National drone detection network for Singapore
Lead Participant:
DRONE DEFENCE SERVICES LTD
Abstract
Our proposal is to deploy a wide- area, ground-based, lower airspace monitoring system, which monitors all conspicuous drones across Singapore. Leveraging the latest machine-learning, cloud and edge technologies, this network will be used to provide a multi-user airspace monitoring service as well as generate a large-scale aggregated dataset, from which insights are extracted to guide future strategy. With this, we will build an unrivalled resource on drone usage which will be an enabler for regulators, airspace planners, UTM providers, operators, and other stakeholders.
We have formed a collaboration with Metropolitan Wireless International who have over 10 years' experience of delivering complex detection/tracking network projects within Singapore.
Our 'multi-faceted' edged-sensor array will combine various sensors (DRI, ADS-B, FLARM), whilst processing data at point-of-capture, significantly reducing bandwidth and data-latency in complex/noisy RF environments. This will facilitate wide-area monitoring and generate large datasets for robust machine-learning models for rapid detection, and flight behaviour analytics. This insight will be used to guide the future integration of drones in non-segregated airspace.
These Richer datasets will mitigate incidences of false-positives/negatives for compliance and, through augmented machine-learning, make autonomous detection and tracking of cooperative drones more robust and efficient, guiding the future integration and control of flight-corridors towards a realistic prospect. Furthermore, the innovative edge-computing approach will ensure low-latency data transfer despite the large volume of data capture necessary for complete airspace coverage.
This project is fully aligned to the Singapore-UK joint statement 2021: a partnership for the future. It will facilitate cross-border data flows and will create an interoperable and highly accessible system that will enable AI to be used to drive the commercial use of drones which will have both environmental and economic benefits for both countries.
We have formed a collaboration with Metropolitan Wireless International who have over 10 years' experience of delivering complex detection/tracking network projects within Singapore.
Our 'multi-faceted' edged-sensor array will combine various sensors (DRI, ADS-B, FLARM), whilst processing data at point-of-capture, significantly reducing bandwidth and data-latency in complex/noisy RF environments. This will facilitate wide-area monitoring and generate large datasets for robust machine-learning models for rapid detection, and flight behaviour analytics. This insight will be used to guide the future integration of drones in non-segregated airspace.
These Richer datasets will mitigate incidences of false-positives/negatives for compliance and, through augmented machine-learning, make autonomous detection and tracking of cooperative drones more robust and efficient, guiding the future integration and control of flight-corridors towards a realistic prospect. Furthermore, the innovative edge-computing approach will ensure low-latency data transfer despite the large volume of data capture necessary for complete airspace coverage.
This project is fully aligned to the Singapore-UK joint statement 2021: a partnership for the future. It will facilitate cross-border data flows and will create an interoperable and highly accessible system that will enable AI to be used to drive the commercial use of drones which will have both environmental and economic benefits for both countries.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| DRONE DEFENCE SERVICES LTD | £498,160 | £ 348,712 |
People |
ORCID iD |
| Daniel Carver (Project Manager) |