Ai Machine Learning For Agricultural Needs & Farming

Ai Machine Learning For Agricultural Needs & Farming

Ai Machine Learning For Agricultural Needs & Farming The world population is expected to reach more than nine billion by the year 2050, The Food and Agriculture Organization (FAO) predicts.

We need a 70-per cent growth in agricultural production to meet the rising demand. 

Arbol CEO Siddhartha Jha on the Future of Weather, Farms & Insurance

– Moreover, farming is a highly time-sensitive endeavour. The information about where and when to plant is essential for optimal production. When farmers get real-time data and information. They can figure out where and how to plant precisely at a granular level. 

– Furthermore, technologies like soil sensors, weather tracking, and GPS-enabled tractors, farmers are now getting unprecedented opportunities to maximise productivity.  
– In addition, data analytics can help farmers tackle unpredictable weather, severe storms, drought and changing insect behaviours.

– Furthermore, farmers now can monitor the growth and health of their crops in real-time. In addition, carry out predictive analytics to measure future yields and make resource management decisions based on historical data.

– They also gain real-time access to pricing data, which enables them to make profitable decisions, the right analytics offers them multifaceted insights at the customer level that they can utilize to gain maximum market share. 

– The supply chain is also being revolutionised by the increasing use of data science. In conclusion, apart from product tracing and timely demand monitoring, the communication among the retailers, distributors, and other stakeholders are getting seamless and effective.

Ai Machine Learning For Agricultural Needs & Farming

The Amazon Rainforest : A Planetary Icon In Danger