Application of WSN in Rural Development, Agriculture Water Management
Rashid Hussain1, J L Sahgal2, Purvi Mishra3, Babita Sharma4
1Rashid Hussain, Associate Professor, E&C, Suresh Gyan Vihar University, Jaipur, India.
2J L Sahgal, Chairman Rajasthan, India, Institute of Engineers, India.
3Purvi Mishra, M.Tech Scholar-DWCE, Suresh Gyan Vihar University, Jaipur, India.
4Babita Sharma, M-Tech Scholar-DWCE, Suresh Gyan Vihar University, Jaipur, India.
Manuscript received on November 01, 2012. | Revised Manuscript received on November 02, 2012. | Manuscript published on November 05, 2012. | PP: 68-72 | Volume-2 Issue-5, November 2012. | Retrieval Number: E1004102512/2012©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: India ranks second in agriculture activities. It supports the employment of several households. Being such a big industry it is important to increase the overall productivity. Today India faces several problems and one of the major problems is the shortage of water for irrigation purposes. Farmers depend heavily on the rains because they lack the access to irrigation facilities. Their crop yields are highly unreliable due to the variability in both rainfall amount and its distribution. Also these farmers depend heavily on the prediction values of various factors such as weather, water, soil, etc. Here we describe the use of sensor networks for improved water management and for controlling other parameters. The target population is the resource poor farmers in the semi-arid areas of rural India. There is a major use of Information and Communication Technology (ITC). Sensor network and other agricultural techniques might help them to store and utilize the rain water, increase their crop productivity, reduce the cost for cultivation and make use of real time values instead of depending just on prediction.
Keywords: WSN, clustering, agriculture, water management.