Probabilistic Framework Allocation on Underwater Vehicular Systems Using Hydrophone Sensor Networks Article Swipe
Pravin R. Kshirsagar
,
Hariprasath Manoharan
,
Shitharth Selvarajan
,
Abdulrhman M. Alshareef
,
Dilbag Singh
,
Heung-No Lee
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/w14081292
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/w14081292
This article emphasis the importance of constructing an underwater vehicle monitoring system to solve various issues that are related to deep sea explorations. For solving the issues, conventional methods are not implemented, whereas a new underwater vehicle is introduced which acts as a sensing device and monitors the ambient noise in the system. However, the fundamentals of creating underwater vehicles have been considered from conventional systems and the new formulations are generated. This innovative sensing device will function based on the energy produced by the solar cells which will operate for a short period of time under the water where low parametric units are installed. In addition, the energy consumed for operating a particular unit is much lesser and this results in achieving high reliability using a probabilistic path finding algorithm. Further, two different application segments have been solved using the proposed formulations including the depth of monitoring the ocean. To validate the efficiency of the proposed method, comparisons have been made with existing methods in terms of navigation output units, rate of decomposition for solar cells, reliability rate, and directivity where the proposed method proves to be more efficient for an average percentile of 64%.
Related Topics
Concepts
Underwater
Reliability (semiconductor)
Computer science
Probabilistic logic
Real-time computing
Directivity
Parametric statistics
Marine engineering
Engineering
Telecommunications
Artificial intelligence
Power (physics)
Statistics
Physics
Antenna (radio)
Geology
Oceanography
Mathematics
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/w14081292
- https://www.mdpi.com/2073-4441/14/8/1292/pdf?version=1650243704
- OA Status
- gold
- Cited By
- 8
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4224240874
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4224240874Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/w14081292Digital Object Identifier
- Title
-
Probabilistic Framework Allocation on Underwater Vehicular Systems Using Hydrophone Sensor NetworksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-04-15Full publication date if available
- Authors
-
Pravin R. Kshirsagar, Hariprasath Manoharan, Shitharth Selvarajan, Abdulrhman M. Alshareef, Dilbag Singh, Heung-No LeeList of authors in order
- Landing page
-
https://doi.org/10.3390/w14081292Publisher landing page
- PDF URL
-
https://www.mdpi.com/2073-4441/14/8/1292/pdf?version=1650243704Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2073-4441/14/8/1292/pdf?version=1650243704Direct OA link when available
- Concepts
-
Underwater, Reliability (semiconductor), Computer science, Probabilistic logic, Real-time computing, Directivity, Parametric statistics, Marine engineering, Engineering, Telecommunications, Artificial intelligence, Power (physics), Statistics, Physics, Antenna (radio), Geology, Oceanography, Mathematics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2, 2023: 4, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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