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A Machine Learning and Augmented Reality based Framework for Multilingual Product Identification in Retail using Mobilenets and Vuforia
Geetanjali Bhola1, Amogh Bansal2, Divij Aggarwal3, Gagan Kishor Upadhyay4

1Ms. Geetanjali Bhola*, Department of Information Technology, Delhi Technological University, New Delhi, India.
2Amogh Bansal, Department of Information Technology, Delhi Technological University, New Delhi, India.
3Divij Aggarwal, Department of Information Technology, Delhi Technological University, New Delhi, India. Email: divij.
4Gagan Kishor Upadhyay, Department of Information Technology, Delhi Technological University, New Delhi, India.

Manuscript received on March 28, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 1885-1888 | Volume-9 Issue-4, April 2020. | Retrieval Number: D8978049420/2020©BEIESP | DOI: 10.35940/ijeat.D8978.049420
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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: INDIA, an agriculture-based country where the economy is dependent on agriculture and climatic conditions. Primary reason of this project is to fulfil the needs of farming quality by reducing excessive fertilizer abuse by controlling some parameters. So, the parameters are temperature, moisture, light, Ph through which we can identify the suitable crop and its nutrition level. Our project uses 3 types of sensors to increase productivity of the crops. Soil testing for productivity is taken by proposal of supplements needs. We are using Arduino UNO with the sensors. Determining the pH of soil is one of the key parameters for improving crop quality so the amount of the amount of fertilizer used is adequate and not excessive for the crops. Other main sensors used are light and hygrometer sensors. We can classify plants based on their light needs like high, medium or low. So, the light received by the crops depends upon the nearness of light. We should adequately address spatial variation for crop productivity when we consider pH to rejuvenate agriculture.
Keywords: FERTILITY OF SOIL, NPK, REAL TIME DETECTION, PH RANGE FOR CROPS.