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Sustainable Watering Solution for Smart Irrigation Using Self-aware Sensors and Semantic Web of Things


K.S. Muralikrishnan and Dr.M. Vijayakumar
Abstract

Agriculture plays major role in economy of many countries. It depends on many factors for food production. Water is the main source for agricultural activities. It needs to be automated in order to use it efficiently. The environmental factor like moisture, temperature, nutrient of soil needs to be analyzed in real-time to predict the necessity of water. It food production depends on the crop, natural climate conditions and adequate supply of irrigation. A decision support system has been proposed with measuring environmental factors using Internet of Things by contacting physical objects and integrating service module. The service module is the combination of communication module and autonomous intelligent prediction module. The communication module works with sensor network and prediction module to communicate each other. The entire system works autonomously by comparing real-time values with historical threshold values and based on event-driven architecture. The numerical validation has been received and analyzed. The result shows that the proposed system uses the water efficiently and increases the food production.

Volume 12 | Issue 1

Pages: 98-103

DOI: 10.5373/JARDCS/V12I1/20201013