Information Technologies for Real-Time Mapping of Human Well-Being Indicators in an Urban Historical Garden
The post-pandemic era has raised awareness on the importance of physical and psychological well-being for decreasing the vulnerability of both individuals and populations. Citizens in urban areas are subject to numerous stress factors which can be mitigated by green spaces such as parks and gardens....
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Published in | Future internet Vol. 14; no. 10; p. 280 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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01.10.2022
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Abstract | The post-pandemic era has raised awareness on the importance of physical and psychological well-being for decreasing the vulnerability of both individuals and populations. Citizens in urban areas are subject to numerous stress factors which can be mitigated by green spaces such as parks and gardens. Sensor and internet technologies support nature-based solutions in various ways. In this paper, we show the results of ongoing research on the use of spatially distributed IoT sensors that collect climate data in an ~8 ha urban garden. The novelty resides in the method for merging the IoT data with a detailed 3D model created by a laser scan survey from a drone flight. The end products are 1 m resolution thermal comfort maps of user-defined scenarios, e.g., at specific times or aggregated in daily/monthly/yearly statistics that represent a thermal comfort distribution. For full replicability, the code is open source and available as an R package on Github. |
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AbstractList | The post-pandemic era has raised awareness on the importance of physical and psychological well-being for decreasing the vulnerability of both individuals and populations. Citizens in urban areas are subject to numerous stress factors which can be mitigated by green spaces such as parks and gardens. Sensor and internet technologies support nature-based solutions in various ways. In this paper, we show the results of ongoing research on the use of spatially distributed IoT sensors that collect climate data in an ~8 ha urban garden. The novelty resides in the method for merging the IoT data with a detailed 3D model created by a laser scan survey from a drone flight. The end products are 1 m resolution thermal comfort maps of user-defined scenarios, e.g., at specific times or aggregated in daily/monthly/yearly statistics that represent a thermal comfort distribution. For full replicability, the code is open source and available as an R package on Github. |
Author | D’Agostini, Marika Pirotti, Francesco Piragnolo, Marco Cavalli, Raffaele |
Author_xml | – sequence: 1 givenname: Francesco orcidid: 0000-0002-4796-6406 surname: Pirotti fullname: Pirotti, Francesco – sequence: 2 givenname: Marco orcidid: 0000-0003-0948-1691 surname: Piragnolo fullname: Piragnolo, Marco – sequence: 3 givenname: Marika surname: D’Agostini fullname: D’Agostini, Marika – sequence: 4 givenname: Raffaele orcidid: 0000-0002-2704-7744 surname: Cavalli fullname: Cavalli, Raffaele |
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Copyright | 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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SubjectTerms | Cities Gardens & gardening geomatics Heat Human body human comfort indices Humidity Internet of Things LoRaWAN mapping Metabolism Microclimate Physiology Psychological factors Radiation Remote sensing Sensors Skin Source code Temperature Thermal comfort Three dimensional models Urban areas Urban farming Vegetation well-being |
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Title | Information Technologies for Real-Time Mapping of Human Well-Being Indicators in an Urban Historical Garden |
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