Fog Cloud Computing and IoT Integration for AI enabled Autonomous Systems in Robotics Article Swipe
Kiran Deep Singh
,
Prabhdeep Singh
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.4108/airo.3617
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.4108/airo.3617
Fog Cloud Computing and the Internet of Things are transforming robotics by empowering AI-enabled autonomous systems. This study analyzes the benefits, drawbacks, and uses of this integration. AI-enabled autonomous robots can use edge computing and cloud resources for real-time data processing and decision-making, improving their performance and adaptability. Communication protocols, data management, security, and scalability are examined in the ecosystem. Case studies reveal how this confluence affects robotics applications. This research shows how FCC, IoT, and AI may improve robotic systems' efficiency, intelligence, and autonomy. The article covers AI-enabled autonomous systems in transportation, manufacturing, healthcare, agriculture, and smart cities. These technologies can improve productivity and safety in many fields, from self-driving automobiles to surgical robots. Integrating these technologies raises safety, ethical decision-making, data privacy, and security concerns. The report emphasizes transparent and ethical AI algorithms, unbiased decision-making, and regulatory frameworks to enable responsible integration and mitigate dangers. In the future, AI-enabled autonomous systems will be shaped by improved AI algorithms, multi-modal sensing, human-robot collaboration, and edge intelligence. It emphasizes the necessity of interdisciplinary collaboration and ethical considerations in responsible technology development. This study concludes with a detailed analysis of fog/cloud computing, IoT, and AI in robotics, revealing the immense promise and problems of AI-enabled autonomous systems. Responsible development and collaboration can help us negotiate this transformational frontier and create a safer, more efficient, and innovative society with AI-driven autonomous systems.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.4108/airo.3617
- https://publications.eai.eu/index.php/airo/article/download/3617/2989
- OA Status
- diamond
- Cited By
- 14
- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4392697344Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.4108/airo.3617Digital Object Identifier
- Title
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Fog Cloud Computing and IoT Integration for AI enabled Autonomous Systems in RoboticsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-03-12Full publication date if available
- Authors
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Kiran Deep Singh, Prabhdeep SinghList of authors in order
- Landing page
-
https://doi.org/10.4108/airo.3617Publisher landing page
- PDF URL
-
https://publications.eai.eu/index.php/airo/article/download/3617/2989Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://publications.eai.eu/index.php/airo/article/download/3617/2989Direct OA link when available
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Cloud computing, Robotics, Internet of Things, Computer science, Artificial intelligence, Systems engineering, Distributed computing, Embedded system, Engineering, Robot, Operating systemTop concepts (fields/topics) attached by OpenAlex
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14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 11, 2024: 3Per-year citation counts (last 5 years)
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.transparent | 130 |
| abstract_inverted_index.agriculture, | 95 |
| abstract_inverted_index.development. | 180 |
| abstract_inverted_index.integration. | 26 |
| abstract_inverted_index.productivity | 103 |
| abstract_inverted_index.self-driving | 110 |
| abstract_inverted_index.technologies | 100, 117 |
| abstract_inverted_index.transforming | 9 |
| abstract_inverted_index.Communication | 48 |
| abstract_inverted_index.adaptability. | 47 |
| abstract_inverted_index.applications. | 68 |
| abstract_inverted_index.collaboration | 173, 209 |
| abstract_inverted_index.intelligence, | 82 |
| abstract_inverted_index.intelligence. | 166 |
| abstract_inverted_index.collaboration, | 163 |
| abstract_inverted_index.considerations | 176 |
| abstract_inverted_index.manufacturing, | 93 |
| abstract_inverted_index.transportation, | 92 |
| abstract_inverted_index.decision-making, | 42, 121, 136 |
| abstract_inverted_index.transformational | 215 |
| abstract_inverted_index.interdisciplinary | 172 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.96965973 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |