MétaCan
Menu
Back to cohort
Record W2128307880 · doi:10.1109/newcas.2010.5603716

Device-less capacitive indoors localization and activity tracking system

2010· article· en· W2128307880 on OpenAlexaff
M. Marzencki, Lydia Neary‐Zajiczek, Bożena Kamińska, Andrew Sixsmith

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCapacitive sensingCapacitanceTracking (education)Computer scienceCapacitive couplingBattery (electricity)Tracking systemReal-time computingElectronic engineeringElectrical engineeringElectrodeEngineeringArtificial intelligencePower (physics)VoltageKalman filter

Abstract

fetched live from OpenAlex

We propose a novel, device-less, battery-less and simple to install localization system for tracking of people in indoors environment. It is based on the capacitive coupling principle, where presence of a person between electrodes induces variation in capacitance. This method can be used in most standard applications including home monitoring, activity tracking or even fall detection. It does not require the subjects to carry any devices and the entire system can be easily concealed in order not to interfere with daily activities of users. An electrical model and a prototype system are presented and analyzed. The experimental results obtained with the prototype installation show very promising characteristics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.205
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicIndoor and Outdoor Localization TechnologiesFrench-language works237,207