AI Case Study
EDF Energy is testing automatic recognition of the figures on meter readings achieving 79% accuracy
EDF has been testing AI for automatic character recognition. It aims at using the technology to read and process the figures on meter readings, an otherwise manual procedure. Until now, the company's optical character recognition system has managed to recognise meters' digits with a 79 percent accuracy. EDF also aims at using machine learning to extract important information and patterns of its customers energy consumption based on the collected usage data.
"On the customer-facing side EDF has been testing AI to perform character recognition to pick out and process the figures on metre readings sent in by energy customers.
So EDF developed an optical character recognition system to "crop the digit zone, process it and we managed to recognise the digits with a 79 percent accuracy," Ferguson said. "This was a few years ago so we are going to have another go at this using more modern techniques."
Now, like many of its peers, EDF is looking towards AI to help make sense of the vast amounts of data it is receiving from customer's smart metres. Working with AWS (presumably the AWS IoT platform), EDF is able to 'collect data from smart metres and thermostats and really begin to examine it and apply machine learning to tease out interesting information.'
This allows the energy provider to 'cluster and segment our customers based on what they actually do' for the first time, according to Ferguson."
79% accuracy in recognising the figures on energy customers' meter readings
"EDF developed an optical character recognition system"
"EDF Energy is one of the biggest energy suppliers in the UK with a network of nuclear, coal and renewable power stations." David Ferguson's team, head of digital innovation at EDF, is "responsible for designing proof of concepts 'to demonstrate the value and potential of new technologies. It is our job to move fast and break things, in a controlled environment', he said.
Previously, EDF was receiving photos of metre readings via its mobile app and sending them to an offshore centre. There "it was looked at by a human who wrote down the numbers and entered it into our system," Ferguson said."