Reviews on Agro Sense Precision Agriculture Using Wireless Sensor Networks

Main Article Content

Ms. Neha A. Wadaskar, Prof. S. A. Ladhake

Abstract

Precision Farming is that the conjunction of a replacement management perspective with the new and rising data and communicat ions technologies resulting in higher yields and lower prices within the running of enormous scale industrial agricultural fields. It guarantees higher yields and lower input prices by time period and automatic observation of web site specific environmental and soil conditions victimisation completely different sensors and thereby up crop management, reducing waste and labou r prices. Wireless sensing element networking is gaining quality for managing exactitude agriculture through time period observation of agricultural parameters and weather conditions. Cheap simulation tools exist for evaluating giant scale sensing element networks; however, they fail to capture sensible aspects of wireless communication. Reality test - beds bring out actual challenges and vital aspects associated with large - scale readying of sensing element networks. During this paper, we have a tendency to g ift a test bed implementation of a wireless sensing element network for automatic and time period observation of soil and environmental parameters influencing crop yield. The paper describes the system design, physical setu p, sensing element node hardware and software package for time period observation and management of agri - parameters through a straightforward graphical interface. The paper presents sensible problems and technical challenges together with the mixing of sensors, placement of se nsors in out of doors setting, energy management theme and actual power consumption rates.

Article Details

How to Cite
, M. N. A. W. P. S. A. L. (2014). Reviews on Agro Sense Precision Agriculture Using Wireless Sensor Networks. International Journal on Recent and Innovation Trends in Computing and Communication, 2(3), 661–664. https://doi.org/10.17762/ijritcc.v2i3.3031
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