From Cows to Canvas: Monitoring Farm Emissions in Grafana

In this talk, Sunil Golpalakrishna discusses the use of Grafana for monitoring emissions in partially ventilated barns used for livestock. He outlines the challenges of measuring emissions such as ammonia and carbon dioxide due to the barns' design and variability in animal presence. Sunil describes a Sensor Array Measuring Ball equipped with low-cost sensors that collects data which is transmitted via LTE. He explains how, despite certain limitations, InfluxDB was selected as the database solution and how Grafana was utilized to create an interactive dashboard. The dashboard provides real-time insights into emissions, barn conditions, and data completeness, facilitating better understanding and management of livestock barn environments.

- Hi, good evening. My name is Sunil Golpalakrishna. I work as a researcher at Thünen Institute of Agriculture Technology in Braunschweig, Germany. I'm gonna talk about how I'm using Grafana for this particular use case where we have sensors built into barns and hence the title, From Cows to Canvas Panels. We have traditionally closed barns. So barns, housing animals, could be cows, could be pigs, could be hen.

And we have changed this build for the last decade or so. We have now a partially ventilated barn. That means we have bay areas where you can see pigs, they come out of these barns, get some fresh air, do their business, get some sun, go back in. Now it becomes very difficult to measure emissions when you have such barns which are, or which have these bay areas.

What happens here is you try to measure emissions in this region and due to winds, due to different scenarios of animals being there and not being there, it becomes pretty difficult. So I work with, in a project that we are trying to measure such barns or emissions from such barns and we developed a Sensor Array Measuring Ball. It consists of four sensors, low cost sensors, measure ammonia,

carbon dioxide, particulate matter, and partial, sorry, differential pressure. And when we're doing this, we get this data from these sensors and we wire each of these sensor balls with each other and send them to telecommunication towers or LTE. And if you look, we try to place them at the interface of these barns and they're all wired to each other. And it's also a possibility that we can

scale these balls up. So let's say we can do 50 balls and try and measure the emissions. And once we have these sensor values, we try to send them using wifi. We have tried it, but it's not easily possible because we are in some locations where there's basically no connection. So we use LTE and some of this data looks like this. And this data in turn, as

I would say, a hundred kilobyte file because of this packages, we have time-indexed data. So basically, from the left to the right, you see time and particulate matter, carbon dioxide, ammonia values. And this is important for us because we are trying to see how much of ammonia emissions, how much of carbon dioxide is emitted from these such barns, right? And once we have this data, it could

gather up and basically create gigabytes of data, which doesn't happen at this point in time because we are doing campaign measurements, we have measurements happening between seasons. So I decided to go ahead and use an open source solution that was InfluxDB. And in this scenario, you could see I have a few buckets, and from these buckets I could get the data from each of these spheres and

also plot them against time. So this is what it looks like. But there were some engineers between us. There were some technicians who realized this doesn't help them so much. So then I thought about it and I decided I would go ahead and use Grafana. And I created a dashboard. And you can see, from top to bottom, I specified what kind of barn it was and how

many spheres are we having on these barns and the concentration with respect to time. And I used the Canvas panel to actually try and create the layout of the barn and the spheres in the barn. And if you look on the top, you can see from each of these spheres we have data in terms of the emissions. And also, I can check and relate the humidity or

other factors from the sphere. And I also have other inputs like this video or two videos from different barns from our partners. So they have been installed. And if you look carefully, I don't think it's installed here, our spheres are also being installed across these barns. And that also helps us to correlate the spikes in these emissions. And we also have annotations on each of these emission

values so that we could actually say what period of time we measured, basically talking about the growth period or the fattening period, or if there was an anomaly because we have two or three pigs added or cows added to this barn. And I also created something like the data completeness here. It makes sense if it's live because then you can actually see in an hour how much

data was received. And if it goes down, then we already know that the sensors or the server itself has an issue. So what I would like to conclude here is that it is possible to use an open source tool like Grafana for this such a use case. And you can basically see what's happening here. We pull the data from the spheres, we calculate the velocity separately using

the partial differences, and then send it to the Influx. And basically, then you have a dashboard. I use the Canvas panel. I'm a bit, I would say I would like few more additional features in the Canvas panel. I had a great talk with a few of the experts here. And also, I'm very thankful to the community here because I was able to go on the forums and

ask questions. I thank you all. Finally, I would like to thank the partners and the team members in my institute. And with that, thank you so much. (audience applauding)