The DOI matches its Crossref record.
Smart home care network using sensor fusion and distributed vision-based reasoning
Abstract
A wireless sensor network employing multiple sensing and event detection modalities and distributed processing is proposed for smart home monitoring applications. Image sensing and vision-based reasoning are employed to verify and further analyze events reported by other sensors. The system has been developed to address the growing application domain in caregiving to the elderly and persons in need of monitored living, who care to live independently while enjoying the assurance of timely access to caregivers when needed. An example of sensed events is the accidental fall of the person under care. A wireless badge node acts as a bridge between the user and the network. The badge node provides user-centric event sensing functions such as detecting falls, and also provides a voice communication channel between the user and the caregiving center when the system detects an alert and dials the center. The voice connection is carried over an IEEE 802.15.4 radio link between the user badge and another node in the network that acts as a modem. Using signal strength measurements, the network nodes keep track of the approximate location of the user in the monitoring environment.The network also includes wall-mounted image sensor nodes, which are triggered upon detection of a fall to analyze their field-of-view and provide the caregiving center with further information about the user 's status. A description of the developed network and several examples of the vision-based reasoning algorithm are presented in the paper.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Wireless sensor networks for healthcare: A survey
Alemdar, H., & Ersoy, C. (2010) · Computer Networks · doi:10.1016/j.comnet.2010.05.003 · Cited by 1,427
Ambient intelligence: Technologies, applications, and opportunities
Cook, D. J., Augusto, J. C., & Jakkula, V. R. (2009) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2009.04.001 · Cited by 964
A survey on fall detection: Principles and approaches
Mubashir, M., Shao, L., & Seed, L. (2013) · Neurocomputing · doi:10.1016/j.neucom.2011.09.037 · Cited by 869
Portet, F., Vacher, M., Golanski, C., Roux, C., & Meillon, B. (2013) · Personal and Ubiquitous Computing · doi:10.1007/s00779-011-0470-5 · Cited by 421
Sensor technology for smart homes
Ding, D., Cooper, R. A., Pasquina, P. F., & Fici-Pasquina, L. (2011) · Maturitas · doi:10.1016/j.maturitas.2011.03.016 · Cited by 272
Metadata
- Authors
- Tabar, A. M., Keshavarz, A., & Aghajan, H.
- Venue
- Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
- Publisher
- ACM
- Published
- 2006-10-27
- Pages
- 145-154
- OpenAlex
- W2099853900
- Cited by
- 178
- References
- 0
- FWCI
- 12.72
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Smart home care network using sensor fusion and distributed vision-based reasoning. https://app.cochat.ai/papers/10.1145/1178782.1178804
- The paper
- Tabar, A. M., Keshavarz, A., & Aghajan, H. (2006). Smart home care network using sensor fusion and distributed vision-based reasoning. Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks. https://doi.org/10.1145/1178782.1178804
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.