Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_NGN_272 | |
| Title | DoorStop | |
| Status | Completed | |
| Energy Categories | Other Cross-Cutting Technologies or Research(Environmental, social and economic impacts) 100%; | |
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | SOCIAL SCIENCES (Psychology) 100% | |
| UKERC Cross Cutting Characterisation | Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 50%; Sociological economical and environmental impact of energy (Technology acceptance) 50%; |
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| Principal Investigator |
Project Contact No email address given Northern Gas Networks |
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| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 October 2020 | |
| End Date | 01 May 2021 | |
| Duration | ENA months | |
| Total Grant Value | £115,060 | |
| Industrial Sectors | Energy | |
| Region | Yorkshire & Humberside | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , Northern Gas Networks (99.999%) |
| Other Investigator | Project Contact , Northern Gas Networks (99.999%) Project Contact , Cadent Gas (0.001%) |
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| Industrial Collaborator | Project Contact , Northern Gas Networks (0.000%) |
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| Web Site | https://smarter.energynetworks.org/projects/NIA_NGN_272 |
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| Objectives | This solution will transform doorstep engagement and mitigate the risk for both customer and colleague, enabling a best-of-class safeguarding processes to be adopted. We will harness facial and voice recognition technologies to redefine how utility companies and potentially other organisations can interact with customers by producing a web-based application to allow customers to scan the face or analyse the voice of a visitor using smart phone or tablet technology and receive instant feedback from the system providing reassurance to the customer.The DoorStop system will immediately recognise the caller as a genuine employee of a utility company or conversely report directly to that company if they are not recognised. The application will be accessed and used through a normal web page without the need for a dedicated mobile app or any special technology, making it as accessible to as many customers on as many devices as possible. Egnida will produce a production-ready application which will be tested in a discrete geographic area with live customers and staff.For customers who may find visual identification difficult, there will be the option to use voice recognition whereby the caller will be asked to give their name and organisation, and their voice will be analysed and matched to identify the caller. Following a number of external and internal stakeholder sessions which have helped scope the opportunities and technologies available the project will be scoped into 3 stages.Stage 1 Utility company admin portal - a portal which selected staff can use to add, remove and update staff information, view metrics on app usage and follow up on failed recognition attempts reported by customers.Stage 2 Customer facial recognition web application – a web page which the customer can use to scan the face of a visitor claiming to work for a utility company to ensure they are a genuine employee and report if not. The page will be designed to work on a wide number of devices which have a camera and web browser, not just latest smart devices. The page can be accessed from any existing domain or a bespoke version for a utility company can be hosted on their own web offer, with the required code hosted on secure Amazon Web Servers. The facial recognition service will also use Amazon Web Services to store and analyse the faces of staff and callers. For customers who may find visual identification difficult, there will also be the option to use voice recognition where the caller will be asked to say their name and who they work for, which will be used to identify the caller.Stage 3 Limited geography trial across NGN and Cadent footprint- generate user experience data from a customer perspective by soliciting feedback from the customer through the application during a trial period. This will look to gauge how comfortable a customer is asking to scan a visitors face and to suggest best practice such as using it whilst the front door is on the chain. The 3 stages will then deliver a final project report which will include feedback and recommendations for further roll out across the country using customer and colleague feedback. Following on from a series of user stories to describe the required system functionality the objectives for each stage will be as followed:Stage 1 : Design and implement a robust data security model Create a user administration portal Develop the user administration functions within the admin portal Develop a mechanism where failed identifications are reported to NGN/Cadent Define and develop analytics requirements with NGN/Cadent Stage 2: Deploy a live customer web application Design an accessible user interface Develop robust technology fall-backs to accommodate older technology Ensure that visitors can be identified within five seconds for facial recognition (and ten seconds for voice recognition) Collect feedback through the customer app and NGN/Cadent staff survey Stage 3: Identify most appropriate trial area(s). Ideally on a adjoining Cadent and NGN patch Make customers in trial areas aware of the availability of the DoorStop app Gather and action defects and enhancements Draft and deliver DoorStop trial report | |
| Abstract | According to the Office of National Statistics, there are between 5,000 and 8,000 reports of doorstep crime per year in the UK (5,784 in 2017, 6,233 in 2018, 7,107 in 2019) Whilst these are instances where a demonstrable offence has occurred, it is estimated that only 5% of cases ever get reported so the actual number of attempts is certainly much higher. On average, a victim of doorstep fraud loses around £3,000, but it is the emotional and mental scars that become the bigger and longer-lasting impact, not to mention a loss of trust in even genuine officials who need access to the home. 65% of doorstep scam victims are aged 75 and over. Trading Standards put this figure even higher and state 85% of victims are aged 65 and over. Scams cost the UK economy up to £10bn every year.Citizens Advice reports that nearly 20% of people have experienced attempted doorstep fraud and of the people surveyed, no one had taken any preventative measures to help protect themselves from doorstep fraud. Only 14% of people were confident they could identify a doorstep scam if it happened to them. Currently utility engineers attending a property typically show their ID badges to gain entry which appears to be often effective. However, the above outlines how an increasing number of customers are likely to have been victims of doorstep fraud and therefore may be less trusting of unknown visitors. It also shows there is an increasing risk that fraudsters may pose as utility staff in order to gain access to someones home - a scenario which people are not confident in being able to spot, are unlikely to report and are not well equipped to deal with. It is also possible that customer metrics within a utility company do not reflect the actual picture given the very low public reporting of this type of fraud across the sector. | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 02/11/22 | |
