Lab to campus
Take connected research beyond the bench
A private research network supports laboratory development and wider campus experiments, helping teams test connected systems in their intended working environment.
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Private networks / Education & Campuses
Private 5G for education & campuses.
Take the experiment beyond the lab.
Give research teams a practical environment for connected robotics and edge AI. Private 5G links the laboratory, test route and local computing infrastructure into one usable project space.
Move from a bench demonstration to a repeatable campus trial, with clear device access, useful observations and a route into teaching and research.
Private 5G in practice
Connect the work. Improve the operation.
Open development
Connect research applications and devices
Application interfaces and IoT integration give researchers a practical platform for developing connected services and testing how they behave.
Teaching
Give students hands-on private 5G experience
A working private network brings devices, applications and mobile networking into practical teaching, demonstrations and student projects.
The operational connection
Take the experiment beyond the lab.
A project that works on a lab bench still has to cope with movement, changing radio conditions and the application running elsewhere. A campus test environment gives researchers a way to explore those interactions with real devices.
Private 5G connects selected robots, instruments and student equipment to local applications. Teams can collect the evidence from a trial, adjust one part of the system and compare the next run without rebuilding the entire environment.
Practical education & campuses use cases
Connect the task to the people who act on it.
01
Follow a delivery robot from the lab onto a campus route
A research team equips a small delivery robot with a compatible connection and assigns a trial between two campus locations. Private 5G carries mission status and selected camera data to the lab. Students can observe how the application behaves as the robot moves through the approved test area.
The team records completed tasks, communication events and operator interventions alongside the robot’s own logs. A change to the application can then be evaluated against the same route. The experiment produces a repeatable record that supports research and teaching, with the robot’s movement governed by its operating arrangements.
The opportunity: more useful outdoor trials and a clearer link between network behaviour and application results.
02
Run the vision model on campus edge compute
A camera or robot sends images to an edge AI application on a local server. The model identifies the agreed objects or conditions and returns the result to a research dashboard. Private 5G links capture and processing, allowing the team to study the complete path rather than the model in isolation.
Researchers compare results against labelled examples and inspect the cases the model gets wrong. They can vary the workload, camera position or network conditions and retain the observations for the next cohort. Computing stays within the chosen campus environment, where access and datasets can be managed for the project.
The opportunity: repeatable AI experiments and practical experience of the full connected system.
03
Turn a campus maintenance observation into a service task
An estates team uses a connected inspection device to record an issue along a campus service route. Photographs, asset references and notes reach the maintenance application through private 5G. A supervisor can review the finding from the office while the team is still close to the location.
The service request is assigned to the right trade, and completion evidence is attached to the same record. A research group can separately trial approved analytics on selected non-sensitive equipment images, creating a useful connection between teaching capability and estate operations. Operational ownership remains clear throughout.
The opportunity: better maintenance handovers and useful applied-learning opportunities.
Robotics and edge AI
From an observation to a useful decision.
Follow a delivery robot from the lab onto a campus route. The robot gathers observations or completes its assigned movement; the private network carries the agreed data. Edge AI means processing selected images or sensor readings on local computing infrastructure.
Choose what the application should identify and who receives the result. A reviewed finding can become a work order, a confirmed handover or a record for the next shift, with the supporting evidence kept alongside it.
Explore private AI → Private compute → Managed open-source applications →
Built around the operation
Plan the complete connection.
- 01 / DevicesRobots, cameras, gateways and staff handsets
- 02 / Working areasAgreed routes, buildings and operational zones
- 03 / Private networkRadio coverage, device access and traffic priorities
- 04 / ApplicationsLocal edge AI and the systems used by your team
Design for the site
Define the lab, outdoor trial routes and buildings in scope. Plan device onboarding, student access periods and radio changes so research activity can coexist with operational users.
Connect to the existing workflow
Choose where the core, edge compute and experiment logs run. Separate project datasets and access rights, and keep a clear record of changes between trial runs.
Planning & costs
We help turn the opportunity into a working solution.
We assess your estate, devices and applications, then design connectivity around the work you want to improve. We help build a business case around the opportunity, deployment costs and ongoing support.
We handle the technical assessment and help connect the investment to useful results. The first conversation starts with what you want to achieve.
One area or the whole estate.
Start with a focused deployment and expand, or move ahead with a full programme. We shape delivery around your priorities and readiness, and coordinate installation with your operation.
Talk to our teamPlanning questions
Private 5G for education & campuses: your questions.
Can the network support both teaching and research?
Yes, with access, capacity and change windows designed around the groups using it. A shared platform can host separate projects with clearly managed device and data access.
Can existing devices and applications connect?
Compatible cellular devices connect directly; suitable gateways can link other equipment. We check the exact device models, interfaces and application requirements before choosing the design.
Where does edge AI run?
Selected analytics can run on local servers, with access and storage designed around the workflow. The application identifies agreed events; staff review the result and retain responsibility for the operational response.
What is needed to scope the project?
A site plan, the chosen task, device details and the applications involved provide a useful start. We then assess coverage, integration, installation and ongoing support for a defined proposal.
Read the private 5G cost guide →Your operation, connected
Which task should work better?
Show us the working area, the equipment and the point where information stops flowing. We’ll help turn it into a practical first project.
Website information and service conditions
Coverage and performance are designed around your site, devices and applications. We set out the agreed service and delivery scope in your proposal.
Use cases illustrate how the service can support an operation. Project specifications and commercial terms are confirmed in the agreed proposal and contract.