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
Subjects:	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
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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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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