Farming is getting smarter every day. From large commercial operations to local organic growers, technology is at the forefront of reducing cost, improving yield and guaranteeing optimal delivery to market. The key ingredient in smart agriculture is data.
Modern farmers have more tools for gathering intelligence than ever before. Soil chemistry data informs fertilization decisions. Moisture sensors and precision irrigation controllers optimize irrigation, while reducing water consumption. Drones precisely apply pesticides. Autonomous harvesters traverse fields under the watchful eye of location and capacity sensors. The list goes on. Almost every agricultural process can be instrumented using sensors generating data that can optimize processes and inform decision making.
The Internet of Things is at the center of this revolution.
IoT hardware has rapidly evolved to offer low-cost sensors for almost every conceivable need. These sensors are being built into IoT devices with battery life that can be measured in years and access to affordable low-power mobile networking.
IoT device management platforms have also evolved rapidly, and have the ability to securely onboard and manage devices on a large scale. IoT cloud services provides suites of application enablement services that can easily be consumed by developers, allowing them to focus on building their application’s business logic. These developments are driving the creation of powerful new IoT applications in almost every vertical, including agriculture.
But what makes today’s farm truly smart? Let me ask that another way. When will smart farm technology reach the point where the domain intelligence it provides exceeds that of experienced professional farmers? The answer may not be as straightforward as you think.
Data is not enough
It‘s true that gathering precise data helps farmers make better decisions. Obtaining soil moisture readings at several depths definitely provides more precise information than if the farmer simply sticks a finger down in the soil. Satellite weather reports provide better forecasting than the farmer’s old barometric weather station. Precise soil chemistry data can help a farmer fertilize the soil, at the lowest cost per acre, and avoid the risk of some soil-borne diseases. A precisely controlled low-flying drone may apply pesticide more efficiently than a traditional crop duster.
But this data simply informs the farmer. It is the farmer’s experience that integrates this intelligence to make the best decisions to optimize operations. An assortment of technology “tools” is not enough.
Smart farming calls for data integration . . .
The applications themselves that the farmer uses must be designed and built with the ability to communicate and work together to optimize outcomes. An experienced farmer intuitively integrates all of the knowledge available. Irrigation decisions will not simply be based on the weather and the type of crop, but by the nature of the soil and its chemical composition. It’s not enough to know how to efficiently apply pesticides over an area. A farmer will also consider the irrigation cycle to maximize the effectiveness of the pesticide.
The problem with many of today’s smart farm IoT technologies is that these applications exist in silos. Even if fully-automated, they do not work efficiently together. The algorithms for scheduling irrigation don’t take into account when fertilizer was last applied.
A truly smart farm is one that can be highly automated so even a novice farmer can optimize their operation. But to do so, valuable data from the many silos throughout the farming operation must easily and automatically integrate.