Crop Monitoring and Recommendation System using Machine Learning and IOT
R. Pallavi Reddy1, B. Vinitha2, K. Rishita3, K. Pranavi4
1R. Pallavi Reddy, Assistant Professor, G. Narayanamma Institute of Technology and Science for Women, Hyderabad, (Telangana), India.
2B. Vinitha, B. Tech Student, G. Narayanamma Institute of Technology and Science for Women, Hyderabad, (Telangana), India.
3K. Rishita, B. Tech Student, G. Narayanamma Institute of Technology and Science for Women, Hyderabad, (Telangana), India.
4K. Pranavi, B. Tech Student, G. Narayanamma Institute of Technology and Science for Women, Hyderabad, (Telangana), India.
Manuscript received on June 13, 2020. | Revised Manuscript received on June 22, 2020. | Manuscript published on July 10, 2020. | PP: 621-625 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.I7008079920 | DOI: 10.35940/ijitee.I7008.079920
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Farming is an important sector of input for any country’s economic growth. Country like India’s majority population livelihood relies on agriculture. The usage of Internet of Things in agriculture promises unavailable productivity, resource and cost reduction, automation and data driven processes. This paper proposes the implementation of a smart agricultural system that uses advantages of cutting edge technologies such as IoT, Sensor network and data analysis to help farmers enhance the way farming and marketing are done. The work focuses on crop selection for planting, conservation of humidity and nutrient content during plant development, suitable usage of fertilizer and quality check of the crop. The selection of crops is done by checking the soil which includes various factors such as color, soil PH value and moisture content. Sensors such as humidity, moisture etc. are used to gather field information and help farmers make precise decisions about insights and recommendations for irrigation based on the data collected. The soil’s nutrient level is sensed, and if there is a deficiency, a suitable fertilizer is suggested and a notification is generated to the farmer. An acceptable price for the plant based on its yield is calculated and a standard price is fixed. Ultimately, the farming and agriculture industries will benefit from these various technologies and platforms. Not only is the revolutionary farming system of today a smart agricultural solution, it is the main solution to the increasing concern for the food intake and environmental footprint of the global population.
Keywords: IoT, pH value, Crop, Soil, Fertilizer, Sensors.
Scope of the Article: Machine Learning