Efficient data sensing and monitoring model for areca nut precision farming with wireless sensor network

Arecanut plays a prominent role in economic life in India; it produces ‘betel nut’ which is primarily used for the masticatory purpose. Nutrient’s cycle and environmental factors impact the forming, these impacts can be minimized through sensing technology i.e., wireless sensor network incorporated with internet of things (IoT). Designing of sensing technologies is considered as primary steps in achieving the arecanut production through precision agriculture; This research focuses on designing and developing an efficient monitoring mechanism named efficient data sensing and monitoring (EDSM), the proposed model will minimize the energy, reduce the false alarm rate, and enhance the detection accuracy. EDSM comprises four-step optimal sensing mechanism; first, formulate the energy consumption, further in this step the sensor device information and all the preliminary details are analyzed. Second step, data are sensed optimally, third step includes monitored and alert is generated the fourth step includes the optimization of packet size. EDSM is evaluated considering the different parameters like energy consumption and alert generation for temperature. Performance comparison is carried out with the existing model considering parameters like fault detection, false alarm detection, event detection, and event false alarm rate. Comparative analysis shows proposed methodology simply outperforms the existing model with significant improvisation.