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Projects: Projects for Investigator
Reference Number NIA_SPEN_0049
Title iDentify
Status Completed
Energy Categories Other Cross-Cutting Technologies or Research(Energy system analysis) 50%;
Other Power and Storage Technologies(Electricity transmission and distribution) 50%;
Research Types Applied Research and Development 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 30%;
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 70%;
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Other Systems Analysis) 100%
Principal Investigator Project Contact
No email address given
SP Energy Networks
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 February 2020
End Date 31 December 2021
Duration ENA months
Total Grant Value £330,000
Industrial Sectors Power
Region Scotland
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , SP Energy Networks (100.000%)
  Industrial Collaborator Project Contact , SP Energy Networks (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA_SPEN_0049
Objectives Exploit AI Recognition technology and augmented reality to 1) crowdsource data on SPEN assets and customer devices to update the SPEN asset records, 2) identify 3rd party assets to reduce aborted calls, and 3) offer training, support and guidance to field staff on SPEN assets. Proof of concept – Initial phase of the project is to use AI and camera combination to recognise asset such as a single cutout to prove the technology works in the application3 Use cases – developed following proof of conceptUse case 1 – Asset data collection – App on phone – return asset data Use case 2 – Reduce aborted calls – send customer a link to a URL – Information to users and problem solvingUse case 3 – Field Staff Support – app on phone with AI and AR – information to user and problem solving The objective of this project is to create an app that will iDentify any asset it is trained on, and provide either useful asset data, or problem solving guidance to the user
Abstract Artificial Intelligence and Augmented Reality in conjunction with mobile Apps have the potential to improve asset management and reduce costs within the networks sector. This project will trial initial use-cases.
Publications (none)
Final Report (none)
Added to Database 02/11/22