IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms
This study focuses on optimizing IoT-enabled stepped basin solar stills by integrating the Taguchi method, Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) algorithms. The objective was to enhance distillate yield, thermal efficiency, and system performance by optimizing key parame...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Desalination and Water Treatment |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1944398625000451 |
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| author | McLuret S. Joe Patrick Gnanaraj Vanthana Jeyasingh |
| author_facet | McLuret S. Joe Patrick Gnanaraj Vanthana Jeyasingh |
| author_sort | McLuret |
| collection | DOAJ |
| description | This study focuses on optimizing IoT-enabled stepped basin solar stills by integrating the Taguchi method, Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) algorithms. The objective was to enhance distillate yield, thermal efficiency, and system performance by optimizing key parameters—water depth, basin material, phase change material (PCM) type, and reflector angle. The Taguchi orthogonal array minimized experimental runs, while PSO and ABC algorithms refined parameter selection. Experimental results showed that a combination of 5 mm water depth, black copper basin, salt hydrate PCM, and a 45° internal reflector angle achieved a distillate yield of 3200 ml/day with 78.05 % efficiency, nearing the theoretical maximum of 4100 ml/day. Real-time IoT monitoring enabled dynamic adjustments, further improving efficiency. The findings highlight the effectiveness of combining smart monitoring and advanced optimization techniques to create scalable and sustainable solar desalination solutions for water-scarce regions. |
| format | Article |
| id | doaj-art-00296db68cf0446b8c506ba798c88013 |
| institution | Kabale University |
| issn | 1944-3986 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Desalination and Water Treatment |
| spelling | doaj-art-00296db68cf0446b8c506ba798c880132025-02-12T05:30:57ZengElsevierDesalination and Water Treatment1944-39862025-01-01321101029IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms McLuret0S. Joe Patrick Gnanaraj1Vanthana Jeyasingh2Department of Mechanical Engineering, St. Mother Theresa Engineering College, Tuticorin, Tamilnadu, India; Corresponding author.Department of Mechanical Engineering, St. Mother Theresa Engineering College, Tuticorin, Tamilnadu, IndiaDepartment of Chemistry, St. Mother Theresa Engineering College, Tuticorin, Tamilnadu, IndiaThis study focuses on optimizing IoT-enabled stepped basin solar stills by integrating the Taguchi method, Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) algorithms. The objective was to enhance distillate yield, thermal efficiency, and system performance by optimizing key parameters—water depth, basin material, phase change material (PCM) type, and reflector angle. The Taguchi orthogonal array minimized experimental runs, while PSO and ABC algorithms refined parameter selection. Experimental results showed that a combination of 5 mm water depth, black copper basin, salt hydrate PCM, and a 45° internal reflector angle achieved a distillate yield of 3200 ml/day with 78.05 % efficiency, nearing the theoretical maximum of 4100 ml/day. Real-time IoT monitoring enabled dynamic adjustments, further improving efficiency. The findings highlight the effectiveness of combining smart monitoring and advanced optimization techniques to create scalable and sustainable solar desalination solutions for water-scarce regions.http://www.sciencedirect.com/science/article/pii/S1944398625000451Stepped Basin Solar StillIoT-Based MonitoringTaguchi MethodArtificial Bee Colony (ABC) AlgorithmParticle Swarm Optimization (PSO)Phase Change Material (PCM) |
| spellingShingle | McLuret S. Joe Patrick Gnanaraj Vanthana Jeyasingh IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms Desalination and Water Treatment Stepped Basin Solar Still IoT-Based Monitoring Taguchi Method Artificial Bee Colony (ABC) Algorithm Particle Swarm Optimization (PSO) Phase Change Material (PCM) |
| title | IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms |
| title_full | IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms |
| title_fullStr | IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms |
| title_full_unstemmed | IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms |
| title_short | IoT-enabled stepped basin solar stills: Advanced optimization with PSO and ABC algorithms |
| title_sort | iot enabled stepped basin solar stills advanced optimization with pso and abc algorithms |
| topic | Stepped Basin Solar Still IoT-Based Monitoring Taguchi Method Artificial Bee Colony (ABC) Algorithm Particle Swarm Optimization (PSO) Phase Change Material (PCM) |
| url | http://www.sciencedirect.com/science/article/pii/S1944398625000451 |
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