Very few organisations operate entirely modern systems. Most environments are a mixture of new software, ageing hardware, proprietary tools, and data formats designed years apart by different teams.
Individually, these systems often work well. The problems appear at the boundaries. Data arrives late, meaning changes between systems are lost, or operators are forced to translate context manually. Over time, decision making slows because nobody fully trusts the combined picture.
We are usually brought in when replacing everything is neither realistic nor desirable.
Rather than pursuing “rip and replace” programmes, our work focuses on helping existing systems cooperate. That often means building small integration layers that translate protocols, normalise data, or expose legacy equipment in ways modern software can understand.
In practice this ranges from connecting serial or proprietary interfaces to web-based services, through to aligning operational data with open standards such as CoT, MAVLink, or structured planning formats. The aim is not simply data exchange, but shared understanding between systems and operators.
Interoperability also has a physical dimension. Many sensing systems fail not because of software limitations, but because power, connectivity, or maintenance assumptions no longer hold. Some of our research explores how infrastructure itself can support persistent sensing, allowing legacy assets to remain useful without large-scale replacement.
Over time, we have found that successful integration is less about building a central platform and more about restoring continuity between systems that were never designed to work together. When interoperability works well, it becomes almost invisible. Systems remain different, but decisions become clearer because information moves reliably between them.
Much of this work informs platforms such as AMP, where coordination depends on reliable integration between diverse systems.
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