Multi-modal positioning platform
Lead Participant:
FINDIFOX LTD
Abstract
This project will develop and validate a feasibility stage, on-device positioning engine designed to deliver high accuracy across a wide range of environments --- particularly indoors --- to overcome the critical limitations of conventional GPS and Bluetooth-only systems that often fail in complex, multi floor environments. The innovation is anchored squarely within the Advanced Connectivity Technologies pillar, aiming to advance UK capabilities in device level spatial awareness, with strong application potential in wearables, IoT (Internet Of Things) systems, robotics and digitally connected environments.
Today's indoor positioning technologies suffer from critical limitations: GPS signals are unreliable or unavailable indoors, and Bluetooth based approaches lack precision in crowded, multi level venues. They are susceptible to interference and cannot differentiate vertical location. Our solution fuses multiple connectivity inputs into a single, edge processed positioning engine that operates independently of physical infrastructure. This architecture enables low latency, high resilience, and privacy first location awareness, making it ideal for real world deployment in sensitive and safety critical environments.
This 5 month feasibility programme will focus on:
* Sensor Fusion R&D: Designing and evaluating compact fusion algorithms that integrate data for reliable indoor positioning..
* Prototype Development: Implementing the engine onto custom built wearable class hardware devices with limited compute and power budgets, suitable for mass market devices.
* Field Validation: Conducting controlled trials of this innovation in public buildings and home environments to assess accuracy, latency, and resilience under varied real world conditions.
The project will deliver a functioning proof of concept prototype, accompanied by benchmark data and a technical development roadmap. These outputs will directly inform further R&D, support IP planning, and prepare for future investor or partnership discussions.
The initial target application is child safety wearables, where rapid, reliable, and accurate location awareness in both indoor and outdoor spaces can help prevent child disappearances and improve family safety. The solution is also applicable in high value markets such as Augmented Reality (AR) headsets, smart venue navigation, and connected devices, but this feasibility phase will remain tightly focused on the underlying connectivity innovation and validation in one lead use case.
By developing an edge native, connectivity first positioning engine, this project contributes directly to UK ambitions around smart infrastructure, embedded communications, and resilient location services by laying the groundwork for scalable, privacy respecting innovations in this and the next generation of connected devices.
Today's indoor positioning technologies suffer from critical limitations: GPS signals are unreliable or unavailable indoors, and Bluetooth based approaches lack precision in crowded, multi level venues. They are susceptible to interference and cannot differentiate vertical location. Our solution fuses multiple connectivity inputs into a single, edge processed positioning engine that operates independently of physical infrastructure. This architecture enables low latency, high resilience, and privacy first location awareness, making it ideal for real world deployment in sensitive and safety critical environments.
This 5 month feasibility programme will focus on:
* Sensor Fusion R&D: Designing and evaluating compact fusion algorithms that integrate data for reliable indoor positioning..
* Prototype Development: Implementing the engine onto custom built wearable class hardware devices with limited compute and power budgets, suitable for mass market devices.
* Field Validation: Conducting controlled trials of this innovation in public buildings and home environments to assess accuracy, latency, and resilience under varied real world conditions.
The project will deliver a functioning proof of concept prototype, accompanied by benchmark data and a technical development roadmap. These outputs will directly inform further R&D, support IP planning, and prepare for future investor or partnership discussions.
The initial target application is child safety wearables, where rapid, reliable, and accurate location awareness in both indoor and outdoor spaces can help prevent child disappearances and improve family safety. The solution is also applicable in high value markets such as Augmented Reality (AR) headsets, smart venue navigation, and connected devices, but this feasibility phase will remain tightly focused on the underlying connectivity innovation and validation in one lead use case.
By developing an edge native, connectivity first positioning engine, this project contributes directly to UK ambitions around smart infrastructure, embedded communications, and resilient location services by laying the groundwork for scalable, privacy respecting innovations in this and the next generation of connected devices.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| FINDIFOX LTD | £49,569 | £ 49,569 |
People |
ORCID iD |
| Michael Dance (Project Manager) |