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SafeHaven-FOSS: Offline Emergency Communication App Using Bluetooth Mesh and Wi-Fi Direct

2025· article· W7128710822 on OpenAlexaff
B Chempavathy, Jahnavi Lakarapu, Nithyashree C, Harini Mukunda

Bibliographic record

Venuenot available
Typearticle
Language
FieldComputer Science
TopicBluetooth and Wireless Communication Technologies
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsUnavailabilityBluetoothScalabilityTransmission (telecommunications)The InternetData transmissionWireless ad hoc network

Abstract

fetched live from OpenAlex

During times of natural disasters, network failure, or in remote locations, unavailability of internet and cellular networks significantly restricts communication, slowing rescue and endangering lives. This study addresses the issue of communication breakdown by developing SafeHaven-Foss, an offline emergency communication application that operates independently of traditional network infrastructure. The system employs Bluetooth Mesh for proximate connectivity and Wi-Fi Direct for distant peer-to-peer networking, creating an ad hoc decentralized network of communications. The app features real-time messaging, alert distribution, and location sharing, guaranteeing secure transmission of critical information among nearby users in isolated settings. SafeHaven-Foss, being Free and Open-Source Software (FOSS), ensures transparency, flexibility, and scalability across various devices and settings.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0050.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.292
Teacher spread0.267 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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