Smart Farming: The Future Direction of Agriculture
The Internet of Things (IoT) offers ways to improve almost every industry imaginable. In agriculture, the Internet of Things not only offers a solution to time-consuming and tedious tasks, but completely changes the way we think about agriculture. So what exactly is a smart farm? Here’s a brief look at what smart farming is and how it’s changing farming.
What Is a Smart Farm?
Smart farming refers to managing farms using modern Information and communication technologies to increase the quantity and quality of products while optimizing the human labor required.
Among the technologies available for present-day farmers are:
Sensors: soil, water, light, humidity, temperature management
Software: specialized software solutions that target specific farm types or applications agnostic IoT platformsConnectivity: cellular, LoRa
Location: GPS, Satellite
Robotics: Autonomous tractors, processing facilities
Data analytics: standalone analytics solutions, data pipelines for downstream solutions
With these tools, farmers can monitor field conditions and make strategic decisions for entire farms or individual plants, without even setting foot in the field.
The driving force behind smart agriculture is the Internet of Things – connecting machines and sensors integrated on farms to make agricultural processes data-driven and automated.
The IoT-Based Smart Farming Cycle
The core of IoT is the data you can draw from things and transmit over the internet. To optimize the farming process, IoT devices installed on a farm should collect and process data in a repetitive cycle that enables farmers to react quickly to emerging issues and changes in ambient conditions. Smart farming follows a cycle similar to this one:
1、Observation . Sensors record observational data from the crops, livestock, soil, or atmosphere.
2、Diagnostics. The sensor values are fed to a cloud-hosted IoT platform with predefined decision rules and models—also called “business logic”—that ascertain the condition of the examined object and identify any deficiencies or needs.
3、Decisions . After issues are revealed, the user, and/or machine learning-driven components of the IoT platform determine whether location-specific treatment is necessary and, if so, which.
4、Action . After end-user evaluation and action, the cycle repeats from the beginning.
IoT Solutions to Agricultural Problems
Many believe that IoT can add value to all areas of farming, from growing crops to forestry. While there are several ways that IoT can improve farming, two of the major ways IoT can revolutionize agriculture are precision farming and farming automation.