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المؤلفMahgoub, Ahmed Osama
المؤلفGowid, Samer
المؤلفGhani, Saud
تاريخ الإتاحة2024-03-13T09:01:26Z
تاريخ النشر2020
اسم المنشورSustainable Cities and Society
المصدرScopus
الرقم المعياري الدولي للكتاب22106707
معرّف المصادر الموحدhttp://dx.doi.org/10.1016/j.scs.2020.102182
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53015
الملخصThe health and well-being of occupants of outdoor environments are largely affected by thermal stress, and therefore a global assessment is essential. Wet-bulb globe-temperature (WBGT) is used as a heat stress indicator and standard effective temperature (SET) is used as a thermal comfort index for assessment of thermal comfort in indoor and outdoor environments. These indices are usually evaluated point-wise which could be sufficient for relatively small spaces, but not suitable for large outdoor environments. This research proposes using a system combining climate sensors readings and thermal imaging to globally evaluate WBGT and SET values for outdoor environments. The algorithm derives air temperature from surface temperature values obtained using a thermal imaging camera. The obtained results were validated using readings of available sensors. Point-wise validation showed that the proposed methodology yielded results with a maximum average error of 11.4% compared to the average of point-wise local measurement for the WBGT, and an error of 8.5% for the SET. To minimize the error, an error reduction model based on artificial neural networks has been implemented. The error was further reduced to a maximum average error of 1.76% and 1.25% for WBGT and SET respectively.
راعي المشروعThe work presented in this paper was supported by the A spire Zone Foundation [External grant number Q UEX-CENG-ASPIRE-11/12-7 ].
اللغةen
الناشرElsevier
الموضوعArtificial neural networks
Heat stress
Outdoor environments
SET
Thermal comfort
WBGT
العنوانGlobal evaluation of WBGT and SET indices for outdoor environments using thermal imaging and artificial neural networks
النوعArticle
رقم المجلد60
dc.accessType Abstract Only


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