Geomaat accelerates the future of mobility with smart data and AI
Within the Digital Infrastructure for Future-Proof Mobility (DITM) programme, Geomaat is one of the partners working on digital innovations that make mobility smarter, safer and more efficient. In the fourth and final year of this national innovation programme, we look back and ahead: how does Geomaat contribute to an agile digital infrastructure through automation, AI and collaboration with TomTom?
Geomaat is part of work package 4 within DITM, led by TomTom. In this work package, Monotch, V-tron, TNO, Geomaat and others are working together to keep digital maps up to date using vehicle-related data, smart detection and AI-supported processing.
From measurement to map: ready in a weekend
Geomaat works within DITM based on a clear vision: collect data on Friday, process it automatically over the weekend, and start with a usable map on Monday. This requires maximum use of technology, with AI and automation playing a central role.
Over the past three years, a lot of hard work has gone into automating processes, including arrow detection, point cloud classification and the recognition of traffic signs and markings. A point cloud is a 3D visualisation of the environment, generated using laser scanners. Geomaat uses this data to automatically identify objects and place them on the map. Whatever is developed must be immediately deployable in the work process: this keeps innovation practical and scalable.
A concrete example: in collaboration with a number of municipalities, the automatic detection of traffic signs and markings is now being used to draw up maintenance plans. In this way, technology contributes directly to more efficient and safer roads.
Taskrunner: scalable data processing in-house
Geomaat's self-developed cloud computing system, Taskrunner, represents a technological leap forward. It distributes heavy computing tasks across dozens of computers, allowing processes to be completed in record time. In practice, this means starting data analysis in the evening and being able to continue with the results first thing in the morning. Faster work, less waiting time and more control over quality.
What one computer does in twenty hours, twenty computers do in one hour. Taskrunner is now a standard part of every project, from road inspection to reconstruction.
Collaboration with TomTom: up-to-date and accurate combined
A powerful example of collaboration within work package 4 is that between Geomaat and work package leader TomTom. While Geomaat provides maps that are accurate to the centimetre via their Streetmapper, TomTom has up-to-date vehicle data (Sensor Derived Observations) from cars on the road.
The combination of precision (Geomaat) and timeliness (TomTom) makes it possible to continuously update digital maps with live data. This literally gives shape to data-driven mobility. Alone you are faster, but together you go further: this collaboration proves that in practice.
AI in practice: from object recognition to customised maps
The next phase within DITM focuses on object detection. AI helps Geomaat recognise objects from point clouds and panoramic images, such as lampposts. A second AI model then determines how these objects are correctly incorporated into maps, taking into account the specific wishes of clients.
This also presents a challenge: every client has different requirements for map data. The complexity therefore lies not only in recognition, but also in the translation to practical applications. Geomaat is developing flexible models for this purpose that combine smart technology with human validation.
This shifts the work at Geomaat from manual drawing to smart checking. Humans will always be needed for quality control, but the heavy lifting is increasingly being left to smart systems.
Social value: technology that works for everyone
Smarter maps and faster processes are not only efficient, but also socially valuable. Local authorities can make faster decisions about maintenance, reconstruction or road safety. Minimising error-prone manual work increases reliability. And because AI models learn from mistakes, processes are continuously improved.
In the video below, Geomaat explains how they contribute to a future-proof mobility infrastructure through technology, collaboration and a clear vision.
