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Record W4391604377 · doi:10.18260/1-2--42385

Board 103: Solar-Powered Car Speed Radar Measurement, Display, and Logging System

2024· article· en· W4391604377 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
TopicFire Detection and Safety Systems
Canadian institutionsConcordia University
FundersNational Science Foundation
KeywordsRadarWind speedComputer scienceMicroprocessorReal-time computingSpeed measurementData loggerPhotovoltaic systemAutomotive engineeringSimulationEngineeringComputer hardwareElectrical engineeringTelecommunicationsMeteorologyOperating systemGeography

Abstract

fetched live from OpenAlex

Abstract Studies have shown that there is a 10% fatality rate when a pedestrian is struck by a vehicle moving at the speed of 20 (mph), and the rate scales up to 90% at the speed of 40 (mph). Moreover, the residential areas with radar speed monitors are shown to be safer in terms of accident probability. Motivated by these statistics, in this senior design project a speed radar system is designed and developed. The components, functionalities, and objectives of the project are listed as follows: (i) A camera will detect and identify a vehicle and distinguish it from other objects; (ii) a radar sensor will measure the speed of the vehicle; (iii) a microprocessor (Raspberry Pi) will acquire the speed data, send it to the display, and analyze and log it in a server; and (iv) a stand-alone solar Photovoltaic system will provide electrical power to and guarantee the continuous operation of the entire system. This senior design project was conducted as a senior design project by a group of undergraduate students in the electrical and computer engineering technology program.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.738
Threshold uncertainty score0.595

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 head0.014
GPT teacher head0.198
Teacher spread0.183 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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