Data processing and predictive analytics
Artificial intelligence and its subset of technologies facilitate processing large amounts of the structured and unstructured volume of data. Temperature, soil, humidity, weather, crop performance, and various other data sources are analyzed to provide better predictive insights. The huge volume of data collected from farm machinery to drone imagery will be evaluated to track and predict the environmental impacts on crop yield, thus improving agricultural accuracy and productivity. In addition to the ground data, AI applications enable fetching data from IOT devices installed on drones and unmanned aircraft systems. AI-enabled IoT (Internet of Things) devices combined with high-precision imagery, can capture images of the entire arable land and analyze it in real-time for monitoring and predicting the soil health and condition of crops. Historical weather patterns, soil reports, humidity levels, underground water levels, pesticide levels, and images from drones and cameras are processed and analyzed to generate real-time alerts and insights.
PRECISION AGRICULTURE A NEW APPROACH TO AGRICULTURE
Artificial Intelligence, IoT, and other technological advances have been embraced by a growing number of farmers in order to increase their land’s productivity. This tech-savvy approach is termed ‘precision agriculture.’ Also known as satellite agriculture, it is “the application of modern information technologies to provide, process and analyze multi-source data of high spatial and temporal resolution for decision making and operations in the management of crop production” (National Research Council, 1997).
In contrast to traditional farming methods where farmlands are treated homogeneously, the precision agriculture method treats the fields variably according to their actual needs. Variable-rate technology (VRT) is used to process the data collected from sensors, tractors, and satellites so that it enables farmers to customize farm inputs such as fertilizers, herbicides, pesticides, irrigation, and more.
Identifying and managing the variability within the fields helps to ensure that the crop receives exactly what it needs. Responding to the needs of farmlands with precision improves crop yields, fertilizer efficiency, and profitability. In addition to increased productivity and efficiency, precision agriculture also ensures sustainability and protection of the environment.
As new sensors and agro-machineries continue to evolve, a shift toward precision farming techniques is becoming vital.
REAL-WORLD APPLICATIONS
Many companies across the world have been leveraging artificial intelligence and its subset of technologies to maximize the efficiency of agro-based businesses. Innovative strategies and solutions are introduced to protect and improve crop yield, reduce manual labour, and enhance value derived from the data sources. Blue River Technology, a US-based company, has developed a robot called ‘See & Spray’ that leverages computer vision to remove weeds from cotton plants. In contrast, Harvest CROO Robotics has launched a robot to help in strawberry farms. When it comes to data prediction and monitoring, PEAT — Berlin-based agricultural tech startup, has developed Plantix, a deep learning application for detecting potential defects and nutrient deficiencies in the soil. Ceres, Prospera, Farmbot, Farmers Edge, and the Climate Corporation are some of the other leading high-tech firms that have been harnessing artificial intelligence and computer vision technologies to help farmers achieve better yields, healthier crops, and higher profits. With the ever-increasing demands for quality and reliability, the agriculture sector finds it imperative to digitize farm production.
