Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/17275
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dc.contributor.authorTyagi, Shekharen_US
dc.contributor.authorShah, Akshaten_US
dc.contributor.authorSrivastava, Abhisheken_US
dc.date.accessioned2025-11-27T13:46:17Z-
dc.date.available2025-11-27T13:46:17Z-
dc.date.issued2025-
dc.identifier.citationTyagi, S., Shah, A., & Srivastava, A. (2025). Environment aware greedy deployment strategy for underwater acoustic sensor networks using bathymetric mapping and transmission loss modeling. PeerJ Computer Science, 11. https://doi.org/10.7717/peerj-cs.3321en_US
dc.identifier.issn2376-5992-
dc.identifier.otherEID(2-s2.0-105021402385)-
dc.identifier.urihttps://dx.doi.org/10.7717/peerj-cs.3321-
dc.identifier.urihttps://dspace.iiti.ac.in:8080/jspui/handle/123456789/17275-
dc.description.abstractUnderwater acoustic sensor networks (UASNs) are rapidly evolving and serve a wide array of applications, including marine biology, underwater surveillance, oceanographic data collection, and disaster prevention. Despite notable technological advancements, UASNs continue to face critical challenges, including high propagation delays, limited bandwidth, and significant signal attenuation. To address these issues, this article proposes a novel greedy approach for optimal sensor deployment that aims to maximize coverage, minimize the number of sensors, and effectively account for transmission loss in underwater environments. The methodology begins with the extraction of a region of interest (RoI) using satellite imagery obtained via Google Earth. Following that is the construction of a bathymetry map that captures key topographical features. Recognizing the dynamic and complex nature of underwater environments, multiple simulation scenarios were developed to estimate transmission losses influenced by factors such as salinity, dissolved minerals (e.g., magnesium and other salts), turbidity, pH, and temperature. These simulations help to evaluate how such environmental constraints affect acoustic propagation ranges and coverage estimations. The proposed approach was validated on a real-world RoI and benchmarked against existing methods, demonstrating up to a 10% improvement in coverage while requiring fewer sensors compared to traditional deployment techniques. Additionally, a prototypical real-world implementation was conducted to determine the optimal number of sensors required and the achieved coverage, thereby confirming the practicality and effectiveness of the method. © 2025 Elsevier B.V., All rights reserved.en_US
dc.language.isoenen_US
dc.publisherPeerJ Inc.en_US
dc.sourcePeerJ Computer Scienceen_US
dc.subjectAbsorption lossen_US
dc.subjectBathymetric mapsen_US
dc.subjectSensor deploymenten_US
dc.subjectTransmission lossen_US
dc.subjectUnderwater acoustic sensor networksen_US
dc.titleEnvironment aware greedy deployment strategy for underwater acoustic sensor networks using bathymetric mapping and transmission loss modelingen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Computer Science and Engineering

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