Agriculture is one of the most important and oldest occupations on Earth. Mankind has come a long way over the millennia in how can we farm and grow a variety of crops with the initiation of artificial intelligence?
Today, the maximum startups in agriculture are accommodating the AI-enabled approach to enhance the adaptability of agricultural production. The Market study report stated that the global Artificial Intelligence in Agriculture market size is predicted to attain 1550 million US dollars by the end of 2025. Carrying out AI-empowered approaches to detect diseases or climate changes sooner will respond more smartly and efficiently.
Agriculture is now becoming digital and AI in the agricultural field is developing in three main categories:
Agricultural Robots - To handle important agricultural tasks like crop harvesting at a higher volume and faster pace than done by human workers, companies are now programming self-governing robots.
Crop and Soil Supervision - Companies are using different ai algorithms to process data that is captured by drones to monitor crop and soil productivity capability.
Predictive Analytics - To predict various environmental impacts on crops such as changes in weather conditions, different machine learning models are being developed.
How AI is transforming agriculture
AI technology helps farmers in optimizing the plans to develop more plentiful yields by determining the best hybrid seed choice, crop choice, and resource usage. AI technologies also help to improve accuracy, harvesting quality and also used as an aid in detecting diseases in pests, plants, and poor plant nourishment on the farms. AI sensors can identify and target weeds and then conclude which herbicides are required to apply on crops?
In addition to ground knowledge, now farmers are also taking to the sky to monitor the farm. Deep learning algorithms and Computer Vision process the data collected from flying drones over the farms and fields. With the help of drones, AI enables cameras to capture images of the whole farming field and evaluate the images to classify problem areas and possible recovery.
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