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 inFuture internet Vol. 14; no. 10; p. 280
Main Authors Pirotti, Francesco, Piragnolo, Marco, D’Agostini, Marika, Cavalli, Raffaele
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 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.
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
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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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