TensorIoT teamed up with AWS to create a solution to visualize data on a new technique for growing animal feed.
How can we measure things like weight, height, evenness, air quality, and water quantity for indoor crops, and then display that information in a way that the client can use to infer actionable insight and inform their next iteration?
To create the solution, the team installed various sensors along the crop’s lifecycle, and then fed the data collected by the sensors into a custom-designed UI.
As Earth’s population continues to grow, the United Nations estimates that demand for meat will grow by 70% and dairy demand will increase by 55% by 2050. To sustain the animals that we rely on, farmers must find affordable, efficient, and dependable sources of food for their livestock. Traditionally grown feed is subject to weather, water availability, and price fluctuations, often making it difficult for farmers to maintain steady supplies. The client, an agricultural start-up, is developing a method of growing feed crops indoors, and needed more data on their production to continue iterating and improving their process.
To start, the team needed to figure out how to hook up sensors that could measure various attributes of the growing wheatgrass throughout its lifecycle. With environmental constraints in mind, we had to look for unique solutions to calculate metrics like grass height, evenness of the grass, weight, and watering quantity. After collecting the data, we also needed to design a way for the client’s operators and scientists to visualize what was happening to the grass as it grew, and be able to look for trends and anomalies that could inform their next iterations.
The Tensor team installed a suite of carefully selected sensors to quantify the lifecycle of each palette of grass, including computer vision cameras to measure evenness, customized weight sensors, lasers to measure height, and moisture sensors. As the grass traverses through the mechanized housing unit, the sensors measure the grass and send the data back to the cloud. The custom designed UI then visualizes the data coming through, helping the client’s operators and scientists gain a better understanding of what’s happening with the grass.