Enhanced whale optimization algorithms with source proximity indicators: Locating gaseous pollutants with time-varying release rates in weak airflow indoors

•Address challenges in localizing time-varying sources in indoor weak airflow.•Substitute concentration gradient with novel source proximity indicators (SPIs).•Assess methods performance via 120 robotic source-tracking experiments.•All three SPI-based methods surpass concentration gradient-based WOA...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Sustainable cities and society Ročník 119; s. 106112
Hlavní autori: Qiu, Jiamin, Mao, Hongyi, Jiang, Yaohua, Zhang, Boyuan, Cai, Hao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.02.2025
Predmet:
Indoor environment with weak airflow
Multi-robot olfaction, Source proximity indicator
Time-varying release rate
Whale optimization algorithm (WOA)
Whale optimization algorithm (WOA)
Multi-robot olfaction, Source proximity indicator
Time-varying release rate
Indoor environment with weak airflow
ISSN:2210-6707
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:•Address challenges in localizing time-varying sources in indoor weak airflow.•Substitute concentration gradient with novel source proximity indicators (SPIs).•Assess methods performance via 120 robotic source-tracking experiments.•All three SPI-based methods surpass concentration gradient-based WOA.•WOA_SC leads among three SPI-based methods with 90 % success in all scenarios. This study enhances the localization of stationary pollutant sources with time-varying release rates in indoor environments with weak airflow, addressing limitations of previous methods that were only effective for constantly released sources and dependent on concentration gradients. We refined the traditional whale optimization algorithm (WOA), based on mean concentration, by incorporating three novel source proximity indicators (SPIs): Bout, introduced by other researchers, and our newly developed modified proximity indicator (MPI) and source confidence (SC). These enhancements resulted in the development of three advanced methods: WOA_Bout, WOA_MPI, and WOA_SC. Using a custom-built multi-robot system, we conducted a two-stage experimental framework involving 120 trials across 8 scenarios to ensure statistical reliability. Our results demonstrate significant improvements in source localization, with WOA_SC achieving an impressive 90 % success rate, surpassing WOA_Bout at 83 %, WOA_MPI at 77 %, and significantly outperforming the traditional WOA at 60 %. Notably, in complex periodic source scenarios, WOA_SC maintained an 87 % success rate compared to WOA’s 40 %, demonstrating enhanced adaptability to variations in source release rates. This research underscores the effectiveness of integrating SPIs to improve localization strategies in indoor environments characterized by weak airflow.
ISSN:2210-6707
DOI:10.1016/j.scs.2024.106112