On Tuesday April 5, 2016, Perry Grossman and Shana Penna exhibited the Dataglen and Nebula solution at Connected Things 2016 at the MIT MediaLab. The event was very successful and we had good interest in the solution as well as some detailed discussions about the platform offering and the IoT board.
We discussed Dataglen’s goal to build analytics platform across many industries and the team’s background at IBM Research in Energy and the targeting of solar and wind farms in India. We showed the analytics from a solar farm and the benefits from identifying inverter faults and the analytics of energy generation by module temperature, ambient temperature, and solar radiation. The Dataglen Solar Power Presentation provides good material on this, particularly the diagram of panels, inverters, gateways, and the dashboard (Please contact Dataglen for a copy). We explained that Dataglen is doing data management at the gateway and articulated the benefits of the Dataglen dashboard and of notifications for plant operators. We talked about plans for advanced analytics, including machine learning, and how string level monitoring will allow more granular level data than that which is currently available at the inverter level.
We explained that Radiostudio, a Dataglen partner, is working on a string level IoT solution to identify string level issues such as dust, leaves, shading, faults etc. We exhibited the Nebula board, which is a a demo device for student use and a step toward providing string level monitoring. We demoed these features:
1) Temperature sensor
2) Humidity sensor
3) Reed switch
4) LED light
5) Relay actuation, through both a toggle on the browser and through a python script
6) Light sensor
The people we spoke to had a range of interests, including the following:
An MBA student was nterested in using Nebula to teach non-programmers to program; he thought Nebula could be great for that. Another educator was interested in using Nebula in IoT coursework.
A couple people asked about predicting future PV output, using machine learning, included analysis of cloud patterns, trends, and identifying maintenance needs based on historical needs.
A few people were interested in using remote sensors with Nebula, including monitoring attic temperatures to help identify potential ice dam issues.
A physician was interested in a health monitoring solution.
Exhibiting at Connected Things 2016 (#connectedthings2016) was a great experience and we look forward to future opportunities to showcase the solution.
-Perry Grossman
