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Record W4404666791 · doi:10.53555/sfs.v10i1.3195

Design and Implementation of a PLC-Driven IoT-Connected Color Sorting System for Inventory Management

2023· article· en· W4404666791 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldEngineering
TopicIndustrial Automation and Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSortingComputer scienceInternet of ThingsInventory managementEmbedded systemOperations managementEngineeringProgramming language

Abstract

fetched live from OpenAlex

With the advancement of Industry 4.0, the integration of automation systems and the Internet of Things (IoT) into industrial processes has seen significant progress. This paper presents the technical design and implementation of a color-based object sorting system using a Siemens Programmable Logic Controller (PLC) integrated into an IoT-enabled inventory management platform. The system utilizes photoelectric sensors for color detection, with control logic executed by the Siemens PLC. Key system components include power supplies, actuators, Ethernet switches, connectors, and an LCD display for real-time user interaction and system monitoring. By integrating these elements, this research demonstrates a novel methodology for automating color-based sorting while enabling real-time data acquisition for inventory management. The architecture is optimized for industrial applications, contributing to enhanced automation efficiency and operational agility

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.158
GPT teacher head0.287
Teacher spread0.129 · 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