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Design a Fabrication of low cost Solar Powered TrashCompactor for Smart cities

2022· article· en· W4289515436 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

VenueInternational Journal of Engineering Technology and Management Sciences · 2022
Typearticle
Languageen
FieldEngineering
TopicIoT-based Smart Home Systems
Canadian institutionsThe Journal of Student Science and Technology
Fundersnot available
KeywordsSolar poweredBattery (electricity)MicrocontrollerPopulationEngineeringSolar energyPhotovoltaic systemGarbageBinAutomotive engineeringComputer sciencePower (physics)Electrical engineeringEmbedded systemWaste managementMechanical engineering

Abstract

fetched live from OpenAlex

Population has been increasing day by day and so pollution also been increasing day by day and in order to maintain the pollution in systematic manner we are developing a smart dustbin for the purpose of serving/managing the waste. In this project we aim to develop a solar powered trash compacting smart dustbin which takes the help of sensors which are incorporated with the microcontroller. The battery is the power source for this circuit, which uses solar energy to get charge and provides power to the circuit as per the requirement. In this report we will study design procedure and implement a small scale model of the garbage bin which will show the demo working of the model.

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)0.001
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 score0.858
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.230
Teacher spread0.216 · 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