NG-RPAS

About this project

NG-RPAS project is the second phase of Smart RPAS with extended capabilities that allows Search and Rescue teams to operate in around-the-clock environments under challenging weather conditions. This new version compiles the following innovations:

  • Real-time human recognition with high accuracy at far distances (150 meters).
  • Camera-aware detection for thermal, optical and blended lenses.
  • Challenging environmental conditions such as snow, night, rocky areas, rivers, cliffs, forests and many others.
  • Portable and cost-effective solution to detect tiny-sized humans on the screen.
  • Assist police forces to find missing people in Search and Rescue operations (SAR).
  • Machine learning based and thus smart, adaptive and extensible.
  • Real drone system deployed by Police of Scotland, Victoria Police and Swedish Rescue Drones.
  • Jointly funded by the Centre of Excellence for Sensors and Imaging Systems (CENSIS) and THALES UK.

Project achievements

The first phase of the project is the winner of:

  • “THE AWARDS 2020” managed by The Times in the category “Knowledge Exchange/ Transfer Initiative of the Year”.
  • “CeeD Industry Awards 2020” in the Innovation category.

This second phase was nominated to:

  • “The Herald Higher EducationAwards 2021” in Outstanding Business Engagement in Universities Nomination.
  • “The Scottish Knowledge ExchangeAwards 2021” in Powerful Partnership Nomination.

BBC Report: https://www.bbc.co.uk/news/uk-scotland-50262650

Internationally disseminated: BBC Radio, The Sun, Telecinco (Spain), 20Minutos (Spain), and VBOX7 (Bulgaria) and also Online Media such as ITPro, PoliceOracle, DIGIT, KBC, Silicon, ukauthority, insider, Myjoyonline, drapersolutions and so on.

References

  • Gelayol Golcarenarenji, Ignacio Martinez-Alpiste, Qi Wang, Jose Maria Alcaraz-Calero, “Illumination-aware image fusion for around-the-clock human detection in adverse environments from Unmanned Aerial Vehicle”, Expert Systems with Applications, Volume 204, 2022, 117413, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2022.117413. Impact Factor: 8.665