• T.V.Thirisa
• V. Priyadharshini
• S.Padmapriya
• A.R.Padmapriya
• Mr. S. Selvakumar

An automatic fertilizer sprayer using machine learning algorithm and Raspberry Pi camera would describe a system that incorporates computer vision and machine learning techniques to optimize the application of fertilizer in agricultural fields. The system would consist of a Raspberry Pi camera that captures images of the plants, which are then processed using a machine learning algorithm. The algorithm would analyze the images and use the data to generate a customized fertilizer spraying plan that takes into account the specific needs of each area of the field. The sprayer would be fully automated, with the algorithm controlling the flow rate and direction of the fertilizer, ensuring that the correct amount is delivered precisely where it is needed. This would reduce the amount of fertilizer needed, decrease labor costs, and increase crop yields, making it an attractive solution for farmers. The integration of the Raspberry Pi camera would enhance the system's ability to identify and respond to changes in soil and crop conditions in real-time, resulting in more efficient and effective fertilizer application.

Machine Learning , Raspberry Pi , Fertilizer Sprayer

"AN AUTOMATIC FERTILIZER SPRAYER USING MACHINE LEARNING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.82-88, June-2023, Available :http://www.jetir.org/papers/JETIRFZ06014.pdf

"AN AUTOMATIC FERTILIZER SPRAYER USING MACHINE LEARNING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. pp82-88, June-2023, Available at : http://www.jetir.org/papers/JETIRFZ06014.pdf