Inaugural New York Open Source IoT Summit a Resounding Success

DataArt, in partnership with Microsoft and Canonical, hosted its first annual Open Source IoT Summit in New York City. On November 12, 2015, six dozen technology innovators gathered at Microsoft’s New York Conference Center on Times Square to learn how they can develop their own in-house IoT solutions. DataArt has always been supporting open innovation movement, which is at the heart of new technology development, and our open source IoT device-management platform DeviceHive is a testament to that. DeviceHive runs on Canonical’s Ubuntu, is available on the Microsoft Azure Marketplace and provides the tools to solve any smart manufacturing or smart home challenge in-house, without costly investments in software solutions. At the summit, we showed how DeviceHive accelerates IoT product development, allows for creating a solution prototype in a matter of hours, and then deploying and scaling it to a limitless number of devices or control variables with no additional software or investments requirements. We walked the audience through the design, prototyping, deployment, and scaling up of a predictive maintenance IoT solution, enabling preventative, condition-based monitoring of a piece of manufacturing equipment. We used accelerometer-based sensors and an IoT gateway to capture the vibration profile of a fan and analyzed it in the Microsoft Azure Cloud using Juju, to determine whether it’s in the range of a normally operating equipment, and if not – to trigger a maintenance alert. Continuously monitoring manufacturing environments for hazards and having the option to prompt people (or even machines) to take corrective action to avoid damage or interruption, can significantly reduce manufacturing risks and costs. Device connectivity enables more than just monitoring and predictive maintenance, it ultimately allows for precise control and management of critical assets, automation of tasks and decision-making, and optimization of processes across the manufacturing value chain. That covers R&D, sourcing, production and outbound logistics which helps attain major reductions in waste, energy costs, and human intervention, leading to vast improvement in efficiency. While manufacturing is the area where IoT is an obvious game changer, IoT presents a rich opportunity for all areas of our lives. Examples include a heart monitor implant that alerts care providers of important changes in a patient’s heart condition, a car with built-in sensors that alerts the owner’s phone when tire pressure becomes low or emissions high, or precision farming equipment with wireless links to data from satellites and ground sensors that adjusts the way each part of the field is farmed based on different soil and crop conditions. IoT can be used to build a home automation system that customizes home devices to the habits of its residents, eventually enabling smart cities: monitoring customers’ power usage behavior, managing power demand and supply to optimize city-wide electricity usage, enabling remote monitoring and maintenance of gas pipeline networks, or installing billboards that assess approaching human traffic and change display messages accordingly. Connected devices are here to stay. Embracing the objects’ ability to sense their environment and communicate about it presents unprecedented opportunities and insight across industry sectors and processes. The greatest challenge ahead is learning to convert vast amounts of data into actionable insight, to make sense of complexity and respond to it swiftly, eventually enabling machine learning and minimizing human intervention. DataArt and its partners look forward to continued sharing of our experience with the IoT community. We welcome new partnerships to create value through new Internet-of-Things capabilities.
Read More »

Open Source IoT Solutions on Azure

Open Source IoT Solutions on Azure

DataArt, the maker of DeviceHive, and Canonical, the maker of Snappy, Ubuntu and Juju, present Open IoT Solutions on Azure Events.

DataArt and Canonical are demonstrating industrial preventive maintenance and home IoT scenarios, that can be prototyped, scaled, and deployed. DataArt’s DeviceHive running on Canonical’s Ubuntu VM, are available on the Microsoft Azure Marketplace, providing accessibility to a flexible IoT platform. New bundled IoT solutions and examples, DeviceHive on Snappy (RPii), Data Analytics stack deployed by Juju, and Microsoft Azure services, will be discussed and demonstrated.

Want to receive updates? Subscribe here!

Ready to visit the event? Find the details here!

The event will take place at Microsoft's New York Conference Center, Central Park East (6th fl, 6501a). November 12, 2015. 1 pm - 5 pm. 11 Times Square, NYC.

Read More »

Strata+Hadoop World NYC 2015 Reflections

Machine learning, cloud, visualization, Hadoop, spark, data science, scalability, analytics, terabytes, petabytes, faster, bigger, more secure, simply better. The kind of a merry-go-round that keeps spinning in your head after you spend three days on the exhibit floor at Strata+Hadoop conference. And lots of elephants, of course
Not only did we attend Strata with fellow colleagues from DataArt and DeviceHive, we also helped our friends at Canonical and brought our demo to their booth. Canonical was showing Juju: a cloud infrastructure and service management tool. We brought our favorite demo: industrial equipment monitoring rig. No PowerPoint slides, only real stuff. A Texas Instruments SensorTag’s accelerometer attached to a fan to monitor its vibration. To simulate the vibration we used a piece of duct tape attached to one of the blades to set the whole thing off balance. Sensor data was streamed using DeviceHive, generating time series data, which was aggregated by Spark Streaming and displayed on a nice dashboard. Everything deployed using Juju, working nicely in AWS. While the exhibition floor had a lot of great companies pitching their awesome products, I think the main highlight of this year’s event was Spark. Learning Spark, running Spark, managing Spark, using Spark for this and using Spark for that. Almost everyone, big or small, was talking Spark, integrating it into their solutions or making their data accessible through Spark. In just a few years Spark has proven to be a great platform for data discovery, machine learning and cluster computing in general. Spark ecosystem will keep expanding, changing the way we work with our data, increasing velocity of data-related projects. Next generation analytics tools will surely interface with Spark or rely on Spark, allowing enterprises to push the envelope of what can be derived from their data. Next generation parallel computing tools will bring business, engineers, data scientists and devops closer together. Databricks, a company commercially supporting Spark, was demonstrating their data analytics product which allowed to create research notebooks and interactively write Spark jobs, run them on AWS cluster, create queries and visualize data. On top of that add Spark Streaming and you can execute your models on a live stream of data. While Databricks is hosting the landing page for the UI, your data as well as the machine to host the infrastructure to run Spark resides in your AWS environment. I’m curious to know how it will compare with Amazon’s Space Needle they are unveiling at re:Invent 2015 in Las Vegas. Besides Spark, it is also becoming apparent, that working with data at large is no longer about a particular choice of a right database or distributed file system. Data platforms are coming. The world is starting to think in terms of data platforms: a set of technologies and architecture patterns designed to work together to solve a variety of data-related problems. Data platform largely defines how we access, store, stream, compute and search structured, unstructured, sensor generated data. A solid example of such a platform is Basho Data Platform where Basho is taking its Riak database and making it a part of something much bigger than a Key-Value store. Personal improvement takeaways:
  • Hack on public data in Spark
  • Keep learning and using Scala
  • Functional programming
  • Functional programming
  • Functional programming
Read More »


DeviceHive platform arrives on Azure Marketplace

DeviceHive platform arrives on Azure Marketplace

The industrial Internet of Things (IoT) enables businesses to predict when industrial equipment is going to fail, so that action can be taken beforehand. A leader in this space, DataArt, developed one of the first IoT and big data open sourced platforms, DeviceHive, and published on the Microsoft Azure Marketplace. DataArt has collaborated with Canonical, the company behind Ubuntu, as well as Microsoft.
Read More »