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Record W4387787644 · doi:10.29117/cic.2023.0168

A Strategic Design Approach for Implementing Rainwater Management System Using an Integration of GIS and BIM Tool

2023· article· en· W4387787644 on OpenAlexaff
Deshbhushan Patil

Bibliographic record

VenueInternational conference on civil infrastructure and construction/Proceedings of the ... International conference on civil infrastructure and construction · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsConcordia University
Fundersnot available
KeywordsRainwater harvestingSustainabilityUrbanizationGeographic information systemComputer scienceBuilding information modelingVisualizationEnvironmental scienceCivil engineeringSystems engineeringEngineeringRemote sensingGeographyOperations management

Abstract

fetched live from OpenAlex

An increase in urbanization and uncontrolled development has resulted in a water stress situation, which necessitates the exploration of alternate water sources. Rainwater has proven to be a prominent alternate water source after being efficiently harvested. On-ground implementation of the Rainwater Harvesting System (RWHs) at a community level in urban areas has always been challenging and requires technological advancement. To facilitate the implementation of RWHs, the proposed study provides a comprehensive methodology by integrating the Geographical Information System (GIS) and the Building Information Modeling (BIM) tools. Initially, the hydro-spatial analysis was performed with a GIS tool to obtain an optimized rainstorm collection network and to aid in establishing the geometrical properties of RWHs. Further, an outcome from the analysis was utilized to develop a visualization model using the BIM tool. The proposed methodology is implemented as a case study in the municipality of Jaipur (India). The developed multidimensional BIM contributes to the sustainability of the project in terms of resources, economy, and efficiency over the life cycle. As an outcome, the proposed study provides a comprehensive methodology for effectively utilizing rainwater to cope with the growing water demand and contribute to flood mitigation in urban regions.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.051
GPT teacher head0.261
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueInternational conference on civil infrastructure and construction/Proceedings of the ... International conference on civil infrastructure and constructionSame topicUrban Stormwater Management SolutionsFrench-language works237,207