AI IN AGRICULTURE

 

Agriculture is the backbone of the Indian economy, but the industry currently needs more support than any other. India is a country billion people in the population, out of which over 70% of the population lives in rural areas. With 40% of the country’s workforce, agriculture is a major industry and an influencer of the Indian economy. Despite this, its contribution to the $2.3 trillion economies is just a meagre 16% of the entire GDP.

 The components of this sector like Insurance companies, banks, traders, pesticide and seed manufacturing companies and farmers can take better information-based decisions by leveraging the combined potentials of technologies like –

·   Cloud Computing

·  Big data

·  Machine Learning

·  The Internet of Things

·  Web-based Software as a Service platforms 

Components of Smart Farming 

Information Management Systems

This is generally a database where all chunks of data from multiple sensors and resources are gathered, stored, analysed, and retrieved for actions. An optimized information management system should offer information on: 

 Crops:

·       Crop stress

·       Statuses on crop tissue nutrients

·       Crop population

·       Weed patches

·       Fungal or insect infestation

·       Crop yield                                                                                                                    

 Soil:

·       Physical condition

·       Soil texture

·       Structure

·       Moisture

·       Nutrients and more 

 Climate:

·       Humidity

·       Rainfall

·       Wind speed

·       Temperature 

 Devices:

Technology is what puts the smart in smart farming and the following make up the network:

·       Global positioning systems and differential global positioning systems for better accuracy                                                                                                               

·       Geographical information systems (GIS)

·       Remote sensing technologies like data sensors, RADARS, data transmitters, drones, cameras, and other connected devices

·       Cloud architecture

·       The Internet of Things, where devices are capable of communicating with each other and deliver real-time updates and notifications to farmers on crop statuses, water levels, moisture content, crop yield, and more.

Technologies like Machine Learning, Data Analytics, and Big Data for the entire process and setup to make sense.