The Fusion Platform® works by running a pipeline of data services to produce the required outputs. This typically involves ingesting from one or more data sources then processing these through an appropriate algorithm, or series of algorithms. The outputs can then be delivered either directly via our SDK or to a target destination, such as your own AWS S3 bucket.

We have designed the Fusion Platform® to run any appropriate algorithm, ingesting the data that is required to output what matters to your business. As an Algorithm-as-a-Service (AaaS) platform, this means that we build solutions which are deployed to the platform to work automatically. We also work with third-party suppliers of algorithms to deploy their solutions so that they work efficiently at scale.

If you want to use one of the existing data services we offer, are interested in whether we can develop a solution to meet your needs, or have an algorithm you think could benefit from our approach, please get in touch with us to discuss your requirements.

Data Sources

We can ingest data from a range of remote sensing data sources, including satellites, weather and IoT data. As experts in remote sensing, we know how to make the best of the data that is available, and how to fuse it with other data to overcome any limitations.

Processing

We offer a wide range of existing data services, or can build a tailored solution for you. Our data services are designed to automatically ingest all of the required input data and to execute all of the steps needed to turn this into the outputs that you need.

Actionable Insights

Each service is designed to produce actionable data in a format that you can consume, typically as geospatial data. These outputs can either be downloaded directly from the platform using our Python SDK, or they can be delivered to a destination of your choice, such as an AWS S3 bucket.

Case Studies & News

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Capabilities

Publications

Budykho, K., Boureanu, I., Wesemeyer, S., Romero, D., Lewis, M., Rahulan, Y., Rajaona, F. and Schneider, S. (2023) "Fine-Grained Trackability in Protocol Executions" Network and Distributed System Security (NDSS) Symposium 2023

Miller, R., Boureanu, I., Wesemeyer, S., Newton, C.J.P. (2022) "The 5G Key-Establishment Stack: In-Depth Formal Verification and Experimentation" Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security

Scarles, C., Treharne, H., Casey, M.C., Abidin, H.Z. (2020) "Micro-mobilities in Curated Spaces: Agency, Autonomy and Dwelling in Visitor Experiences of Augmented Reality in Arts and Heritage" Mobilities

Hickman, D.L., Smith, M.I., Lim, J., Jeon, Y. (2018) "Modelling of Celestial Backgrounds" Proceedings of SPIE 10641, Sensors and Systems for Space Applications XI

Al-Khalili, J., Smith, A., Sen, P. (2017) "Gravity and Me: the Force that Shapes our Lives" BBC 4 science programme using an iOS and Android app to measure local relativity effects

Treharne, H., Casey, M.C., Schneider, S., Wesemeyer, S., Ross, T., May, A., Blainey, S., Pritchard, J. (2016) "Integrating Data Sources to Enhance the Experience for Passengers with Special Needs and/or Disabilities through Privacy Aware Mobile Applications" Data to Improve the Customer Experience, RRUKA, 20/09/2016 Download

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