Prof Antonio Torija Martinez A.J.TorijaMartinez@salford.ac.uk
Professor
Prof Antonio Torija Martinez A.J.TorijaMartinez@salford.ac.uk
Professor
Prof Bill Davies W.Davies@salford.ac.uk
Professor
To develop a world first ‘intelligent sound level meter’ and new digital services, combining acoustics and machine learning expertise to further develop RHE’s pioneering “Noise App”
Type of Project | Knowledge Transfer (Provision of Services) |
---|---|
Status | Project Complete |
Funder(s) | Innovate UK |
Value | £218,537.00 |
Project Dates | Nov 1, 2021 - Apr 30, 2024 |
DroneNoise: Addressing Public Health and Wellbeing Harms for a Sustainable Drone Sector Feb 1, 2022 - Oct 31, 2024
REFMAP Feb 1, 2023 - Jan 31, 2026
Impact and capacity Assessment Framework for U-space Societal Acceptance (ImAFUSA) Sep 1, 2023 - Feb 28, 2026
KTP with Greenjets Limited Sep 4, 2023 - Mar 3, 2025
To develop a rapid and easy-to-use conceptual toolset to predict and analyse the noise signature of electric ducted fans; leading to the design and manufacture a new generation of quieter and zero-carbon electric jet engines to power drones
Preventing Light And Noise impacting Biodiversity and ecosystem services (PLAN-B) Jan 1, 2024 - Dec 31, 2027
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
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