Occupant Activity Recognition in IoT-Enabled Buildings: A Temporal HTN Planning Approach

Ilche Georgievski

2025

Abstract

Given that people spend most of their time indoors, it is imperative that buildings maintain optimal well-being for occupants. To achieve this, research must prioritise occupants over buildings themselves. IoT-enabled buildings can improve quality of life by understanding and responding to occupant’s behaviour. This requires recognising what occupants are doing based on IoT data, particularly by considering the objects they use in specific building areas. Situated within the realm of plan and goal recognition as planning, we propose a novel knowledge-engineering approach to occupant activity recognitions leveraging temporal HTN planning. Our approach consists of two primary processes: generating problem instances from IoT data and engineering HTN domain models for activity recognition. The first ensures the representation of IoT data using planning constructs, while the second integrates knowledge about occupant activities into HTN domain models. To support our approach, we provide two HTN domain models tailored for workspaces and homes. Experimental validation with the latter domain and a real-world dataset show that the quality of our computed solutions surpasses that of baseline data-driven approaches and is comparable to more advanced, hybrid approaches.

Paper Citation

in Harvard Style

Georgievski I. (2025). Occupant Activity Recognition in IoT-Enabled Buildings: A Temporal HTN Planning Approach. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 956-966. DOI: 10.5220/0013241900003890

in Bibtex Style

@conference{icaart25,
author={Ilche Georgievski},
title={Occupant Activity Recognition in IoT-Enabled Buildings: A Temporal HTN Planning Approach},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={956-966},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013241900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Occupant Activity Recognition in IoT-Enabled Buildings: A Temporal HTN Planning Approach
SN - 978-989-758-737-5
AU - Georgievski I.
PY - 2025
SP - 956
EP - 966
DO - 10.5220/0013241900003890
PB - SciTePress