How AI Can Be Used in Agriculture Sector for Higher Productivity?

Artificial Intelligence (AI) with help of Machine Learning (ML) can create an automated model for different fields. Agriculture and farming are one of the them, provides the food to the majority of populace on this earth that also need such technology to boost its productivity and efficiency.

Machine Learning in AI

Machine learning is the branch of AI, and such AI models cannot be developed without using the machine learning process. The ML process involves using the training datasets into an algorithms to learn the certain patterns and predict the results learnt from such data sets.

And when such models are trained enough to work automatically when exposed to new data and take actions without help of humans. Similarly, in agriculture sector, the AI technology can be used at promising scale to enhance the productivity level with better quality at less cost.

AI in Agriculture      

AI can be used in agriculture in many areas like from growing crops, to harvesting and keeping control of insects through aerial view monitoring on crops or spraying the pesticides.  Actually, AI-enabled devices and machines can play many roles in agriculture and farming.

And the role of machine learning is that, the models that can be used for agriculture sector, need to be trained with quality machine learning training data. So that, agro-oriented AI models can recognize the crops health conditions or understand the harvesting or other process to perform accordingly.

AI Use Cases in Agriculture:

·         Use of Autonomous Tractors

·         Robotics for Harvesting & Weed Control 

·         Drones for Pest Controlling & Infestations

·         Drones & Apps for Soil and Crops Health Monitoring

·         AI Applications for Precision Farming with Predictive Analytics

For more detailed applications and use cases of AI in Agriculture, you can read here, and you will get to know how AI and ML can be used in agriculture sector. However, there is too much scope of using the AI enabled devices, machines or applications to make this sector more efficient and productive.

Whatever, the method of using the AI, but unless the right training data sets will be not available, developing an expedient model is not possible for the developers. So, agriculture training data is an important aspect of AI and ML based model development process.

Actually, such data sets help the visual perception based models like Robots or Drones to identify and recognize the object of interest and learn from that, so that it can utilize this source of information while analyzing and predicting the results when used in real-life.