Farming accounts for 70 percent of the water consumed and most of its wasteful use. Farmers are central to the whole picture an they are where most of the world's poverty is concentrated.
Agriculture cannot be ignored in the water equation, it is the most important part of the developing world.
Our model is responsible for obtaining data regarding the location, time and weather conditions (most prominently rain) and automate the working of irrigation system according to the moisture content of the soil at required intervals in a day.
The model facilitates agility while working with varied soil types, crop variants in different weather conditions and seasons.
All of this is done while keeping in mind its feasibility to farmers even in the remote areas.
The project comprises of two models one arduino based and the other is raspberry pi based.
Challenges we way: Difficulty in finding previous data sets related to our problem.
We are able to facilitate the smooth functioning of irrigation system thus benefiting farmers and the agricultural system of the country as a whole.
Improved knowledge of IoT.
Making it smarter with help of Machine Learning and better user interface using AI.
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