Review Paper Based on Machine Learning in Smart Irrigation System using Self-Organizing Maps and Hidden Markov Model

Author(s):

Jeeva N , Dr. NGP. INSTITUTE OF TECHNOLOGY; Siva Sanjeev M, Dr. NGP. INSTITUTE OF TECHNOLOGY; Swathi T, Dr. NGP. INSTITUTE OF TECHNOLOGY; Udhaya Girishan S, Dr. NGP. INSTITUTE OF TECHNOLOGY; Sruthi B, Dr. NGP. INSTITUTE OF TECHNOLOGY

Keywords:

Self-organizing maps (SOM), Hidden Markov Model (HMM), Raspberry pi, Convolutional Neural Network (CNN)

Abstract:

A machine learning technology in the ingenious irrigation system can be used and optimized for watering the crops and at the same time it will be updated by the data which was sensed by the cellular sensors and webcam. The webcam is coupled to the Raspberry-pi through a Wi-Fi or bound technology. For this the cellular sensors are also worn to find the exact data for the irrigation. Accordingly this irrigation system is meant for watering the crops render to the optimized data from webcam and wireless sensor networks. The Convolutional Neural Networks is the main program of this machine learning system, using the algorithms based on the CNN .The system will be updated automatically for all weather conditions and there is no dispersal of water for crops. This setup can be quickly sense the weather by analyzing the cloud and sensing the temperature at that time, by using this it can be served as a water saving system.

Other Details:

Manuscript Id	:	IJSTEV4I8033
Published in	:	Volume : 4, Issue : 8
Publication Date	:	01/03/2018
Page(s)	:	81-85

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