The concept of Precision Agriculture consumes a great deal of human capital in the study, development, and expansion of the Precision Ag ecosystem, as well as a great deal of a farmer’s time in practice. Several key disciplines are required in the Precision Ag ecosystem, and while Big Data is getting a lot of the attention lately, understanding how the data is acquired can provide a greater understanding of a farm. This brings us to the Internet of Things (IoT) and its practice in Agriculture.
IoT is defined in a variety of ways, but in general the concept is connecting everyday objects to a network so that relevant information is reported back to a consumer. In the case of agriculture this could be as simple as an alert on your smartphone that your vehicle in the field is below a quarter tank of fuel and needs to be filled, or a desktop application that takes data from the field to determine an optimum nitrogen prescription. In either case, sensors must gather and report data for analysis so that an informed decision can result in improved profitability. All of this may seem abstract, but a few examples generally provide greater context and improved understanding.
Where did my cattle go?
Imagine it’s winter. There is 18 inches of fresh snow on the ground, and the wind is conveniently blowing at 30 MPH. You go to move the herd under shelter to minimize livestock loss, and discover that there are three cattle missing. If every animal has a GPS ear tag, you could pull up an app on your smart phone and determine the location of each animal. You can then get to them quickly and move them in with the rest of the herd, avoiding loss of livestock.
Alternatively, perhaps you have put the herd out to graze the harvested corn field that is 640 acres. As you bring them all in to take back to the feedlot, you realize you are several head short. So you pull up your mobile app and track where they are to immediately minimize your time searching. Maybe one even left your field boundary; you could be alerted whenever your livestock leave a predefined area (geofence) and avoid having to bother your neighbor for help. In any of the above scenarios, time is money and saving this time can allow you to accomplish more.
Small, remote sensors, such as a GPS tag in this example, can send data across a network, exact location data in this case, so that an application can process it and present it to you in a value added fashion. The examples that can be presented extend to planting, harvesting, and general daily operations for the modern farmer.
Have a better understanding of how IoT relates to Agriculture now? What other applications can you think of? Share with us in the comments!