Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization
The study introduces an innovative intelligent agent-controlled elevator system specially designed to improve passenger wait times and enhance the efficiency of high-rise buildings. By utilizing the classic single-agent planning model, we developed a unique strategy for handling calls from halls and...
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| Format: | Article |
| Language: | English |
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Russian Academy of Sciences, St. Petersburg Federal Research Center
2025-01-01
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| Series: | Информатика и автоматизация |
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| Online Access: | https://ia.spcras.ru/index.php/sp/article/view/16482 |
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| author | Atef Gharbi Mohamed Ayari Yamen El Touati |
| author_facet | Atef Gharbi Mohamed Ayari Yamen El Touati |
| author_sort | Atef Gharbi |
| collection | DOAJ |
| description | The study introduces an innovative intelligent agent-controlled elevator system specially designed to improve passenger wait times and enhance the efficiency of high-rise buildings. By utilizing the classic single-agent planning model, we developed a unique strategy for handling calls from halls and cars, and combined with this strategy we significantly improved the overall performance of the elevator system. Our intelligent control methods are in-depth compared with conventional elevator systems, assessing three important performance indicators: response time, system capacity to handle multiple active elevator cars simultaneously, and average passenger waiting time. The results of the full simulation show that an intelligent agent-based model consistently exceeds conventional elevator systems in all measured criteria. Intelligent control systems have significantly reduced response times, and improved simultaneous elevator management and passenger wait times, especially during high traffic. These advances not only improved traffic flow efficiency, but also greatly contributed to passenger satisfaction and brought smoother and more reliable transport experiences within the building. Furthermore, the increased efficiency of our systems is in line with the goals of building energy management, as it minimizes unnecessary movements and idle time. The results demonstrate the system's ability to meet dynamic, high-occupation environment requirements and mark a significant step forward in intelligent infrastructure management. |
| format | Article |
| id | doaj-art-d975074b7f9a47329b766be6e316aaa9 |
| institution | Kabale University |
| issn | 2713-3192 2713-3206 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Russian Academy of Sciences, St. Petersburg Federal Research Center |
| record_format | Article |
| series | Информатика и автоматизация |
| spelling | doaj-art-d975074b7f9a47329b766be6e316aaa92025-01-21T11:27:24ZengRussian Academy of Sciences, St. Petersburg Federal Research CenterИнформатика и автоматизация2713-31922713-32062025-01-01241305010.15622/ia.24.1.216482Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency OptimizationAtef Gharbi0Mohamed Ayari1Yamen El Touati2Northern Border UniversityNorthern Border UniversityNorthern Border UniversityThe study introduces an innovative intelligent agent-controlled elevator system specially designed to improve passenger wait times and enhance the efficiency of high-rise buildings. By utilizing the classic single-agent planning model, we developed a unique strategy for handling calls from halls and cars, and combined with this strategy we significantly improved the overall performance of the elevator system. Our intelligent control methods are in-depth compared with conventional elevator systems, assessing three important performance indicators: response time, system capacity to handle multiple active elevator cars simultaneously, and average passenger waiting time. The results of the full simulation show that an intelligent agent-based model consistently exceeds conventional elevator systems in all measured criteria. Intelligent control systems have significantly reduced response times, and improved simultaneous elevator management and passenger wait times, especially during high traffic. These advances not only improved traffic flow efficiency, but also greatly contributed to passenger satisfaction and brought smoother and more reliable transport experiences within the building. Furthermore, the increased efficiency of our systems is in line with the goals of building energy management, as it minimizes unnecessary movements and idle time. The results demonstrate the system's ability to meet dynamic, high-occupation environment requirements and mark a significant step forward in intelligent infrastructure management.https://ia.spcras.ru/index.php/sp/article/view/16482intelligent agent controlelevator system optimizationpassenger waiting time |
| spellingShingle | Atef Gharbi Mohamed Ayari Yamen El Touati Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization Информатика и автоматизация intelligent agent control elevator system optimization passenger waiting time |
| title | Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization |
| title_full | Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization |
| title_fullStr | Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization |
| title_full_unstemmed | Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization |
| title_short | Intelligent Agent-Controlled Elevator System: Algorithm and Efficiency Optimization |
| title_sort | intelligent agent controlled elevator system algorithm and efficiency optimization |
| topic | intelligent agent control elevator system optimization passenger waiting time |
| url | https://ia.spcras.ru/index.php/sp/article/view/16482 |
| work_keys_str_mv | AT atefgharbi intelligentagentcontrolledelevatorsystemalgorithmandefficiencyoptimization AT mohamedayari intelligentagentcontrolledelevatorsystemalgorithmandefficiencyoptimization AT yameneltouati intelligentagentcontrolledelevatorsystemalgorithmandefficiencyoptimization |