Industrial internet of things solution provider Relayr has drawn on Microsoft Azure services to optimise remote monitoring solutions for elevators.
Relayr has used the cloud to collect and analyse sensor data from devices since it was founded in 2013. The company today receives approximately 100 million pieces of sensor data per day from around 50,000 connected devices. Its data scientists use this data to train and improve machine learning (ML) models and increase the precision of artificial intelligence (AI) analyses and predictions.
Relayr introduced Microsoft Azure as its new cloud platform in 2020 after its original cloud architecture was no longer able to handle the volume of orders and data. The firm then began migrating all the relevant microservices in 2021.
“Our chief technology officer and data scientists agreed that we had to move away from this approach,” said Nico Wintergerst, staff AI research engineer at Relayr. “Deployment is quicker than it could have been with our old technology.”
Azure stores data gathered from Relayr’s on-site Franz boxes, devices installed on the roof of the elevator that continually collect data on location, speed and from the door’s motor. This then trains ML models to identify anomalies in the data and proactively fix issues before they occur.
Relayr’s solution benefits maintenance companies by allowing them to instantly view information without being on site. Staff are alerted to deviations in data, which can improve day-to-day planning, cut costs and increase customer satisfaction.
“We’re now able to get a functioning model with relevant insights up and running in just a couple of weeks thanks to Azure ML,” said Wintergerst. “We’re expanding our Azure reference architectures to encompass the entire life cycle of connected devices and systems.”
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