MERCEDES 2.0: Sistema de reconocimiento de actividades en entornos de multiocupación

  • Javier Medina Quero Universidad de Granada. Granada, España
  • Aurora Polo Rodríguez Universidad de Jaén. Jaén, España
Palabras clave: Personas con fragilidad, Actividades cotidianas, Entornos inteligentes

Resumen

Bibliografía


  1. Nations, U. World population prospects-population division. New York, USA: United Nations, 2019.

  2. Donnelly, Sarah; O'Brien, Marita; Begley, Emer; Brennan, John. 'I'd Prefer to Stay at Home but I Don't Have a Choice': Meeting Older People's Preference for Care: Policy, but What About Practice? Technical Report, University College Dublin. School of Social Policy, Social Work and Social Justice, 2016.

  3. ResearchAndMarkets.com. Global Smart Home Market Research Report (2021 to 2026) - by Product, Technologies, Service, Deployment and Region, December 2021.

  4. Lupión, Marcos; Medina-Quero, Javier; Sanjuan, Juan F.; Ortigosa, Pilar M. DOLARS, A Distributed On-line Activity Recognition System by Means of Heterogeneous Sensors in Real-life Deployments—A Case Study in the Smart Lab of the University of Almería. Sensors, 2021; 21(2): 405. https://doi.org/10.3390/s21020405.

  5. Medina Quero, Javier; Orr, Claire; Zhang, Shuai; Nugent, Chris; Salguero, Alberto; Espinilla, Macarena. Real-Time Recognition of Interleaved Activities Based on Ensemble Classifier of Long Short-Term Memory with Fuzzy Temporal Windows. MDPI Proceedings, 2018; 2(19): 1225. https://www.mdpi.com/2504-3900/2/19/1225.

  6. Hayward, SJ; van Lopik, Kate; Hinde, Christopher; West, AA. A Survey of Indoor Location Technologies, Techniques and Applications in Industry. Internet of Things, 2022; 100608. http://dx.doi.org/10.1016/j.iot.2022.100608.

  7. Zhan, Yuting; Haddadi, Hamed. MOSEN: Activity Modelling in Multiple-Occupancy Smart Homes. arXiv preprint arXiv:2101.00235, 2021.

  8. Oguntala, George; Abd-Alhameed, Raed; Jones, Stephen; Noras, James; Patwary, Mohammad; Rodriguez, Jonathan. Indoor Location Identification Technologies for Real-time IoT-based Applications: An Inclusive Survey. Computer Science Review, 2018; 30: 55–79. http://dx.doi.org/10.1016/j.cosrev.2018.09.001

  9. Gao, Chuhan; Li, Yilong; Zhang, Xinyu. LiveTag: Sensing Human-Object Interaction Through Passive Chipless Wi-Fi Tags. GetMobile: Mobile Computing and Communications, 2019; 22(3): 32–35. https://doi.org/10.1145/3308755.3308766

  10. Meng, Meng; Drira, Hassen; Boonaert, Jacques. Distances Evolution Analysis for Online and Off-line Human Object Interaction Recognition. Image and Vision Computing, 2018; 70: 32–45. https://doi.org/10.1016/j.imavis.2017.12.003


 

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Cómo citar
1.
Medina Quero, Javier; Polo Rodríguez, Aurora. MERCEDES 2.0: Sistema de reconocimiento de actividades en entornos de multiocupación. Paraninfo Digital. 2024; (38): e3809p. Disponible en: https://ciberindex.com/c/pd/e3809p [acceso: 19/07/2024]
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