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An Intelligent Air Quality Sensing System for Open-Skin Wound Monitoring

Department of Computer Science, Govt Sadiq College Women University, Bahawalpur 63100, Pakistan
Department of Computer Science & IT, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
Author to whom correspondence should be addressed.
Electronics 2019, 8(7), 801;
Received: 16 May 2019 / Revised: 27 June 2019 / Accepted: 8 July 2019 / Published: 17 July 2019
PDF [6365 KB, uploaded 17 July 2019]


There are many factors that may have a significant effect on the skin wound healing process. The environment is one of them. Although different previous research woks have highlighted the role of environmental elements such as humidity, temperature, dust, etc., in the process of skin wound healing, there is no predefined method available to identify the favourable or adverse environment conditions that seriously affect (positively or negatively) the skin wound healing process. In the current research work, an IoT-based approach is used to design an AQSS (Air Quality Sensing System) using sensors for the acquisition of real-time environment data, and the SVM (Support Vector Machine) classifier is applied to classify environments into one of the two categories, i.e., “favourable”, and “unfavourable”. The proposed system is also supported with an Android application to provide an easy-to-use interface. The proposed system provides an easy and simple means for patients to evaluate the environmental parameters and monitor their effects in the process of open skin wound healing. View Full-Text
Keywords: IoT; health sensors; machine learning; SVM classifier IoT; health sensors; machine learning; SVM classifier

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Sattar, H.; Bajwa, I.S.; Shafi, U.F. An Intelligent Air Quality Sensing System for Open-Skin Wound Monitoring. Electronics 2019, 8, 801.

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