AWS Announces Five Industrial Machine Learning Services

Amazon Web Services have announced the following five new industrial machine learning services.

• Amazon Monitron offers an end-to-end machine monitoring system comprised of sensors.
• Amazon Lookout for Equipment provides a way to send sensor data to AWS to build models for them and return predictions to detect abnormal behaviour.
• The AWS Panorama Appliance provides a new hardware appliance that allows organisations to add computer vision to existing on-premises cameras that customers may already have deployed.
• The AWS Panorama SDK enables hardware vendors to build new cameras that can run meaningful computer vision models at the edge.
• Amazon Lookout for Vision offers customers a high accuracy, low-cost anomaly detection solution that uses machine learning to process thousands of images an hour to spot defects and anomalies.

When used together, these new machine learning services aim to assist industrial and manufacturing customers to embed intelligence into their production processes. This improves operational efficiency, quality control, security and workplace safety.

The services integrate sophisticated machine learning, sensor analysis and computer vision capabilities to tackle the technical challenges faced by industrial customers. It is becoming more and more common for companies to add machine learning capabilities to industrial environments such as manufacturing facilities. Data is the connective glue that holds their complex systems together.

Numerous independent processes are prevalent in industrial systems as they operate with small tolerances for error, the most minor issue can bring about major ramifications. The ability to analyse data about equipment that is in operation in the workplace can help customers to address the challenge. Customers have embraced services such as AWS IoT SiteWise in order to gather data and generate real-time performance metrics.

Customers have begun to use the cloud to collate and analyse industrial data sets as well as asking for new ways in which they can incorporate machine learning to help them understand the data, driving operational efficiency. Some cases have shown that customers would like machine learning to help them realise the benefits of predictive maintenance, helping them to reduce costs and improving operational efficiency.