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Smart Home Architecture based on LoRa Wireless Connectivity and LoRaWAN® Networking Protocol

2020· article· en· W3046561874 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIoT Networks and Protocols
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsComputer scienceHome automationArchitectureDefault gatewayWirelessProtocol (science)Wireless sensor networkCommunications protocolComputer networkSmart environmentResidential gatewayServerEmbedded systemGateway (web page)Internet of ThingsTelecommunicationsWorld Wide Web

Abstract

fetched live from OpenAlex

In the recent years, the smart home systems have achieved a colossal attention for making people lives easier and more comfortable. In fact, they allow them to control the whole environment of their houses in commodious and effective way. One of the technological progress fruits is the production of a huge number of highly developed and smart systems that assist the technology of smart living. In this respect, this paper aims to present a design of a new smart home architecture integrating a wireless communication module to communicate with sensors and smart devices (LoRa). A LoRaWAN gateway was built to manage and establish this communication between the LoRa server (loraserver) and house sensors which are intelligent modules combining both LoRa and Wi-Fi technologies.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.811
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.224
Teacher spread0.210 · 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

Quick stats

Citations15
Published2020
Admission routes1
Has abstractyes

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