EX-DSS: An Explorative Decision Support System for Designing and Deploying Smart Plug Forecasting Pipelines

Giulia Rinaldi, Lola Botman, Oscar Agudelo, Bart De Moor

2024

Abstract

Artificial Intelligence pipelines are increasingly used to address specific challenges, such as forecasting smart plug loads. Smart plugs, which remotely control various appliances, can significantly reduce energy consumption in commercial buildings by about 20% when effectively scheduled using AI techniques. Designing these AI pipelines involves numerous steps and variables, requiring collaboration and shared knowledge among designers. A Decision Support System (DSS) can facilitate this process. This paper introduces the Explorative Decision Support System (EX-DSS), which extends the classical DSS framework. The EX-DSS integrates an Explorative Management Subsystem to provide project-specific recommendations and a Data Quality (DQ) module to validate user inputs, ensuring clarity and enhancing information sharing. The EX-DSS architecture framework was tested through a software prototype designed to create AI pipelines for forecasting smart plug loads. The study found that using the EX-DSS improves the quality of suggestions, making them more problem-specific and resulting in a more personalized and meaningful user experience, with a significant potential to reduce energy consumption in commercial buildings.

Paper Citation

in Harvard Style

Rinaldi G., Botman L., Agudelo O. and De Moor B. (2024). EX-DSS: An Explorative Decision Support System for Designing and Deploying Smart Plug Forecasting Pipelines. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS; ISBN 978-989-758-716-0, SciTePress, pages 197-205. DOI: 10.5220/0012925800003838

in Bibtex Style

@conference{kmis24,
author={Giulia Rinaldi and Lola Botman and Oscar Agudelo and Bart De Moor},
title={EX-DSS: An Explorative Decision Support System for Designing and Deploying Smart Plug Forecasting Pipelines},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS},
year={2024},
pages={197-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012925800003838},
isbn={978-989-758-716-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS
TI - EX-DSS: An Explorative Decision Support System for Designing and Deploying Smart Plug Forecasting Pipelines
SN - 978-989-758-716-0
AU - Rinaldi G.
AU - Botman L.
AU - Agudelo O.
AU - De Moor B.
PY - 2024
SP - 197
EP - 205
DO - 10.5220/0012925800003838
PB - SciTePress