Knowledge-based Analysis of Residential Air Quality

Aaron Hunter, Rodrigo Mora

Abstract

This paper proposes an approach for residential air quality investigations (IAQ), building on a knowledge-based theory of building science for systems integration. We present a case study related to the diagnosis of an air quality problem in a residential building, and we suggest that a logic-based formalization can help direct investigators towards solutions. This is a problem of significant practical importance, which has not been specifically addressed in the AI research community. It is envisioned that a formal methodology could improve storage and retrieval of archival information, and it could be used as a reasoning engine for diagnosis.

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Paper Citation


in Harvard Style

Hunter A. and Mora R. (2020). Knowledge-based Analysis of Residential Air Quality.In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-395-7, pages 801-805. DOI: 10.5220/0009102908010805


in Bibtex Style

@conference{icaart20,
author={Aaron Hunter and Rodrigo Mora},
title={Knowledge-based Analysis of Residential Air Quality},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2020},
pages={801-805},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009102908010805},
isbn={978-989-758-395-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Knowledge-based Analysis of Residential Air Quality
SN - 978-989-758-395-7
AU - Hunter A.
AU - Mora R.
PY - 2020
SP - 801
EP - 805
DO - 10.5220/0009102908010805