Self-adaptive Sensing IoT Platform for Conserving Historic Buildings and Collections in Museums

Rita Tse, Marcus Im, Su-Kit Tang, Luís Menezes, Alfredo Dias, Giovanni Pau

Abstract

As historic buildings and collections in museums are normally of deteriorated structure or materials, any sudden change of weather or environment, such as oxygen level, temperature, humidity, air quality, etc., may cause damages to them and it may not be recoverable. Internet of Things (IoT) is common in solving problems by collecting environmental data using sensors. The data is live and immediate for visualizing the environment, which is suitable for conserving the buildings and collections. However, there is no one-for-all IoT solution for this conservation problem. In this paper, we propose the design of the sensor device in the IoT platform for conserving historic buildings and collections in museums. The sensor device is self-adaptive, running continuously without any interruption causing by the instability of power and network connection. The platform is currently implemented for the conservation project in the Science museum, University of Coimbra, Portugal. It has been running over a year and the conservation work is going well.

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Paper Citation


in Harvard Style

Tse R., Im M., Tang S., Menezes L., Dias A. and Pau G. (2020). Self-adaptive Sensing IoT Platform for Conserving Historic Buildings and Collections in Museums.In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-426-8, pages 392-398. DOI: 10.5220/0009470203920398


in Bibtex Style

@conference{iotbds20,
author={Rita Tse and Marcus Im and Su-Kit Tang and Luís Menezes and Alfredo Dias and Giovanni Pau},
title={Self-adaptive Sensing IoT Platform for Conserving Historic Buildings and Collections in Museums},
booktitle={Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2020},
pages={392-398},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009470203920398},
isbn={978-989-758-426-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Self-adaptive Sensing IoT Platform for Conserving Historic Buildings and Collections in Museums
SN - 978-989-758-426-8
AU - Tse R.
AU - Im M.
AU - Tang S.
AU - Menezes L.
AU - Dias A.
AU - Pau G.
PY - 2020
SP - 392
EP - 398
DO - 10.5220/0009470203920398