EHS problems owing to air quality in plants can be traced to smoke, fumes and emissions, which vary in their toxicity based on type of industry. Drop in efficiency with poor working conditions.
What it does
Unified approach to collect environmental data from multiple premises / sensors and ingest into Predix Cloud.
How we built it
Started on the analysis of the most common factors which affect air quality and derivations of the algorithms for the calculation of air quality. [Reference: National Pollution Control Board, India] As monitoring and control involves IoT, we selected one of the best IoT platforms for implementing the solution - Predix.
We call it "IoT for Good" as this is the first step towards full fledged EHS and help organizations reduce their carbon footprint.
We started off with standard Predix tech stack, designed crisp UI, defined microservices. IN order to mimic the real-time data, we incorporated the Predix data simulator and to further prove it with actual data, we picked up Raspberry-pi along with Arduino. Following sensors were deployed on our Raspberry-pi: Temperature, Humidity, gas and air quality.
In order to facilitate quick response, we incorporated Slack for alerting on mobile devices.
Further, in quest of making IoT more accessible and reducing the cost as well as e-waste, by re-using Android devices as our IoT devices - we successfully deployed Predix machine to kick off the idea of any Android as our IoT device via Predix Machine. These Android devices can use wireless sensors and OTG based sensors.
Challenges we ran into
Predix Machine integration with Raspberry-pi, Time Series Issuer conflicts
Accomplishments that we're proud of
Successful deployment of Predix Machine on Android Raspberry-pi to collect air quality and hygiene information
What we learned
More insights on Predix Machine
What's next for TCS-Cassini Industrial Air Quality Monitoring
Domain agnostic, interoperable solution supported by Analytics of Things for real time insights, unique or novel co-relations