Reliability of Sensor Network-Based Systems for Arbitrary Shape Plot Monitoring Considering Multiple Failures

The paper presents a Python software tool to generate a wireless sensor network (WSN) with the given number of sensors for forestry area monitoring and evaluate the WSN reliability considering multiple sensor failures. The main functions of the software tool are highlighted and parameters that can be set are explained. A sequence diagram is proposed and explained to detail the interactions and data flows between the software tool components during the configuration, execution, and reporting of an experiment. An example of the software tool utilization to generate WSNs for monitoring forest fires within a given forest area in the Kharkiv region (Ukraine), as well as to calculate the probability of WSN failure for various combinations of WSN sensor failures is given.

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Published
2024-10-11
DOI
https://doi.org/10.1109/dessert65323.2024.11122204
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Reliability of Sensor Network-Based Systems for Arbitrary Shape Plot Monitoring Considering Multiple Failures

S. Skorobohatko, Herman Fesenko, Vyacheslav Kharchenko, Sergiy Yakovlev et al.
1 links
Industrial Vision Systems and Defect Detection
article

Reliability of Sensor Network-Based Systems for Arbitrary Shape Plot Monitoring Considering Multiple Failures

S. Skorobohatko, Herman Fesenko, Vyacheslav Kharchenko, Sergiy Yakovlev, Kyrylo Leichenko
article en

Abstract

The paper presents a Python software tool to generate a wireless sensor network (WSN) with the given number of sensors for forestry area monitoring and evaluate the WSN reliability considering multiple sensor failures. The main functions of the software tool are highlighted and parameters that can be set are explained. A sequence diagram is proposed and explained to detail the interactions and data flows between the software tool components during the configuration, execution, and reporting of an experiment. An example of the software tool utilization to generate WSNs for monitoring forest fires within a given forest area in the Kharkiv region (Ukraine), as well as to calculate the probability of WSN failure for various combinations of WSN sensor failures is given.

Simon Kuznets Kharkiv National University of Economics (UA), National Aerospace University – Kharkiv Aviation Institute (UA), V. N. Karazin Kharkiv National University (UA)
Openalex Percentile: Top 55%
Industrial Vision Systems and Defect Detection
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Reliability of Sensor Network-Based Systems for Arbitrary Shape Plot Monitoring Considering Multiple Failures — S. Skorobohatko, Herman Fesenko, et al. · (2024) | TGRS Research Map | TGRS