Improving Energy Conversion Efficiency in Pest-Detector WSN Environments Using Genetic Programming-Based Data Aggregation

Subject Areas : Optimization

Mohammad Ahmadinia ¹ (Computer Department, Islamic Azad University, Kerman Branch, Kerman, Iran)
Fahimeh Azampour ² (Computer Department, Islamic Azad University, Kerman Branch, Kerman, Iran)

Received: 2021-11-04 Accepted : 2022-01-18 Published : 2022-05-02

Keywords: Wireless Sensor Network, Genetic Programming, Data aggregation, Pest Detection, Energy Conversion Efficiency,

Abstract :

Wireless Sensor Networks (WSNs) have numerous applications in agriculture, including pest detection to ensure high crop yields. However, energy optimization is a major challenge for WSNs, particularly with regard to the energy consumption of sensor nodes. To address this challenge, in this paper, is proposed a novel approach for improving energy conversion efficiency in WSNs for pest detection in agriculture environments, using genetic programming-based data aggregation. The proposed approach is implemented in MATLAB software, and the results are compared with previous works to validate its effectiveness in improving energy conversion efficiency. By optimizing energy conversion, the proposed approach can enhance the accuracy and effectiveness of pest detection while minimizing energy consumption, prolonging the lifespan of sensor nodes, and supporting sustainable and eco-friendly agriculture practices.