How Artificial Intelligence is Transforming the Way We Farm?

According to UN Food and Agriculture Organization (FAO), the world population will reach 9.1 billion by 2050. And in order to feed the inhabitants, the global food production must increase by 70 percent. However, FAO projects that the area of arable land will be expanded by five percent only. Over exploitation of natural resources, rising pollution levels, degradation of land and depleting water levels and climate change have imposed barriers to traditional farming. In this context, agriculture sector needs technological reforms and solutions to increase crop yield by producing more food using fewer resources and effort. As a result, Artificial Intelligence (AI) is steadily emerging as an imperative to transform the agricultural sector without jeopardising our ecosystem. Let us explore how AI and cognitive solutions can benefit agriculture.

Automation techniques to tackle labor challenges


Agricultural sector has been facing workforce shortage as the world has moved from being an agrarian society to an urban lifestyle. Traditional farms need workers to sow seeds, irrigate land, harvest crops, remove weeds and many more activities. Artificial Intelligence helps to solve such challenges by providing automation solutions. Many companies are developing autonomous bots for handling human intensive processes in farming. Augmenting the human workforce , such agricultural bots can deliver increased productivity, faster pace, reduced costs and higher quality outputs.

Real time monitoring


Advanced remote sensing techniques along with high resolution multispectral imagery helps to monitor crop and soil health. Companies are leveraging artificial intelligence and cognitive computing to process the data captured by sensors in order to keep track of the farm conditions. AI-based technology solutions can help farmers to assess their crop health throughout its lifecycle from time and effort perspective. In addition to crop monitoring, AI solutions can identify potential defects and nutrient deficiencies in soil. Having better insight into soil’s strengths and weaknesses can help in preventing plant diseases and defective crop production.

Data processing and predictive analytics


Artificial intelligence and its subset of technologies facilitate processing large amounts of structured and unstructured volume of data. Temperature, soil, humidity, weather, crop performance and various other data sources are analyzed to provide better predictive insights. 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 the agricultural accuracy and productivity. In addition to the ground data, AI applications enables 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 is 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 as ‘precision agriculture’. Also known as satellite agriculture, it is “the application of modern information technologies to provide, process and analyze multisource 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, precision agriculture method treats the fields variably according to its 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, 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 whereas 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 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, agriculture sector finds it imperative to digitize farm production.

Concluding thoughts


AI-driven technology are extremely promising and ensure a significant shift in agriculture sector. Farms across the world can harness the potential of artificial intelligence and cognitive technology to improve decision-making, cut through data, automate laborious jobs and improve efficiency.



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