IOT BASED SMART AGRICULTURE SYSTEM

Authors

  • TURKI ALI SULAIMAN AL BAHRI MIDDLE EAST COLLEGE
  • C.JAYAKUMARI

Keywords:

IoT, Smart agriculture, Arduino, sensors

Abstract

The objective of this project is to develop and design a IoT irrigation system with help of blynk app. Due to the change in the climatic conditions prevailing it is very challenging to monitor and maintain plants. There are several approaches followed to monitor and control the growth of plants. The climatic conditions play a vital role in growing the plants. Plants need regular watering, manure supply and proper irrigation methods for different climatic conditions. The growth of the plant depends also on the type of the soil used. It’s being done manually by farmers in rural areas of Sultanate of Oman and there is no sufficient guidance to properly educate them. So it is very essential to have an automatic system to deal with all these. The solution to achieve all those is an implementation of green house.  This paper proposes an IoT based pant monitoring system to establish a greenhouse to maintain all the above-mentioned suggestions for indoor plants (echo house) to get best environment experience. This would drive the people to be confidence and would help to build an integrated environment of the agroindustry. The main purpose of agriculture monitor system is water consumption, improve plant condition by measuring level of water automatically to take care of plants that will save money and time. 

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References or Bibliography

KRISHNA, K. L., SILVER, O., MALENDE, W. F. & ANURADHA, K. Internet of Things application for implementation of smart agriculture system. 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), 2017. IEEE, 54-59.

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SUSHANTH, G. & SUJATHA, S. IOT based smart agriculture system. 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2018. IEEE, 1-4.

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ZHU, N., LIU, X., LIU, Z., HU, K., WANG, Y., TAN, J., HUANG, M., ZHU, Q., JI, X. & JIANG, Y. 2018.

Deep learning for smart agriculture: Concepts, tools, applications, and opportunities. International Journal of Agricultural and Biological Engineering, 11, 32-

Published

06-01-2022

How to Cite

AL BAHRI , T. A. S. ., & C.JAYAKUMARI. (2022). IOT BASED SMART AGRICULTURE SYSTEM. Journal of Student Research. Retrieved from https://jsr.jofsr.org/index.php/path/article/view/1557