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AWS brings IoT, machine learning to the ‘edge’


November 30, 2017  


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This week at AWS re:Invent in Las Vegas, Amazon Web Services, Inc. (AWS), an Amazon.com company, announced six services and capabilities for connected devices at the edge.

The company says that AWS IoT 1-Click, AWS IoT Device Management, AWS IoT Device Defender, AWS IoT Analytics, Amazon FreeRTOS, and AWS Greengrass ML Inference make getting started with IoT as easy as one click, enable customers to rapidly onboard and easily manage large fleets of devices, audit and enforce consistent security policies, and analyze IoT device data at scale.

Amazon FreeRTOS is an operating system that extends the functionality of AWS IoT to devices with very low computing power, such as lightbulbs, smoke detectors, and conveyor belts.

Meanwhile, AWS Greengrass ML Inference is a new capability for AWS Greengrass that allows machine learning models to be deployed directly to devices, where they can run machine learning inference to make decisions quickly, even when devices are not connected to the cloud.

“The explosive growth in the number and diversity of connected devices has led to equally explosive growth in the number and scale of IoT applications,” said Dirk Didascalou, vice president of IoT at AWS. Today, many of the world’s largest IoT implementations run on AWS, and the next phase of IoT is all about scale as we’ll see customers exponentially expand their fleet of connected devices.

“These new AWS IoT services will allow customers to simply and quickly operationalize, secure, and scale entire fleets of devices, and then act on the large volumes of data they generate with new analytics capabilities specifically designed for IoT.

“With Amazon FreeRTOS, we’re making it easy for customers to bring AWS IoT functionality to countless numbers of small, microcontroller-based devices. And, customers have also told us they want to execute machine learning models on the connected devices themselves, so we’re excited to deliver that with AWS Greengrass ML Inference.”

According to an AWS press release, when considering IoT, “many customers just want an easy way to get started by enabling devices to perform simple functions. These are functions like single-button devices that call technical support, reorder goods and services, or track asset locations.”

The new AWS IoT services  manage, secure, and analyze the data generated by large fleets of devices

“At scale, IoT solutions can grow to billions of connected devices. Today, this requires customers to spend time onboarding and organizing devices, and even more time integrating multiple systems to manage tasks like monitoring, security, auditing, and updates,” the company said.

“Building solutions for such tasks is time consuming and easy to get wrong, and integrating third party solutions is complex and may introduce hard-to-detect gaps in security and compliance. Once a device fleet is operationalized, analytics is often the next challenge customers face. IoT data isn’t the highly structured information that most existing analytics tools are designed to process. Real-world IoT data frequently has significant gaps, corrupted messages, and false readings, resulting in the need for customers to either build custom IoT analytics solutions, or integrate solutions from third parties.”

Full coverage of the conference will appear online soon and appear in an upcoming issue of Connections+.


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