IJBTT

Smart Irrigation System based on Spatial Temporal Convolution Long Short Term Memory for Forecasting of Temperature and Humidity

Smart Irrigation System based on Spatial Temporal Convolution Long Short Term Memory for Forecasting of Temperature and Humidity
	© 2022 by IJETT Journal
	Volume-70 Issue-8
	Year of Publication : 2022
	Authors : A. Venkateshwar, Venkanagouda C. Patil
	DOI : 10.14445/22315381/IJETT-V70I8P215

How to Cite?

A. Venkateshwar, Venkanagouda C. Patil, "Smart Irrigation System based on Spatial Temporal Convolution Long Short Term Memory for Forecasting of Temperature and Humidity," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 149-157, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I8P215

Abstract
Smart irrigation system and the Internet of Things (IoT) is used in agriculture to preserve water and improve crop productivity. Various pieces of research were carried out for smart irrigation using IoT and have limitations of outlier and lower performance. This research uses the Spatial Temporal – Convolutional Long Short Term Memory (ST-ConvLSTM) model to improve the efficiency of predicting temperature and humidity. Dataset collected from sensors was applied to evaluate the ST-ConvLSTM model in a smart irrigation system. The convolutional layer preserves the spatial information and applies to temperature and humidity forecasting. The temporal information of relevant information is stored in LSTM for the long term to increase the effectiveness of the prediction. The RMSE of the proposed ST-ConvLSTM model has 0.77 RMSE, and K Nearest Neighbor (KNN) has an RMSE of 1.53.

Keywords
Convolutional Layer, Internet of Things (IoT), Spatial Information, Spatial Temporal – Convolutional Long Short Term Memory, and Temporal Information.

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