Paper Info
Title
An IoT-based intelligent irrigation system with data fusion and a self-powered wide-area network
Abstract
Water resources have a great influence on human society, but saving water in irrigation still remains a challenge. This article proposes an intelligent irrigation system that integrates a data fusion model and a long-rang (LoRa) network for optimizing the watering schedule. A data fusion model is proposed, which first adopts the long short-term memory (LSTM) network to simulate and predict the proper watering demands by integrating multi-source heterogeneous data, that is, historical weather data, user irrigation logs, weather forecasts, and online monitoring sensor data. A self-powered wide-area network is implemented and deployed by using LoRa to facilitate multiple Internet of Things (IoT) application scenarios. It includes a gateway and two types of nodes: a valve node and a sensing node. The node is capable of energy autonomy through the scheme of waterflow-based power generation, thus realizing maintenance-free throughout the life cycle. A cloud platform is designed to provide network management, intelligent irrigation control, and the interface of the mobile application. The proposed system is evaluated through a case study of landscape watering. On average, the proposed system achieves a water-saving efficiency of 94.74% compared with the conventional manual setting solutions.
Year
DOI
Venue
2022
10.1016/j.jii.2022.100367
Journal of Industrial Information Integration
Keywords
DocType
Volume
Low Power Wide Area Network (LPWAN),Long-Range (LoRa),Intelligent irrigation,Long Short-Term Memory (LSTM),Internet of Things (IoT),Energy autonomous
Journal
29
ISSN
Citations 
PageRank 
2452-414X
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
l gong100.34
j yan200.34
y chen300.34
Antonio Plaza43475262.63
l he500.34
Li-rong Zheng662878.34
z zou700.34