Smart farming differs from precision agriculture because it is less concerned with exact measurements. As a result, smart farming is all about collecting and analyzing data to make farming operations more predictable and efficient.
FREMONT, CA: Agriculture is a highly labor-intensive industry. Farm management has become a little less laborious and a lot more rewarding due to the modernization of farm operations fueled by the increasing rate of technology adoption. However, as digital technology has evolved, several new concepts have emerged interchangeably.
Precision farming or
precision agriculture entails highly controlled, precise, and optimized agricultural production. It enables more efficient resource utilization, increased yield, and decreased environmental impact simultaneously. A perfect example of precision agriculture practices is targeted agrochemical application using AI-assisted analysis, which targets only areas that require attention rather than applying chemicals uniformly.
This agricultural practice entails the application of contemporary information and communication technologies (ICT). Additionally, producers incorporate a variety of devices and machinery that aid in the collection of critical field data, including remote sensors, automated hardware and software, telematics, drones, autonomous vehicles, soil sampling using GPS, and robotics.
Precision farming has existed since John Deere introduced GPS guidance for tractors in the early 1900s to increase yield through automated steering and reducing agri-input wastage. It has evolved significantly since then, owing to the rapid advancement of technology in recent years.
Smart farming focuses on using data and information technologies to maximize the efficiency of human labor and improve crop quality and quantity. Today, most farmers, particularly in rural areas, rely on inherited knowledge and educated guesses when seeding, applying fertilizers and crop protection products, and harvesting.
Smart farming optimizes and accelerates these processes through agritech tools and software solutions. It enables producers to make more informed, data-driven decisions and increase economic efficiency through workforce reduction.
Smart farming is distinct from precision agriculture in that it is not concerned with precise measurements. Rather than that, smart farming focuses on capturing and interpreting data
through computing technologies to improve the predictability and efficiency of farm operations.
Smart farming makes use of computing technologies to transmit agricultural data. Several components that ICT-based platforms leverage for smart farming include smartphones and tablets, the internet of things (IoT), artificial intelligence (AI), robotics, unmanned aerial vehicles (UAS), actuators, sensors, and drones.
