Walking through one of the Halls at the Hannover Messe, you suddenly find yourself in the Cloud—computing that is. There was Amazon Web Services, Microsoft Azure, and Google Cloud. The Manufacturing IT section just keeps growing. And getting more interesting.

One interesting aspect—I’m beginning to see articles speculating on the “end of Cloud computing.” Wonder what could come next?

Meanwhile, here is one piece of Cloud news I picked up. Amazon Web Services (AWS), an Amazon company, announced the general availability of AWS IoT Analytics, a fully-managed service that makes it easy to run simple and sophisticated analytics on massive volumes of data from IoT devices and sensors, empowering customers to uncover insights that lead to more accurate decisions for their IoT and machine learning applications.

AWS IoT Analytics collects, pre-processes, enriches, stores, and analyzes IoT device data at scale so companies can easily identify things like the average distance traveled for a fleet of connected vehicles, or how many doors are locked after work hours in a smart building, or assess the performance of devices over time to predict maintenance issues and better react to changing environmental conditions. With AWS IoT Analytics, customers don’t have to worry about all the cost and complexity typically required to build their own IoT analytics platform. AWS IoT Analytics is available today in the US East-1 (N. Virginia), US East-2 (Ohio), US West (Oregon), and EU (Ireland) regions, with support for additional regions coming soon.

“AWS IoT Analytics is the easiest way to run analytics on IoT data. Now, customers can act on the large volumes of IoT data generated by their connected devices with powerful analytics capabilities ranging from simple queries to sophisticated machine learning models that are specifically designed for IoT,” said Dirk Didascalou, VP, IoT, AWS. “As the scale of IoT applications continues to grow at a rapid rate, AWS IoT Analytics is designed to provide the best tools for our customers to mine their raw data, gaining insights that lead to intelligent actions.”

AWS IoT Analytics also has features like a built-in SQL query engine to answer specific business questions and more sophisticated analytics, enabling customers to understand the performance of devices, predict device failure, and perform time-series analysis. Also, AWS IoT Analytics offers access to machine learning tools with hosted Jupyter Notebooks through seamless integration with Amazon SageMaker. Customers can directly connect their IoT data to a Jupyter Notebook and build, train, and execute models at any scale right from the AWS IoT Analytics console without having to manage any of the underlying infrastructure.

Using AWS IoT Analytics, customers can apply machine learning algorithms to device data to produce a health score for each device in a fleet, prevent fraud and cyber intrusion by detecting anomalies on IoT devices, predict device failures, segment fleets of devices, and identify other rare events that may have great significance but are hard to find without analytics. And, by using Amazon QuickSight, a fast, cloud-powered business analytics service, in conjunction with AWS IoT Analytics, it is easy for customers to surface insights in easy-to-build visualizations and dashboards.

AWS IoT Analytics can accept data from any source, including external sources using an ingestion API, and integrates fully with AWS IoT Core. Launched in 2015, AWS IoT Core is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT Analytics also stores the data for analysis, while providing customers the ability to set data retention policies.

Modjoul, Georgia Pacific, Teralytic, Siemens, OSIsoft, Pentair, 47Lining, Domo, NetFoundry, and Laird Technologies are just a few of the customers and Amazon Partner Network members using AWS IoT Analytics to uncover valuable insights within their data and use those findings to innovate across their specialized businesses.

Modjoul is a data invention company for wearable technology that is focused on keeping employees safe. “Our mission is to keep industrial workers safe, whether they’re working in or out of a vehicle,” said Eric Martinez, CEO and Founder, Modjoul. “In an eight-hour shift, we collect data 28,800 times per day from our connected activity tracker worn by each of our employees that includes 40 metrics including heart rate and activity level. With AWS IoT Analytics, we not only analyze all that health data, but also enrich it with location and environmental data, such as outdoor temperature, to get accurate analytics that prevent injuries and save lives. Today, we’re operating better and faster.”

