• Tammana Karthik
• Kondra Avinash

World population is expected to grow by over a third by 2050. This says that market demand for food will continue to grow. Projections show that feeding a world population of 9.1 billion people in 2050 would require raising overall food production by some 70 percent in order to feed the world. There is a gap between current food productivity growth and needed growth. To boost the yield farmers switched to extensive use of chemical fertilizers. Excessive fertilizer usage has its own negative impact like decreased yield, wastage of fertilizer, damage to soil and ground water contamination. Currently farmers mostly rely on guess work, estimation, past experience when deciding the crop that should be grown and the fertilizer that should be used. In this paper we propose a solution that uses technologies like Machine Learning, Image Processing and Internet of things to improvise the farm productivity and at the same time decrease the fertilizer usage. This paper describes the outcomes of a prototype implemented in Rajasthan, India.

Cloud, Arduino Programming, IOT, ESP8266

"Automated Plant Watering System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.e182-e185, October-2021, Available :http://www.jetir.org/papers/JETIR2110439.pdf

"Automated Plant Watering System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppe182-e185, October-2021, Available at : http://www.jetir.org/papers/JETIR2110439.pdf