developments. This could provide a robust feedback loop between plans, policies and validation of the estimated impact of development proposals against real-life data.
Image recognition is the process of detecting patterns in digital images or videos to identify an object or feature.
Image recognition technologies, which are already used in satellite imagery, could provide new data sets to inform and validate policies and development proposals. For example, image recognition can be used to identify vacant buildings or land for future development, or it could be used to assess the impact of a development once it’s built, such as measuring pedestrian and traffic activity.
A form of digital cartography using geographical information systems (GIS). Using three dimensional layers a user can visualise and model new ideas and development.
3D modelling technology gives the opportunity to build large scale complex 3D digital maps which convey a number of spatial factors that are almost invisible in 2D maps. This includes height and massing of buildings, enclosure of streets and spaces and citywide skylines from multiple viewpoints.
This allows for a better understanding of the form of development and its impact on views, enclosure and light.
A modelling technique that brings together data (live or static) and forecasts impact of development or lack of. Predictive urban models are tools that allow the visualisation of issues and solutions in real-time to help decision making.
By visualising a city and the impact of development it could become a lot easier to assess what kinds of developments are suitable. It allows policymakers to understand the dynamics of a city and it allows people to engage and understand the complexity of cities.
Big data is the name attributed to the vast amount of data being generated by the daily activities of users within a city.
Big data could allow cross-verification and better and more efficient data collection which in turn can help automate monitoring, making it easier to develop monitoring outputs for performance reports.
A form of digital verification where records are shared and spread over a number of computer devices. Each record is independent of each other yet update by verifying that all the other records are also updating to be identical.
This creates a system which allows a secure backlog of transactions to be recorded, making it almost impossible for individual users to alter the ‘digital-trail’
There are areas in planning where automatic verification would not only save time but make the system more trustworthy. Transactions occur all the time in planning and there is a strong legal narrative on the importance of recording these transactions.
While the technology itself is an application of encryption it is not necessarily a ‘technological’ device that can be applied however its implications for automatic verification is important.
Last Updated: 25 Apr 2022