Privacy Sensitive Building Monitoring Through Generative Sensors

Angan Mitra, Denis Trystram, Christopher Cerin

2024

Abstract

A building equipped with sensors collects heterogeneous data, distributed naturally across zones. The lack of spatiotemporal awareness can lead to excessive sensors or non-optimal distribution across a building. We introduce a novel approach to reduce the friction between high smartness cost and ecological sustainability by proposing virtual sensors as an artifact to estimate the environmental benefit for the planet of doing the ”same with less.” The key idea behind the contribution is to inject data from virtual sensors to determine if an actual sensor can be replaced, followed by a sub-grouping of sensors. As a first contribution, our work exploits the concept of ”less is more” to bring down the capital investment (CAPEX) and recurring expense (OPEX) of the smart-building solutions. This fact opens the door to new research for an eco-responsible deployment of sensors by revisiting the current approach of blind systematic deployment of sensors. We aim to deploy the necessary amount (according to actual, simulated, or virtual uses) and not every room with all possible sensors. As a second contribution, our experiments show a trade-off between virtualization accuracy and active monitoring. Additionally, we validate our insights with 40-60% savings on sensor reduction for a 7-storied Thailand building.

Paper Citation

in Harvard Style

Mitra A., Trystram D. and Cerin C. (2024). Privacy Sensitive Building Monitoring Through Generative Sensors. In Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS; ISBN 978-989-758-699-6, SciTePress, pages 107-118. DOI: 10.5220/0012728100003705

in Bibtex Style

@conference{iotbds24,
author={Angan Mitra and Denis Trystram and Christopher Cerin},
title={Privacy Sensitive Building Monitoring Through Generative Sensors},
booktitle={Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS},
year={2024},
pages={107-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012728100003705},
isbn={978-989-758-699-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS
TI - Privacy Sensitive Building Monitoring Through Generative Sensors
SN - 978-989-758-699-6
AU - Mitra A.
AU - Trystram D.
AU - Cerin C.
PY - 2024
SP - 107
EP - 118
DO - 10.5220/0012728100003705
PB - SciTePress