Over the past decade, I have supported a wealth of geospatial programmes for governments and clients in the infrastructure space.
Once, knowing ‘where’ something was, was enough. But, the emergence of era-defining technologies such as connected autonomous vehicles (CAVs) and 5G (alone predicted to supercharge the UK economy by up to £15.7 billion a year by 2025), has prompted a surge in demand for a much richer level of data our roads and roadscape.
Those planning and implementing these revolutionary new services – with so much riding on their success – demand a level of detail and context that makes data truly relevant to their decision making.
Take a telegraph pole – a critical asset for many use cases and commonly not a feature on many maps. If it is, typically only the location is provided.
Far more useful for the policymaker, planner or designer is to have in their grasp the level of detail provided by the breed of highways technology companies like Gaist: How many cables are there? Which house do they join? Length of the span? How congested is the pole?
Another example is street lights. Here, users need to know construction material, bulb orientation and height. Street light have the potential for supporting so many additional use cases such as siting 5G small cells
And again ground surface: Understanding the ground surface material type – whether cobblestones, paving slabs, grass or trees – is key information to avoiding expensive site surveys and reducing abortive civils visits.
At Gaist, we have spent more than a decade building our knowledge and capability so as to provide this rich level of data- and provide it to our customers in such a way that it is easily accessible, engaging and auditable. In short, we are taking data insight to the next-level.
Using our camera-imaging systems and harnessing machine-learning and other technologies, we are harvesting and providing a depth of detailed insight which was previously unachievable. We help asset owners and those impacting with the network, to answer three critical questions: Where is it? What is it? And what condition is it in?
These sorts of ‘good’ data-sets – as the Geospatial Commission recognises in its 2020-2025 Strategy – have the power to unlock huge economic and social advantages and to transform the decision making and operations of those who manage and interact with our road network.
This is both asset owners and managers – local authorities – and those working on their behalf such as contractors as well as those working to roll out a raft of era-defining developments like 5G and CAVs.
Think how quickly, for example, key questions like “what percentage of roads are ready for fibre?” or “show me the condition of all UK roads” are answered with rich, precise detail available to answer them rather than a series of costly visits to the roadside.
The commercial value being placed today by organisations on securing the greatest possible depth of intelligence and insights into our roads and roadscape is evident: We were recently commissioned, by one single customer, to collect data on highways and footways for approximately 100 towns and cities in the UK.
The market for maps for CAVs alone – which rely on machine-readable digital maps or ‘splines’ to operate – is predicted to grow to $24.5bn by 2050.
The rich level of roadscape data available is also playing a critical role in making our roads safer: By arming local authorities with the ability to know where to prioritise their repairs, to proactively manage defects and to more effectively manage budgets.
The curation of more real world digital models combining where, what and information about the health of assets are being demanded by more and more users.
What is clear is this: With the ‘right’ data, readily available and easy to understand, we can transform our relationship with our roads in readiness for the next generation of users – who may not be in cars …