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Link to original content: https://doi.org/10.5220/0008979401050112
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Authors: Mathieu Bourdeau 1 ; 2 ; David Werner 1 ; Philippe Basset 2 and Elyes Nefzaoui 2

Affiliations: 1 CAMEO SAS 55, Rue de Châteaudun, 75009, Paris, France ; 2 Université Paris-Est, ESYCOM (FRE2028), CNAM, CNRS, ESIEE Paris, Université Paris-Est Marne-la-Vallée, F-77454 Marne-la-Vallée, France

Keyword(s): Sensor Network, Energy Monitoring, Building Energy Efficiency, Energy Retrofit.

Abstract: Enhancing residential buildings energy efficiency has become a critical goal to take up current challenges of human comfort, urbanization growth and the consequent energy consumption increase. In a context of integrated smart infrastructures, sensor networks offer a relevant solution to support building energy consumption monitoring, operation and prediction. The amount of accessible data with such networks also opens new prospects to better consider key parameters such as human behaviour and to lead to more efficient energy retrofit of existing buildings. However, sensor networks planning and implementation in general, and in existing buildings in particular, is a particularly complex task facing many challenges and affecting the performances of such a promising solution. In the present paper, we report on a field experiment of a sensor network deployment involving more than 250 sensors in three collective residential buildings in Paris region for the evaluation of a deep energy ret rofit. More specifically, we describe the whole process of the sensor network design and roll-out and highlight the main critical aspects in such complex process. We also provide a feedback after several months of the sensor network operation and preliminary analysis of collected data. Reported results path the way for an efficient and optimized design and deployment of sensor networks for energy and indoor environment quality monitoring in existing buildings. (More)

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Paper citation in several formats:
Bourdeau, M.; Werner, D.; Basset, P. and Nefzaoui, E. (2020). A Sensor Network for Existing Residential Buildings Indoor Environment Quality and Energy Consumption Assessment and Monitoring: Lessons Learnt from a Field Experiment. In Proceedings of the 9th International Conference on Sensor Networks - SENSORNETS; ISBN 978-989-758-403-9; ISSN 2184-4380, SciTePress, pages 105-112. DOI: 10.5220/0008979401050112

@conference{sensornets20,
author={Mathieu Bourdeau. and David Werner. and Philippe Basset. and Elyes Nefzaoui.},
title={A Sensor Network for Existing Residential Buildings Indoor Environment Quality and Energy Consumption Assessment and Monitoring: Lessons Learnt from a Field Experiment},
booktitle={Proceedings of the 9th International Conference on Sensor Networks - SENSORNETS},
year={2020},
pages={105-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008979401050112},
isbn={978-989-758-403-9},
issn={2184-4380},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Sensor Networks - SENSORNETS
TI - A Sensor Network for Existing Residential Buildings Indoor Environment Quality and Energy Consumption Assessment and Monitoring: Lessons Learnt from a Field Experiment
SN - 978-989-758-403-9
IS - 2184-4380
AU - Bourdeau, M.
AU - Werner, D.
AU - Basset, P.
AU - Nefzaoui, E.
PY - 2020
SP - 105
EP - 112
DO - 10.5220/0008979401050112
PB - SciTePress