Publication Type : Conference Paper
Publisher : IEEE
Source : 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2021, pp. 414-419
Url : https://ieeexplore.ieee.org/abstract/document/9418392
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Verified : No
Year : 2021
Abstract : The IoT advancements have majorly influenced in redefining the agricultural field. A reliable remote monitoring system is the need of the hour. In this paper, two objectives are addressed. Firstly, an app based solution is presented which helps in displaying the current sensor values that efficiently aid in remotely administrating the field. Secondly, an IoT based prototype system for surveillance is proposed that embeds the concept of multi-class classification technique using Machine and Deep Learning for the labels clear farm, horse, cow, wild elephant and wild boar. Support Vector Machines (SVM) and Convolutional Neural Networks (CNN) were analysed for this purpose and the best model was chosen based on accuracy metric.
Cite this Research Publication : G. Abraham, R. R. and M. Nithya, "Smart Agriculture Based on IoT and Machine Learning," 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2021, pp. 414-419, doi: 10.1109/ICCMC51019.2021.9418392.