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| Formato: | Recurso digital |
| Lenguaje: | inglés |
| Publicado: |
Zenodo
2025
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| Materias: | |
| Acceso en línea: | https://doi.org/10.5281/zenodo.17230778 |
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| _version_ | 1866902215065600000 |
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| author | Srivastava, Prashant Anand |
| author_facet | Srivastava, Prashant Anand |
| contents | <p>The integration of autonomous navigation and spatial computing is transforming smart homes from basic remote‐controlled devices into sophisticated ecosystems capable of perceiving, understanding, and adapting to their environments. In this paper, we propose a novel evaluation framework that quantitatively benchmarks spatial awareness technologies in residential settings. Our methodology integrates advanced sensor fusion, edge computing, and adaptive mapping algorithms to assess system performance, integration efficiency, and user experience. Experimental results demonstrate significant improvements in energy management, security, and personalized automation, while addressing interoperability challenges and ensuring privacy preservation. Our work provides actionable insights for optimizing smart home technologies and outlines a roadmap for future research.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17230778 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Transforming smart homes: The role of autonomous navigation and spatial computing in modern home automation Srivastava, Prashant Anand Smart Home Evaluation Framework Hybrid Fusion Architecture Adaptslam Hybrid edge Processing Multi-Modal Sensor Integration Privacy-Preserving Spatial Computing Matter Protocol Interoperability <p>The integration of autonomous navigation and spatial computing is transforming smart homes from basic remote‐controlled devices into sophisticated ecosystems capable of perceiving, understanding, and adapting to their environments. In this paper, we propose a novel evaluation framework that quantitatively benchmarks spatial awareness technologies in residential settings. Our methodology integrates advanced sensor fusion, edge computing, and adaptive mapping algorithms to assess system performance, integration efficiency, and user experience. Experimental results demonstrate significant improvements in energy management, security, and personalized automation, while addressing interoperability challenges and ensuring privacy preservation. Our work provides actionable insights for optimizing smart home technologies and outlines a roadmap for future research.</p> |
| title | Transforming smart homes: The role of autonomous navigation and spatial computing in modern home automation |
| topic | Smart Home Evaluation Framework Hybrid Fusion Architecture Adaptslam Hybrid edge Processing Multi-Modal Sensor Integration Privacy-Preserving Spatial Computing Matter Protocol Interoperability |
| url | https://doi.org/10.5281/zenodo.17230778 |