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Drip Irrigation Management System using WSN combined with IOT and Cloud Computing Methodologies

A. Inigo Mathew, Raj Kumar


In this paper a concise outline for improving throughput and average end to end delay of information gathered from the agriculture field for precision agriculture, using a distributed clustering mechanism has been outlined. This algorithm offers a throughput of 180 bits/seconds. Besides delivery of water level information packets/signals to base station, it also computes a threshold as well as calculates the values based on transmission range. This overall computational mechanism helps us to build a robust mechanism for delivery of information to the base station, thus reducing the packet loss. A wireless sensor network is a system consisting of sensor nodes, which incorporates a radio frequency (RF) transceiver, sensor, microcontroller and a power source. Recent advances in wireless sensor networking technology have led to the expansion of low cost, low power, multifunctional sensor nodes. Sensor nodes facilitate environment sensing together with data processing, are able to network with other sensor systems and exchange data with external users. Sensor networks are used for a variety of applications including wireless data acquisition, environmental monitoring, irrigation management, safety management and in many other areas. In this paper, a review of incorporating a distributed clustering algorithm for an agricultural application has been elaborated. Also IoT technique has been vividly explained, and its integration with cloud computing and wireless sensor network has been accounted.


Wireless Sensor Network, IOT, Cloud Computing, Sensor Node, Distributed Clustering, Water Level Monitoring, Drip Irrigation, Precision Agriculture.

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