Browsing Faculty of Engineering, Applied Science and Technology by Author "Al-Hitmi, Mohammed Abdulla E"
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ItemAn Autonomous Multi-Variable Outdoor Air Quality Mapping Wireless Sensors IoT Node for Qatar(Institute of Electrical and Electronics Engineers Inc., 2020-06) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Mnaouer, Adel BenIn all outdoor long haul air quality monitoring and mapping applications, sensing accuracy, the sustainability of telemetry, and resilience in node systems and operation are major challenges. The severity of these challenges varies depending on the moderateness and harshness of the climate of observation. In this work, an autonomous environmentally powered, sensors self-diagnostic/calibration, and context-aware IoT-based telemetry for multi-variable sensing node is being proposed. In this node, photo-voltaic and piezoelectric energy harvesters contributed to self-calibration and sustainable measurement of temperature (in °C), humidity (in %), pressure (in bar), geo-position (in NMEA format), volatile organic compounds-VOC (in ppm), particulate matter PM (in ppm), ozone (in Dobson Unit), Carbon mono-oxide (in ppm), Nitrogen dioxide (in ppm), and Sulphur dioxide (in ppm). Results have shown that the proposed system worked autonomously for days and optimized the real-time air quality mapping for the chosen geo-spatial cluster, i.e. Qatar University. © 2020 IEEE.
ItemDesign and Implementation of Cadastral Geo-spatial IoT Network Gateway Analyzer for Urban Scale Infrastructure Health Monitoring(Institute of Electrical and Electronics Engineers Inc., 2020-01) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Mnaouer, Adel BenUrban and global scale health monitoring systems have gained significance in digital ecosystems. Every stakeholder is striving for efficiency through performance analysis of digital infrastructure health monitoring (IHM) solutions. In this work, a geospatial network analyzer (GNA) is designed and implemented in python using the synergic strengths of Plotly, NetworkX, Scipy, Numpy, MatplotLib, Network2tikz, Pysocks, and PyPing. The GNA uses as a case study a utility computing model (UCM) to make structural health monitoring (SHM) that is based on analysis of geographical area network (GAN). A geo-distributed SHM deployment is assessed from a network performance perspective and verified from geo-spatial packet processing in GNA. The results have shown that this work can lead to standardizing the future of global-scale IoT networks analytics. © 2020 IEEE.
ItemDesign and Implementation of Multi-Protocol Data Networks Interface Detector in Heterogeneous IoTs(Institute of Electrical and Electronics Engineers Inc., 2020-02) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Manouer, Adel BenIn Internet of Everything (IoE) or heterogeneous IoTs, there exist a plethora of protocols and inter-connected Internet of Things. For every network protocol, the complexity of communication and wiring at the physical interface becomes more and more challenging. In this work, an automated interface detector (or gateway) is proposed using a novel port, that scans the physical layer parameters, interpolates with Electronic Industry Association/Telecommunication Industry Association (EIA/TIA) standards specification parameters and compares packet format initiates communication. In this approach, line impedance, voltage, current, SNR, power, and network capacity are used as the coefficients of merit for physical layer detection by interpolation and averaging methods. Standard packet architectures are the key parameters for communication initiation and network fastening at both ends of the data line. The serial protocols such as CANopen, Ethernet, UART, I2C, and SPI are tested and verified. Results have shown that the proposed system can detect any physical layer interface and initiate a data network regardless of connector pinouts and interface wiring complexities. The implementation results exhibit a fertile resource for redundancy handling in-line parameters of data networks. © 2020 IEEE.
ItemA real-time gradient aware multi-variable handheld urban scale air quality mapping IoT system(Institute of Electrical and Electronics Engineers Inc., 2020-06) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Manouer, Adel BenIn outdoor urban scale air quality mapping, electrochemical sensors warm-up time, cross-sensitivity, geo-location typography, and energy efficiency are major challenges. These challenges lead to real-time gradient anomalies that effect the accuracy and prolonged lags in air quality mapping campaigns for state and environmental/meteorological agencies. In this work, a gradient aware, multi-variable air quality sensing node is proposed with event-triggered sensing based on position, gas magnitudes, and cross-sensitivity interpolation. In this approach, temperature, humidity, pressure, geo-position, photovoltaic power, volatile organic compounds, particulate matter, ozone, Carbon mono-oxide, Nitrogen dioxide, and Sulphur dioxide are the principle variables. Results have shown that the proposed system optimized the real-time air quality mapping for the chosen geo-spatial cluster, i.e. Qatar University. © 2020 IEEE.