Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture
In order to modernize numerous areas, the Internet of Things (IoT) is an emerging paradigm that connects various intelligent physical objects. As the rising global population depletes resources and causes unforeseeable environmental changes, producing sufficient food has now become a prime concern...
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| Format: | Article |
| Language: | English |
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Austrian Statistical Society
2024-12-01
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| Series: | Austrian Journal of Statistics |
| Online Access: | https://www.ajs.or.at/index.php/ajs/article/view/1874 |
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| _version_ | 1841543698719965184 |
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| author | Shalini Sharma Bhupendra Kumar Pathak Rajiv Kumar |
| author_facet | Shalini Sharma Bhupendra Kumar Pathak Rajiv Kumar |
| author_sort | Shalini Sharma |
| collection | DOAJ |
| description |
In order to modernize numerous areas, the Internet of Things (IoT) is an emerging paradigm that connects various intelligent physical objects. As the rising global population depletes resources and causes unforeseeable environmental changes, producing sufficient food has now become a prime concern globally. Hence, to resolve this issue, agriculture is shifting to "smart agriculture," whose focus is to accelerate production using wireless sensor networks, cloud computing and IoT. The service composition is thought to be a crucial component in this technology for increasing functionalities and satisfying user's complex needs. This paper presents an improved version of the multi-objective genetic algorithm (iMOGA) for optimizing the time and cost associated with the services involved in the production of apple orchards to maximize the farmer's financial goals while reducing their potential time. It has been observed that (iMOGA) is a promising approach to obtaining Pareto optimal solutions for service composition optimization in smart agriculture.
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| format | Article |
| id | doaj-art-74d7036e28de41918d759de207425019 |
| institution | Kabale University |
| issn | 1026-597X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Austrian Statistical Society |
| record_format | Article |
| series | Austrian Journal of Statistics |
| spelling | doaj-art-74d7036e28de41918d759de2074250192025-01-13T07:12:26ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2024-12-0153510.17713/ajs.v53i5.1874Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart AgricultureShalini Sharma0Bhupendra Kumar Pathak1Rajiv KumarJaypee University of Information TechnologyAssistant Professor In order to modernize numerous areas, the Internet of Things (IoT) is an emerging paradigm that connects various intelligent physical objects. As the rising global population depletes resources and causes unforeseeable environmental changes, producing sufficient food has now become a prime concern globally. Hence, to resolve this issue, agriculture is shifting to "smart agriculture," whose focus is to accelerate production using wireless sensor networks, cloud computing and IoT. The service composition is thought to be a crucial component in this technology for increasing functionalities and satisfying user's complex needs. This paper presents an improved version of the multi-objective genetic algorithm (iMOGA) for optimizing the time and cost associated with the services involved in the production of apple orchards to maximize the farmer's financial goals while reducing their potential time. It has been observed that (iMOGA) is a promising approach to obtaining Pareto optimal solutions for service composition optimization in smart agriculture. https://www.ajs.or.at/index.php/ajs/article/view/1874 |
| spellingShingle | Shalini Sharma Bhupendra Kumar Pathak Rajiv Kumar Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture Austrian Journal of Statistics |
| title | Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture |
| title_full | Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture |
| title_fullStr | Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture |
| title_full_unstemmed | Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture |
| title_short | Adopting an Improved Genetic Algorithm for Multi-Objective Service Composition Optimization in Smart Agriculture |
| title_sort | adopting an improved genetic algorithm for multi objective service composition optimization in smart agriculture |
| url | https://www.ajs.or.at/index.php/ajs/article/view/1874 |
| work_keys_str_mv | AT shalinisharma adoptinganimprovedgeneticalgorithmformultiobjectiveservicecompositionoptimizationinsmartagriculture AT bhupendrakumarpathak adoptinganimprovedgeneticalgorithmformultiobjectiveservicecompositionoptimizationinsmartagriculture AT rajivkumar adoptinganimprovedgeneticalgorithmformultiobjectiveservicecompositionoptimizationinsmartagriculture |