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Living-lab Integrated Sensing Architecture (LISA): A modular platform for real-time multimodal data acquisition

Yulith V. Altamirano-Flores et al.

Software Impacts2026https://doi.org/10.1016/j.simpa.2026.100825article
AJG 1
Weight
0.50

What the paper says

Living labs require the coordinated acquisition of heterogeneous data sources to support behavioral research in real-world environments. We present LISA (Living-lab Integrated Sensing Architecture), an open-source and GDPR-compliant software platform for real-time multimodal data acquisition in living-lab research. LISA integrates video streams and IoT sensors through a modular, container-based architecture that supports extensibility and privacy-aware data management. The platform has been deployed in multiple experimental studies, enabling long-term data collection and supporting published research in computer vision and activity monitoring. LISA provides a reusable software infrastructure for reproducible experimentation in intelligent environments. • Open-source platform synchronizes multiple data sources in research environments. • Supports real-world data acquisition in home and occupational therapy settings. • Enables synchronized collection of video and sensor data for daily activity studies. • Has supported international conference publications and scientific presentations. • Multimodal dataset publicly released through Zenodo for reuse by research community.

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https://doi.org/https://doi.org/10.1016/j.simpa.2026.100825

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@article{yulith2026,
  title        = {{Living-lab Integrated Sensing Architecture (LISA): A modular platform for real-time multimodal data acquisition}},
  author       = {Yulith V. Altamirano-Flores et al.},
  journal      = {Software Impacts},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.simpa.2026.100825},
}

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Living-lab Integrated Sensing Architecture (LISA): A modular platform for real-time multimodal data acquisition

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.