AWS Introduces A New Initiative, AWS for Industrial

‘AWS for Industrial’ is a new initiative that features new and existing services and solutions from AWS and its Partners, which are built specifically for developers, engineers and operators at industrial companies.  This initiative simplifies the process for customers to build or deploy innovative Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), analytics and edge solutions to achieve step change improvements in operational efficiency, quality, and agility.

To address industrial use cases that require near real time decision making, AWS provides five new purpose-built services bringing AI and ML to industrial environments, born out of complex automation and factory operations of Amazon.  These new services enable customers to use machine data to predict when equipment will require maintenance and to use computer vision (like images from existing camera feeds) to improve processes, identify bottle necks and detect anomalies, real-time – with no machine learning expertise required.

Using machine data to predict when equipment will require maintenance:

• Amazon Lookout for Equipment. AWS Lookout for Equipment is an anomaly detection service for industrial machinery. It uses data from equipment tags and sensors, and historical maintenance events to detect abnormal equipment behavior.
• Amazon Monitron. Amazon Monitron is an end-to-end system that detects abnormal behavior in industrial machinery, such as motors, gearboxes, fans, and pumps, enabling customers to implement predictive maintenance and reduce unplanned downtime. It includes sensors to measure vibration and temperature, a gateway device, and a mobile app to set up devices and track and review potential failures in equipment.

Using computer vision to improve processes, identify bottle necks and detect anomalies:

• Amazon Lookout for Vision. Amazon Lookout for Vision enables customers to spot industrial product defects and anomalies using computer vision, accurately and at scale. Customers can automate real-time visual inspection for processes like quality control and defect assessment by analyzing images from cameras that monitor the process line. Amazon Lookout for Vision identifies missing components, damage to products, irregularities in production lines, and even minuscule defects in silicon wafers such as a missing capacitor on a printed circuit board.
• AWS Panorama. AWS Panorama is a machine learning appliance and SDK, which enable customers to add computer vision (CV) to existing on-premises cameras or to new Panorama enabled cameras. It gives customers the ability to make real-time decisions to improve operations, automate monitoring of visual inspection tasks, find bottlenecks in industrial processes, and assess worker safety within facilities.
  • The AWS Panorama Appliance turns existing onsite cameras into powerful edge devices with the processing power to analyze video feeds from multiple cameras in parallel and generate highly accurate predictions within milliseconds. With a dust resistant and waterproof appliance, customers can install devices in different environments without compromising functionality.
  • The AWS Panorama SDK enables hardware partners to build new Panorama enabled devices that run more meaningful CV models at the edge and offer a selection of edge devices to satisfy different use cases. New Panorama enabled devices, coming soon from partners including ADLINK Technology, Axis Communications, Basler AG, Lenovo, STANLEY Security, and Vivotek.

AWS IoT services to securely collect, organize, and monitor industrial data at scale.

• AWS IoT SiteWise. AWS IoT SiteWise is a managed service that makes it easy to collect, store, organize and monitor data from industrial equipment at scale to help customers make better, data-driven decisions in optimizing their operations.
• AWS Snowcone. AWS Snowcone is the smallest member of the AWS Snow Family of edge computing, edge storage, and data transfer devices. It is ruggedized, secure, and purpose-built for use outside of a traditional data center, and Its small form factor makes it a perfect fit for tight spaces or where portability is a necessity. Customers can execute compute applications at the edge and can ship the device with data to AWS for offline data transfer or can transfer data online with AWS DataSync from edge locations.
• AWS Snowball Edge. AWS Snowball Edge, a part of the AWS Snow Family, is an edge computing, data migration, and edge storage device that customers use for data collection, machine learning and processing, and storage in environments with intermittent connectivity or in extremely remote locations before shipping them back to AWS.
• AWS Outposts. AWS Outposts is a fully managed service that offers the same AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. AWS Outposts is ideal for workloads that require low latency access to on-premises systems, local data processing, data residency, and migration of applications with local system interdependencies.
• Amazon Lake Formation. Setting up and managing data lakes involves manual and time-consuming tasks such as loading, transforming, securing, and auditing access to data. AWS Lake Formation automates many of those manual steps and reduces the time required to build a successful data lake using Amazon S3, from months to days.