Sensor Network for Monitoring

Abstract Sensor networks are widely used nowadays. They can be used with various applications, such as monitoring, tracking, communication, and many more. The positioning of the sensors in the network is of great importance. It should enable full coverage, communication between sensors, and transmission of collected data. On the other hand, it is important to do this with as few sensors as possible. When the network is used for monitoring, it is important to consider the presence of impenetrable obstacles. They cover part of the coverage area of some of the sensors. This requires a different positioning of the sensors compared to the case without obstacles. For the solution, we propose an algorithm based on Ant Colony Optimization (ACO) methodology. We have shown how the algorithm works, when there are impenetrable obstacles in the observed space. Using the obstacles, areas of arbitrary shape can be modeled.

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Publication Details

Journal
Cybernetics and Information Technologies
Published
2025-12-01
DOI
https://doi.org/10.2478/cait-2025-0032
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Sensor Network for Monitoring

Stefka Fidanova
Cybernetics and Information Technologies
Energy Efficient Wireless Sensor Networks
article

Sensor Network for Monitoring

Stefka Fidanova
article en

Abstract

Abstract Sensor networks are widely used nowadays. They can be used with various applications, such as monitoring, tracking, communication, and many more. The positioning of the sensors in the network is of great importance. It should enable full coverage, communication between sensors, and transmission of collected data. On the other hand, it is important to do this with as few sensors as possible. When the network is used for monitoring, it is important to consider the presence of impenetrable obstacles. They cover part of the coverage area of some of the sensors. This requires a different positioning of the sensors compared to the case without obstacles. For the solution, we propose an algorithm based on Ant Colony Optimization (ACO) methodology. We have shown how the algorithm works, when there are impenetrable obstacles in the observed space. Using the obstacles, areas of arbitrary shape can be modeled.

Cybernetics and Information TechnologiesVol. 25(4)
Angel Kanchev University of Ruse (BG)
Openalex Percentile: Top 55%
Energy Efficient Wireless Sensor Networks
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