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Record W4225986377 · doi:10.5455/jjee.204-1624302314

A Solar Energy System with Vehicle-to-Home and Vehicle-to-Grid Option for Newfoundland/Canada Conditions through Mozilla IoT

2022· article· en· W4225986377 on OpenAlexaffabout
Raghul Sundararajan, M. Tariq Iqbal

Bibliographic record

VenueJordan Journal of Electrical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsInternet of ThingsGridSolar energyComputer scienceTelecommunicationsEnvironmental scienceMeteorologyGeographyEmbedded systemEngineeringElectrical engineeringGeodesy

Abstract

fetched live from OpenAlex

The hardware implementation of a solar energy system with vehicle-to-home (V2H) and vehicle-to- grid (V2G) options for Newfoundland conditions through Mozilla IoT is discussed in this paper. To illustrate IoT, remote monitoring and control concepts, a prototype - is entirely a 12 V system - is created in the lab. To operate in multiple modes, the system checks the current and voltage parameters. The data is transmitted to the gateway using an ESP 32 microcontroller and the internet of things (IoT). Mozilla IoT is the platform that hosts the Raspberry Pi Things Gateway and serves as a dashboard to remotely control and monitor the system. The data that is transmitted is logged, and the logged data is shown as a graph. This paper presents the system design, details of demo experimental setup in addition to the test results which reveal that the successful implementation of proposed system - with V2H and V2G options - for Newfoundland/ Canada conditions.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.818

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.003
GPT teacher head0.173
Teacher spread0.170 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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Same venueJordan Journal of Electrical EngineeringSame topicElectric Vehicles and InfrastructureFrench-language works237,207