(00:03) At the SEMICON West 2016 conference, ReadWrite sponsored the Industrial IoT Hackathon. The grand prize for Best Overall Industrial IoT Solution included a cash prize of $5000 US, an Amazon Alexa Device for each team member, and a spot in the Wearable IoT World Labs Accelerator.
All of the winning projects using IBM Bluemix, IBM Watson, or IBM Watson IoT services to implement their Industrial IoT Solutions.
First project: Team EcoByte – Pollution Awareness Platform for Cities (Winner of Amazon’s best use of Alexa technology prize and Grand Prize winner)
(00:18) A pollution awareness platform for the smart city that provides interactive environmental information for the residents enabling enhanced well-being. Air pollution is a growing problem around the world. Integrated platform to help the city and all its residents. Their platform has smart air quality sensors, Intel Edison boards connected to gas monitors… These nodes would be placed around the city and monitor the air pollution levels. The data from the sensors go up to the cloud, and then it is published to a Twitter feed using the IBM Bluemix platform and also to an IFTTT channel to make the data accessible to users. Data could be accessed on smart devices, such as Alexa, which you can ask Alexa whether you should go outside today, and Alexa uses the data to give you an answer.
Second project: Team Leo – Smart Irrigation System (Winner of IBM’s best use of Watson IoT and Cognitive APIs prize)
(06:30) Their smart irrigation system project tackles the California water drought problem. It uses the stress monitoring technology and soil sensing data to identify different watering methods to help address the drought problems. Their system uses the Intel Edison board with 4 sensors attached to it: moisture sensor, temperature sensor, UV sensor, and water sensor. Using a Node-RED app, the sensor data is sent up to the IBM Watson IoT Platform in the IBM Cloud, then the Weather Insights service and Watson cognitive services analyze the data, and appropriate actions are sent to the sensors and monitors back down on the Edison board.
Third project: Rahul Dubey – Edge and Cloud Based Energy Optimization of Retail Freezers (Winner of Intel’s best use of Intel technology)
(11:57) Industrial IoT has many layers of control. His solution sets up two tiers of control – edge controllers that are close to the freezer units and an analytics engine in the cloud. He used Node-RED apps at both tiers of his IoT solution. The edge controllers that used Grove sensors gathered temperature data and data about opening the freezer door. His analytics engine uses Watson IoT Platform in the IBM Cloud to optimize systems using information gathered from IoT sensors and devices.
Fourth project: Service IoT Team – Winner of Samsung’s Best Use of Technology for Samsung ARTIK Cloud
(16:41) Connect all the sensors to the machines in the factory, and sensors send their data (temperature and noise level) to all of the ARTIK Clouds, which record everything. He used Slack’s chat bot to query the data as it is coming in. His solution used a natural language processing engine to ask allow him to ask what the problem is. Then, it used IBM Watson and one of its retrieval ranking algorithm to locate an appropriate fix for the problem. Lastly, his data was displayed in charts in a dashboard on ARTIK Cloud. He talked about his next steps would be to add predictive analytics to the IoT solution.
More, more, more
John Walicki blogged about these hackathon winners in the Watson IoT Platform developerWorks community
You can also see John Walicki’s demo of how to use IBM Watson IoT Platform at the hackathon.