A New Approach toward Successful Farming By the use of AI in Agriculture.

Agriculture, the fundamental ends and means for the foundation of any economy, is gradually growing digital in its different activities like planting, maintaining, and harvesting; for this purpose, farmers require time, money, energy, labor, and resources. What if these agricultural activities become automated?

Here is where AI (Artificial Intelligence ) influences agriculture. In the starting, many doubts and questions were raised by researchers and organizations about whether AI could work with agriculture or not. The farmers were also curious about the Advantages of AI in farming. Still, all these doubts have now been cleared by the technology itself.

As data management was complicated in agriculture, the (Original Equipment Manufacturers(OEM) and farm management information system groups have concentrated more on taking out the trouble of making data-based decisions with the application of machine learning.

The New Holland combine development team has set the first stage stone for machine learning algorithms for agriculture at the Agritechnica Farm Show in 2017 and will turn reality in the coming year, 2019. They are starting a new technology named the Field and Yield Prediction System, a self-monitoring tool that can predict variations in the slope and crop density.

Vehicle data is a future interest in the agriculture industry. Data recording tools with connected devices can perform various tasks like live data transferring, analysis of machine data, and decision-making for preventive maintenance and services. This will allow the OEMs and dealerships to guarantee efficiency in the resource management, and it will enable them to take action on any issues before they occur.

Organizations today evolve various robots for handling different agricultural tasks like the faster harvesting of crops than humans in a greater volume. AI in agriculture will obtain more opportunities for predictive analytics by predicting and tracing the natural disasters or influences on the cultivation, such as climate change. Organizations influence machine learning algorithms to analyze the data gathered by the devices for monitoring soil and crop health.

Adoption of Technological applications in the agriculture industry is as significant as the other industrial applications. Still, sometimes it will be critical when the drive is impacted by certain environmental risks that cannot be controlled easily as AI does in other sectors. After all, the adoption of AI technologies in agriculture is highly increasing.