IoT Based Indoor Monitoring Framework to Reduce the Effects of Passive Smoking
Hidayat Ullah, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture, Peshawar, Pakistan.
Javed Iqbal Bangash, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture, Peshawar, Pakistan.
Junaid Ur Rahman, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture, Peshawar, Pakistan.
Rafiullah Khan, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture, Peshawar, Pakistan.
Abdul Waheed Khan, Department of Information Technology and Computer Science, PAF-Institute of Applied Sciences and Technology, Haripur, Pakistan.
Riaz Ud Din, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture, Peshawar, Pakistan.
Corresponding Author:
Hidayat Ullah (hidayatullahkhelgi@gmail.com)
Abstract:
Passive smoking and other indoor used combusted sources emit toxic compounds in the living premises. These sources produce TVOC’s and CO2 that are dangerous to health and causes some serious diseases like lungs cancer and asthma. A real time solution is necessary to protect human health. Hence, this paper presents an IoT-Based indoor monitoring framework to monitor indoor TVOC’s and CO2 in real time and an automatic mechanism to reduce the effects of these pollutants. Node MCU microcontroller and CCS811 sensor for reading TVOC’s and CO2, are used in the developed framework. The developed framework reads TVOC’s and CO2 for every second and send the collected data to cloud server for storing and analyzing remotely. In case of unhealthy air pollution level, an automatic exhaust fan runs according to predefined threshold level. User gets notification message through mobile phone in case of unhealthy pollution level. The experimental framework was tested in a room for passive smoke and other indoor combusted sources. Advantages of the developed framework are: easy to install, low cost hardware, low power sensor, open source, modular and capable to add more sensors. Best reading position for the system installation founded in the experiments is the main contribution in this research.
Keywords:
Passive smoking, Indoor combusted sources, Internet of Things (IoT), Node-MCU, Total Volatile Organic Compounds (TVOCs), Carbon Dioxide (CO2)