Design of a Wireless Sensor Network for Optimal Deployment of Sensor Nodes in a Cocoa Crop

Abstract

In this study, factorial experiments were conducted in two different scenarios to design a Wireless Sensor Network for monitoring a cocoa crop in a rural area in Colombia. Node sensors measured temperature, relative humidity, soil moisture, Ultra-Violet light, and visible light intensity. The factors considered in the experiments were distance between node sensors, height from the ground, and type of antenna; in turn, Received Signal Strength Indicator and data transfer time were the outputs. The wireless sensor network was deployed in the crop, covering approximately 3 % of the area and using 7 different nodes in a cluster tree topology. First, an open field scenario with line of sight was used to determine the appropriate height of the node sensors. Second, a scenario in the actual cocoa crop was utilized to find the appropriate distance between modules and type of antenna. We found, based on our calculations and experimental data, that a height of 1.25 m was required to avoid the Fresnel zone and improve the RSSI of the network. Furthermore, we determined that a distance below 35 m was needed to guarantee signal reception and avoid long data transfer times. The wire antenna exhibited a better performance. Finally, the proposed methodology and monitoring system can be used for agronomic applications in rural areas in Colombia to increase crop yield.

Application of Artificial Intelligence Technology in the Optimal Deployment of Wireless Sensor Network Nodes

“…Largescale WSN consists of thousands of micro-sensors, and these sensor nodes monitor the target. Nodes in the network can perceive the surrounding environment, perform simple calculations on the perceived information, and communicate with their neighboring nodes within the communication radius [2][3]. Wireless sensor nodes form a highly flexible and low-energy network through self-organization.…”

A forest fire monitoring and detection system based on wireless sensor networks

“…The authors in [20], deployed a WSN based on a low energy adaptive clustering hierarchy (LEACH) system, which led to effective communication using a device that worked optimally for temperatures above a fixed threshold. In Cúcuta, a WSN was developed for the optimal deployment of nodes in a cocoa crop considering the type of antenna and the position of the nodes [21], whereas an error-detection system was also implemented to report in almost real-time to a mobile application [22]. A WSN was proposed in China to prevent fires using software based on the triangular fuzzy number (F-AHP), combined with a Monte Carlo algorithm to improve the performance level of the code [23].…”

End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax

“…This driver application is only one notable example where such distance constraints occur, but they pose a challenge to node deployment in wireless sensor networks in general. Larger-scale networks traditionally deal with an inherent trade-off between coverage and node distance, posing challenges for the node energy consumption, link reliability and data transfer time [8]- [10].…”