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Irrigation control system‐data gathering in WSN using IOT.
- Source :
- International Journal of Communication Systems; 11/10/2020, Vol. 33 Issue 16, p1-23, 23p
- Publication Year :
- 2020
-
Abstract
- Summary: Agriculture plays an important role in the growth of agriculture nation like India. The main source of water is essential for agriculture. The irrigation process supplies water, but sometimes the wastage of water may occur. For this reason, the irrigation control scheme in wireless sensor network (WSN) using Internet of things (IoT) is developed to save water and time. This paper presents an ANFIS‐PEGASIS: Irrigation control system‐data gathering in WSN using IoT. The process of the fuzzy inference system (FIS) is utilized for an optimum cluster head (CH) selection that depends on the distance and residual energy. After that, the power‐efficient gathering in sensor information system (PEGASIS) is used for the data collecting process in irrigation structure. PEGASIS is to make a chain between the sensor nodes (SNs), and every node communicates to the CH, and it's transferring the data to the base station (BS). Finally, the decision‐making process can be implemented by adaptive neuro‐FIS (ANFIS) for the automated irrigation process. ANFIS is a useful tool for the decision‐making process. Here, based on the information delivered by the sensors, the decisions are generated using ANFIS for the irrigation system. In the system, the various sensors like humidity, temperature, light intensity, and soil moisture are utilized to sense the different parameters of soil. Based on the value of soil moisture, the land becomes automatically irrigated by ON/OFF, the lamp, and the water pump. The simulation outcomes show that the developed (ANFIS‐PEGASIS) technique outperforms other recent approaches. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10745351
- Volume :
- 33
- Issue :
- 16
- Database :
- Complementary Index
- Journal :
- International Journal of Communication Systems
- Publication Type :
- Academic Journal
- Accession number :
- 146251401
- Full Text :
- https://doi.org/10.1002/dac.4563