Fusion Intelligence: Confluence of Natural and Artificial Intelligence for Enhanced Problem-Solving Efficiency
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910449298046976 |
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| author | Kalavakonda, Rohan Reddy Huan, Junjun Dehghanzadeh, Peyman Jaiswal, Archit Mandal, Soumyajit Bhunia, Swarup |
| author_facet | Kalavakonda, Rohan Reddy Huan, Junjun Dehghanzadeh, Peyman Jaiswal, Archit Mandal, Soumyajit Bhunia, Swarup |
| contents | This paper introduces Fusion Intelligence (FI), a bio-inspired intelligent system, where the innate sensing, intelligence and unique actuation abilities of biological organisms such as bees and ants are integrated with the computational power of Artificial Intelligence (AI). This interdisciplinary field seeks to create systems that are not only smart but also adaptive and responsive in ways that mimic the nature. As FI evolves, it holds the promise of revolutionizing the way we approach complex problems, leveraging the best of both biological and digital worlds to create solutions that are more effective, sustainable, and harmonious with the environment. We demonstrate FI's potential to enhance agricultural IoT system performance through a simulated case study on improving insect pollination efficacy (entomophily). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_09763 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fusion Intelligence: Confluence of Natural and Artificial Intelligence for Enhanced Problem-Solving Efficiency Kalavakonda, Rohan Reddy Huan, Junjun Dehghanzadeh, Peyman Jaiswal, Archit Mandal, Soumyajit Bhunia, Swarup Artificial Intelligence Emerging Technologies Multiagent Systems Systems and Control This paper introduces Fusion Intelligence (FI), a bio-inspired intelligent system, where the innate sensing, intelligence and unique actuation abilities of biological organisms such as bees and ants are integrated with the computational power of Artificial Intelligence (AI). This interdisciplinary field seeks to create systems that are not only smart but also adaptive and responsive in ways that mimic the nature. As FI evolves, it holds the promise of revolutionizing the way we approach complex problems, leveraging the best of both biological and digital worlds to create solutions that are more effective, sustainable, and harmonious with the environment. We demonstrate FI's potential to enhance agricultural IoT system performance through a simulated case study on improving insect pollination efficacy (entomophily). |
| title | Fusion Intelligence: Confluence of Natural and Artificial Intelligence for Enhanced Problem-Solving Efficiency |
| topic | Artificial Intelligence Emerging Technologies Multiagent Systems Systems and Control |
| url | https://arxiv.org/abs/2405.09763 |