Contactless Small-Scale Movement Monitoring System Using Software Defined Radio for Early Diagnosis of COVID-19

The exponential growth of the novel coronavirus disease (N-COVID-19) has affected millions of people already and it is obvious that this crisis is global. This situation has enforced scientific researchers to gather their efforts to contain the virus. In this pandemic situation, health monitoring and human movements are getting significant consideration in the field of healthcare and as a result, it has emerged as a key area of interest in recent times. This requires a contactless sensing platform for detection of COVID-19 symptoms along with containment of virus spread by limiting and monitoring human movements. In this paper, a platform is proposed for the detection of COVID-19 symptoms like irregular breathing and coughing in addition to monitoring human movements using Software Defined Radio (SDR) technology. This platform uses Channel Frequency Response (CFR) to record the minute changes in Orthogonal Frequency Division Multiplexing (OFDM) subcarriers due to any human motion over the wireless channel. In this initial research, the capabilities of the platform are analyzed by detecting hand movement, coughing, and breathing. This platform faithfully captures normal, slow, and fast breathing at a rate of 20, 10, and 28 breaths per minute respectively using different methods such as zero-cross detection, peak detection, and Fourier transformation. The results show that all three methods successfully record breathing rate. The proposed platform is portable, flexible, and has multifunctional capabilities. This platform can be exploited for other human body movements and health abnormalities by further classification using artificial intelligence

Mitigation of particulate matters and integrated approach for carbon monoxide remediation in an urban environment

Air pollution is a serious threat throughout the world and may cause remarkable loss to human health and other living beings. A study was conducted to investigate the main sources of contaminants including CO, fine particle (PM2.5), coarse particle (PM10), and total suspended particulate (TSP) in the ambient air of a typical South Asian industrial city of Faisalabad, Pakistan. Twenty sites under five different city sectors (residential, health centers, commercial, industrial, and vehicular) were surveyed over one month. The average concentrations of TSP, PM10, PM2.5 and CO were 1037.62 ± 383.6 μg/m3, 434.62 ± 65 μg/m3, 35.88 ± 1.7 μg/m3, and 6.4 ± 1.95 μg/m3, respectively. The highest Air Quality Index (AQI) was recorded at the recorded commercial areas followed by the vicinities of health centers and industrial areas. The obtained results were compared against the acceptable limits of Pakistan (national) Environmental Quality Standards (NEQS) and the United States, Environmental Protection Agency (US-EPA). The results demonstrated that concentration of TSP, PM10,PM2.5, and CO in the ambient air of Faisalabad city exceeded the USEPA and NEQs air quality standards. Consequently, air pollution control should not only emphasize on regulatory particulate emissions but also involve the implementation of an integrated multi-pollutant control strategy.This research was funded through the HEC-NRPU project (No. 5635), Pakistan and IERI-GIST research project (2018), Pakistan