Georgia Pacific is one of the world’s leading makers of tissue, pulp, paper, packaging, building products, and related chemicals. “At Georgia Pacific, our industry-leading dispensers allow us to deliver solutions to customers, not just sell products,” said Erik Cordsen, IoT Program Architect and Product Leader, Georgia-Pacific. “Now we are focused on making our dispensers ‘smart’ by adding sensors and connectivity that allow us to improve customer experience by providing real-time information about product levels and other statistics. With thousands of endpoints continuously feeding in data, we are using AWS IoT Analytics to enrich messages with location and product metadata in order to calculate platform health and value to our customers. AWS lets my team focus on solving the business problem instead of wrestling with technology.”

Teralytic is a soil health company focused on improving farmer’s yield by monitoring and improving the condition of their soils. “We have a network of soil-sensing IoT devices embedded in the soil from which data are collected, fed, and analyzed for us to understand the health of our customers’ agricultural ecosystems,” said Dan Casson, Vice President of Engineering, Teralytic. “We chose AWS IoT Analytics for its ability to filter outlier readings from our calculations and proactively detect issues as they arise so we can resolve them faster. In some cases, we’re able to identify and prevent issues before they occur. With AWS IoT Analytics, we use Machine Learning models to help detect situations where nutrients in the soil are at risk of leeching into ground water or runoff into surface water so the farmer can adjust the watering schedule, if needed. In addition to the environmental benefits, these machine learning models can help reduce a farmer’s costs as well as potentially increasing their yield.”

47Lining develops big data solutions and delivers big data managed services — built from underlying AWS building blocks like Amazon Redshift, Kinesis, Amazon Simple Storage Service (Amazon S3), and Amazon DynamoDB — to help customers manage their data across a variety of verticals including energy, life sciences, gaming, and financial services. “Because AWS IoT Analytics is designed around time-series data, it’s a great fit for our customers in industrial, energy, and oil & gas, who seek real-time decision support and process optimization,” said Mick Bass, Senior Vice President, Big Data Practice, 47Lining.

Domo is a computer software company that specializes in business intelligence tools and data visualization. “Since our inception in 2010, AWS has been a trusted service provider that keeps up with the demands of our dynamic business,” said Jay Heglar, Chief Strategy Officer, Domo. “We extended our relationship with AWS to IoT Analytics because we wanted a flexible option to enable faster access to machine-generated data for our customers. Through our proprietary connector to AWS IoT Analytics, we are ensuring our customers have access to one of the most innovative solutions, allowing them to leverage machine-generated data at scale.”

Laird Technologies designs, develops, manufactures, and supports wireless systems solutions and performance materials for wireless and other advanced electronics applications. “By combining our long range wireless sensor and gateway products with AWS IoT, our customers have been able to quickly and securely get data from their devices into the cloud,” said Paul Elvikis, Business Development Director for Industrial, Laird Technologies. “Unfortunately, they would often get overwhelmed with the amount of sensor data that would start coming in. Customers would struggle to figure out how to do anything with it. AWS IoT Analytics has been a great help in extending our capabilities to solve that issue for our customers.”

NetFoundry gives its customers and their applications control of their networks without any telco, hardware, or private circuit constraints. “The capabilities of AWS IoT Analytics in enabling the transformation of vast amounts of data into actionable information, without the high costs and steep learning curve of other IoT platforms, enables NetFoundry’s IoT customers to get the ROI they need,” said Michael Kochanik, Co-founder and Global Head of Channel Revenue, NetFoundry.“With AWS IoT Analytics, we can integrate IoT networking capabilities to provide our IoT customers with ‘one-stop shopping’ including data collection, networking, analysis, transformations, storage and visualization. Partnering with AWS enables our customers to get integrated, end-to-end agility, security, performance and cost efficiency at scale.”

AWS offers over 125 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 54 Availability Zones (AZs) within 18 geographic regions and one Local Region around the world, spanning the U.S., Australia, Brazil, Canada, China, France, Germany, India, Ireland, Japan, Korea, Singapore, and the UK.

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