Cities worldwide are dealing with increasing environmental and infrastructure challenges, including rising pollution levels, unpredictable climate conditions, and outdated infrastructure. The growing urban population further exacerbates these issues, resulting in traffic congestion, housing shortages, and overstretched public services. Addressing these problems requires efficient urban planning solutions that provide accurate and timely insights.
Scenexus, a spin-off from TNO, builds upon the foundation of Urban Strategy, a digital planning tool developed over years of research. While similar solutions have been introduced in the past, Scenexus aims to enhance urban planning with real-time, data-driven insights. The software integrates diverse data sets to create a digital twin of a city, allowing urban planners to simulate different scenarios quickly. Comparable efforts in urban digital modeling have existed, but Scenexus focuses on scalability and usability to ensure widespread adoption.
How does Scenexus improve urban planning?
Scenexus provides a software-as-a-service (SaaS) platform that helps cities analyze urban developments efficiently. The software allows planners to visualize land-use changes and assess their impact on accessibility, environmental conditions, and public health. By leveraging digital twins, decision-makers can explore multiple scenarios within minutes instead of waiting for extensive reports.
The platform enables city officials to evaluate the effects of housing projects, transportation expansions, and environmental policies in a more interactive manner. Scenexus’ Urban Strategy tool, often compared to a professional version of city-building simulations, is designed to support complex decision-making processes.
What technology powers Urban Strategy?
Scenexus’ Urban Strategy platform operates using high-performance algorithms running on graphical processing units (GPUs). The use of GPUs facilitates rapid calculations, significantly reducing the time required for simulation-based urban planning. According to the company, this approach allows cities to complete planning tasks faster and optimize budget allocations for infrastructure projects.
The software integrates multiple data sources and presents them through an intuitive interface, catering to different levels of users. Planners with varied expertise can access different functionalities, ensuring flexibility in city planning efforts.
“The platform is set up modularly, allowing parallel processing of multiple domains. The interaction between the modules is covered by our integration platform. Therefore, data sources can be calibrated and validated per domain,” said Jeroen Borst, CEO of Scenexus.
Addressing urban planning challenges
One of the main challenges in urban planning is the fragmentation of data across different departments, making it difficult to create a unified strategy. Scenexus’ platform seeks to break down these silos by integrating transportation, environmental, and infrastructure data into a single system. This consolidated approach enables municipal authorities to make more informed decisions.
“Every silo, e.g., transportation, has developed its workflow, procedures, and instruments. This makes it very difficult to get a holistic view of what is happening in the city, let alone the insight into future scenarios,” said Borst.
Several cities, including Amsterdam, San Diego, and Singapore, have adopted Scenexus’ technology to improve urban development strategies. The company is also working on expanding its reach in the European and North American markets.
“The first step is to develop lighthouse projects with front-running cities (big and small). These early adopters help us understand the city’s needs, and in return, these cities have a large influence on the Urban Strategy development roadmap,” Borst added.
As urban areas continue to grow, the demand for smarter and more efficient planning tools increases. The integration of artificial intelligence with digital twins could further refine decision-making processes, allowing cities to optimize resource allocation. While AI enhances simulation capabilities, deterministic models remain essential for ensuring transparency and accountability in public planning.
