Rotherham NHS Foundation Trust
Using Computer Vision to Bring Accuracy and Insight to Hospital Space Utilisation
Rotherham NHS Foundation Trust provides acute healthcare services to a large regional population, operating within the constraints and complexity typical of NHS organisations.
As with all NHS Trusts, there is an ongoing requirement to report on and optimise space utilisation.
Hospital space is a finite and high-cost resource, and how it is used has a direct impact on operational efficiency, patient flow and future estate planning. At the same time, hospitals are dynamic environments.
Departments move, services evolve and physical space is continually reconfigured. Maintaining an accurate, up-to-date understanding of how space is actually used is both critical and challenging.
The Problem
Across the NHS, space utilisation is a persistent challenge.
Trusts are required to report how effectively their estate is being used, but the methods for capturing that data are often manual and inconsistent.
Typically, this involves sending staff to physically check whether rooms are occupied at a single point in time. This approach creates several issues:
Data is based on momentary observation, not actual usage over time
Results are highly inconsistent and prone to human error
It is resource-intensive and difficult to scale
It provides limited insight into real usage patterns
A room recorded as empty at a specific moment may in reality be heavily used throughout the day. Equally, underutilised spaces can go unnoticed.
Without reliable data, decisions about space allocation, service planning and future investment are often based on assumption rather than evidence.
The Challenge
Capturing accurate, continuous usage data
Hospital environments are constantly changing. Rooms are used differently across days, weeks and departments. Capturing meaningful utilisation data requires more than periodic checks.
It requires continuous, objective measurement.
Eliminating reliance on manual processes
Manual audits are not only inefficient, they fail to provide the depth and reliability of data needed for strategic decision making.
A scalable solution needed to remove this dependency entirely.
Supporting estate planning and operational decisions
Space utilisation data is not just a reporting requirement. It underpins decisions around:
Service delivery and scheduling
Departmental layout and movement
Long-term estate planning and investment
Any solution needed to provide trusted, actionable insight, not just raw data.
The Solution
The Curve designed and delivered a computer vision solution to automate the measurement of hospital space utilisation. Using image recognition models, the system detects room occupancy from visual data and converts it into structured, time-based insights. This replaced manual, point-in-time observations with continuous, objective measurement across the estate. By integrating this data into a centralised reporting layer, the Trust gained a consistent and scalable view of how spaces are used, enabling more informed operational and estate planning decisions.
Our Approach
We replaced manual observation with a computer vision approach to capture continuous, objective space utilisation data.
Starting with the problem, not the technology
We worked closely with the Trust to understand how space utilisation was currently measured, where the limitations existed and what decisions the data needed to support.
The focus was on creating a reliable, repeatable way to measure real usage, rather than improving an already flawed manual process.
Introducing computer vision for automated measurement
We developed a computer vision solution capable of analysing images of hospital spaces and identifying whether rooms were occupied.
Using trained image recognition models, the system can detect the presence of people within a space, creating an objective record of utilisation.
Rather than relying on a single observation, this approach enables consistent and repeatable measurement over time.
Turning observations into usable data
The captured data is structured and aggregated to provide insight into how spaces are used across different times and locations.
This allows the Trust to move beyond isolated data points and understand patterns such as:
Which rooms are consistently underutilised
When peak usage occurs
How usage varies across departments and days
Creating a foundation for scalable insight
The solution was designed to be scalable across different areas of the hospital and adaptable as requirements evolve.
It provides a foundation for broader adoption of data-driven decision making across the estate.
The Results
rom assumptions to evidence-based decisions: The Trust can now make decisions about space usage based on actual data rather than point-in-time observations.
Improved visibility of space utilisation: The solution provides a clearer picture of how hospital spaces are used, highlighting inefficiencies and opportunities for optimisation.
Reduced reliance on manual audits: Manual, resource-intensive space checks are no longer required, freeing up staff time and improving consistency of data.
Supporting ongoing estate optimisation: With reliable utilisation data, the Trust is better positioned to, optimise existing space, plan service delivery more effectively and inform future estate investment decisions
The Trust moved from inconsistent, manual reporting to accurate, continuous insight, enabling more confident, data-driven decisions about how hospital space is used and optimised.
“Space utilisation has always been difficult to measure accurately. Traditionally, you’re relying on someone checking a room at a single point in time, which doesn’t reflect how it’s actually used.
This approach gives us real data. It allows us to see patterns, understand how spaces are used across the week and make much better decisions about how we manage the estate.”