Smart Agriculture Monitoring System using ML
Pramoda R1, Preethi R M2, Spoorthi V3, Samarth Y M4, Shashank S5
1Pramoda R*, Department of CSE, Nagarjuna College Of Engineering And Technology, Bangalore, India.
2Shashank S, Department of CSE, Nagarjuna College Of Engineering And Technology, Bangalore, India.
3Samarth Y M, Department of CSE, Nagarjuna College Of Engineering And Technology, Bangalore, India.
4Spoorthi V, Department of CSE, Nagarjuna College Of Engineering And Technology, Bangalore, India.
5Preethi R M, Department of CSE, Nagarjuna College Of Engineering And Technology, Bangalore, India.
Manuscript received on March 30, 2020. | Revised Manuscript received on April 05, 2020. | Manuscript published on April 30, 2020. | PP: 2404-2407 | Volume-9 Issue-4, April 2020. | Retrieval Number: D7916049420/2020©BEIESP | DOI: 10.35940/ijeat.D7916.049420
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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: Agriculture plays vital role in every individual’s life. As the technology improves, agricultural sector has been improving by the needs of people. Basically, the idea here deals with monitoring of weather, temperature, soil moisture and other agriculture related aspects. The objective of this paper is to upgrade -growth probability. So by making use of Advance technologies good and efficient crop can be yield. Cloud (Firebase) is typically used to store the pre-computed data (data sets) and the data from the efficiency of agriculture sector. This idea comprises of Machine Learning techniques, Cloud Computation  and IoT. Here we will use machine learning techniques for predicting crop sensors and comparison between these. IoT includes NPK sensors, temperature sensor, and humidity sensor. The mechanism goes like this- initially the data from humidity, temperature sensor will be noted and NPK sensors will be placed in the soil, the values from the sensors will be sent to cloud by making use of any communication technology (ZigBee, IoT gateway devices). In cloud comparison of pre-computed data and data from sensors happens by making use of machine learning. The outcome from cloud may be stored in the server (Admin) or directly be notified to authorized person of the land in the form for notification. By taking all these parameters into consideration, we can predict the best suitable crop that can be grown and farmers will earn profit in a cost-effective manner.
Keywords: Firebase, IOT gateways, NPK Sensors, s Zig Bee .