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Record W2954505356 · doi:10.22260/isarc2019/0055

The Design of Building Management Platform Based on Cloud Computing and Low-Cost Devices

2019· article· en· W2954505356 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueProceedings of the ... ISARC · 2019
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Technology in Applications
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectural engineeringComputer scienceCloud computingBuilding management systemFacility managementBuilding automationControl (management)Thermal comfortService (business)Systems engineeringEngineeringOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

The Design of Building Management Platform Based on Cloud Computing and Low-Cost Devices Li-Te Huang, Yi-Yang Chiu and Ying-Chieh Chan Pages 407-414 (2019 Proceedings of the 36th ISARC, Banff, Canada, ISBN 978-952-69524-0-6, ISSN 2413-5844) Abstract: Indoor environment monitor and control are important aspects of reducing building energy consumption and maintaining occupants’ visual and thermal comforts. Previous research showed that the lots of buildings were not able to provide designed service level in the daily operation and the feedback from occupants showed that the predetermined service level sometimes did not match occupants’ desire. However, most of existing buildings and residential buildings did not have building management systems that can systematically monitor the indoor environment, collect occupants’ feedback, and fine-tune built-in control logic when the occupants’ needs could not be met. An easy-to-build and easy-to-use build management system can help researchers, engineers, and occupants themselves to identify the issue. The goal of this study was to develop a building management platform with the functions of indoor environment data collection (temperature, relative humidity, solar radiation, etc.), remote control (air conditioner, window, shading), occupants’ feedback collection (set point, status of building components, etc.), and user interface for retrieving the data and modifying control logic. The platform was developed using Arduino-based and Raspberry Pi-based microcontroller board, low-cost sensors, 3D printing technology, and cloud computing technology. The stored data can serve for personal behavior/comfort analysis, components efficiency analysis, and advanced control logic development. This last part of this paper demonstrated the ability of the developed platform and exhibited the potential application. In the end, we provided further discussion about the potential challenges we might face when developing building management systems in other existing spaces/buildings. Keywords: Building Management Platform; Cloud Computing; Low-Cost Devices DOI: https://doi.org/10.22260/ISARC2019/0055 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.288

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 science0.0020.001
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 head0.251
Teacher spread0.237 · 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