Development of a Test-Bench for Evaluating the Embedded Implementation of the Improved Elephant Herding Optimization Algorithm Applied to Energy-Based Acoustic Localization

The present work addresses the development of a test-bench for the embedded implementation, validity, and testing of the recently proposed Improved Elephant Herding Optimization (iEHO) algorithm, applied to the acoustic localization problem. The implemented methodology aims to corroborate the feasib...

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Published in:Computers (Basel) Vol. 9; no. 4; p. 87
Main Authors: Correia, Sérgio, Fé, João, Tomic, Slavisa, Beko, Marko
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.12.2020
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ISSN:2073-431X, 2073-431X
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Abstract The present work addresses the development of a test-bench for the embedded implementation, validity, and testing of the recently proposed Improved Elephant Herding Optimization (iEHO) algorithm, applied to the acoustic localization problem. The implemented methodology aims to corroborate the feasibility of applying iEHO in real-time applications on low complexity and low power devices, where three different electronic modules are used and tested. Swarm-based metaheuristic methods are usually examined by employing high-level languages on centralized computers, demonstrating their capability in finding global or good local solutions. This work considers iEHO implementation in C-language running on an embedded processor. Several random scenarios are generated, uploaded, and processed by the embedded processor to demonstrate the algorithm’s effectiveness and the test-bench usability, low complexity, and high reliability. On the one hand, the results obtained in our test-bench are concordant with the high-level implementations using MatLab® in terms of accuracy. On the other hand, concerning the processing time and as a breakthrough, the results obtained over the test-bench allow to demonstrate a high suitability of the embedded iEHO implementation for real-time applications due to its low latency.
AbstractList The present work addresses the development of a test-bench for the embedded implementation, validity, and testing of the recently proposed Improved Elephant Herding Optimization (iEHO) algorithm, applied to the acoustic localization problem. The implemented methodology aims to corroborate the feasibility of applying iEHO in real-time applications on low complexity and low power devices, where three different electronic modules are used and tested. Swarm-based metaheuristic methods are usually examined by employing high-level languages on centralized computers, demonstrating their capability in finding global or good local solutions. This work considers iEHO implementation in C-language running on an embedded processor. Several random scenarios are generated, uploaded, and processed by the embedded processor to demonstrate the algorithm’s effectiveness and the test-bench usability, low complexity, and high reliability. On the one hand, the results obtained in our test-bench are concordant with the high-level implementations using MatLab® in terms of accuracy. On the other hand, concerning the processing time and as a breakthrough, the results obtained over the test-bench allow to demonstrate a high suitability of the embedded iEHO implementation for real-time applications due to its low latency.
Author Fé, João
Beko, Marko
Tomic, Slavisa
Correia, Sérgio
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  givenname: Marko
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  surname: Beko
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StartPage 87
SubjectTerms Algorithms
arduino programming
Complexity
Electronic devices
Electronic modules
embedded programming
Embedded systems
energy-based acoustic localization
ESP32 platform
Heuristic methods
High level languages
Internet of Things
Localization
Microprocessors
Optimization
Product development
Real time
Sensors
Software
software/hardware testing
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Title Development of a Test-Bench for Evaluating the Embedded Implementation of the Improved Elephant Herding Optimization Algorithm Applied to Energy-Based Acoustic Localization
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