If you’re involved in the engineering of an Internet of Things (IoT) application for the agricultural space, there are a handful of considerations you’ll want to keep in mind. (Some people refer to wireless monitoring for farms as “smart agriculture,” “IoT agriculture,” or “M2M agriculture,” terms we’ll use interchangeably throughout this article.) IoT agriculture covers a wide variety of use cases, but you already know that one system won’t work for everything. So what are the key areas of focus you’ll need to keep in mind while you’re building out your product? We’ve detailed these questions below.
1. What will your application be monitoring?
Farmers, agriculturalists, and industrial food producers alike are looking at IoT solutions to increase efficiencies and yields and reduce loss and theft. In other words, they’re looking to optimize resources and lower costs through these innovative solutions. So, when you’re engineering something for the IoT agricultural space, you need to consider what you will be monitoring and why. Naturally, there are major differences here.
A corn farmer may be primarily concerned with water usage. He doesn’t want to use too much water, because water is becoming a scarce resource, but he also needs to be sure that enough water is getting where it’s needed so he doesn’t kill his crops. This is quite a bit different from real-time monitoring. A rancher wants to be able to locate a sick cow in her herd before it contaminates the rest of the animals. By doing this, she will dramatically reduce losses, and she can cut costs associated with purchasing antibiotics needed to treat a large group.
Whatever the end user will be monitoring should be front-and-center as you design the application. By doing this, the farmer may become more profitable.
2. How much wireless range is necessary?
The distance that data needs to travel makes a huge impact on what type of technology should be used. If you’re measuring something 10 meters away, you won’t use the same technology that you’d use for something 1500 meters away.
For something nearby, you may use radio frequency identification (RFID) or near field communication (NFC), which is common in cell phones. This may be used if you’re tagging a feedbag, and need to know how many pounds of soybeans are in each bag.
If you’re sending data to an object that’s 10 meters or closer, Bluetooth or Bluetooth Low Energy (BLE) might be good options. For example, you may consider engineering a Bluetooth ear tag for pigs living in a small area, which would tell the end user the swines’ ages and important information about them.
If your application needs to send data over hundreds or even thousands of meters, you might look at low power, wide-area network (LPWAN) options. A few examples include Symphony Link or other sub-GHz technologies. An application over this type of network might be used to measure soil moisture in fields or find and track livestock as they graze. This type of application is also ideal for fish farms that have large, fenced-in areas of aquaculture that need to be monitored but are difficult to access regularly.
3. Where is the power source coming from?
There is a very close correlation between battery life and range. A sensor that is very far away requires more energy to get information from one point to another. To get around that, IoT product creators often engineer applications to send much less data (or send data more infrequently) to save on costs and power efficiency.
So, you’ll need to determine where a sensor application will draw power from. Given that most IoT agriculture is typically outside or spread over a large area, you’ll need to consider something low power. Otherwise, the service and upkeep of many distant sensors will be overwhelming for the end user.
4. How often does the end user need to gather data?
You may think that the more data packets a sensor can send along the better, but this isn’t necessarily the case. It depends on many different factors, including the end-user application and the local environment. Let’s walk through a few examples.
If a farmer has a moisture sensor in a far away potato field, he likely doesn’t need to gather information every two seconds. Once or twice a day is probably sufficient, which means the battery life will be far greater. (And the farmer will really appreciate the extended battery life so he doesn’t have to find and service the sensor batteries regularly.)
On the other hand, if the application is going to be used to send GPS coordinates and other information gleaned by a tractor, sending near-constant data packets back to the gateway wouldn’t be difficult. After all, a tractor offers a perfect (and nearly unlimited) power source, so large amounts of data or video streams can be sent without clogging up the network. You can see how this is a lot different than our moisture sensor example, which doesn’t have a constant power source.
Another example is a comparison of tank leveling and irrigation. Many farms have large tanks that house fertilizer, fuel, or livestock feed. Monitoring the levels of these tanks more than once a day is probably unnecessary. On the other hand, when irrigation is on, continual updates can ensure that the right amounts of water are being released, and that there isn’t a leak.
All in all, before you create an M2M agriculture application, make sure you consider how much data is too much data.
5. What type of sensors are necessary, and how will they be interfaced?
Every wireless sensing technology is different, so you’ll want to consider which ones you’re going to use and how you’ll be interfacing with them before you get started. Some sensors—like moisture sensors—are very embedded, and they require microcontrollers to correctly interface. Creating the sensor itself and then weatherizing it so it’s able to be out in the field is an engineering challenge that would need to be met.
Positioning the sensor for an optimal communication path is another engineering challenge. If sensors are placed in an orange orchard, the many trees may interfere if the antennae aren’t mounted properly. This is obviously not as big of a challenge if an antenna is mounted in a strawberry field.
Remember this: The technology you engineer into your IoT agriculture application should not be a hindrance to what the end user is trying to measure. There are technologies that can cater to your end user, but give and take is associated with each of them. So, make sure you understand what your end user will need to measure; then, choose a solid technology to build around in order to get that information out.