Browsing Faculty of Engineering, Applied Science and Technology by Author "Al-Hitmi, Mohammed Abdulla E."
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ItemDesign and implementation of information centered protocol for long haul SHM monitoring(Institute of Electrical and Electronics Engineers Inc., 2019) Tariq, Hasan ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E. ; Crescini, Damiano ; Mnaouer, Adel BenIn structural health monitoring systems (SHM), robust data transmission is the fundamental constraint. In this work, an information centered protocol is being proposed for multi-sensor and multi-variable communication channels in (SHM). The core objective is communication traffic optimization, data streams compression, bottleneck compensation for seamless information system. A novel SHM hierarchical information model has been designed and implemented using addressing taxonomy and domain definitions accumulated with data segments, beacons and flags-handshaking. On both ends of an SHM channel, a SQLite based encoding and decoding preprocessor is implemented, which requires the use of serial protocols such as CANopen, UART, 12C and SPI. Results have shown that the proposed system optimizes traffic monitoring in handling critical situations of dynamic baud rate switching. © 2019 IEEE.
ItemDesign and implementation of programmable multi-parametric 4-degrees of freedom seismic waves ground motion simulation IoT platform(Institute of Electrical and Electronics Engineers Inc., 2019) Tariq, Hasan ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E. ; Crescini, Damiano ; Mnaouer, Adel BenThe early warning and disaster management agencies spend billions of dollars to counter and cater earthquakes but it has always been unique accident. In this work, a programmable four degrees of freedom electromechanical seismic wave events simulation platform design is being proposed to study and experiment seismic waves and earthquakes realization in form of ground motions. The platform can be programmed and interfaced through an IoT cloud-based Web application. The rig has been tested in the range of frequencies of extreme seismic waves from 0.1Hz to 178Hz and terrestrial inclinations from -5.000° to 5.000°, which is key contribution of this work. This would be an enabler for a variety of applications such as training self-balancing and calibrating seismic resistant designs and structures in addition to studying and testing seismic detection devices. Nevertheless, it serves as an adequate training colossus for machine learning algorithms and event management expert systems. © 2019 IEEE.
ItemGeographical area network-structural health monitoring utility computing model(MDPI AG, 2019) Tariq, Hasan ; Tahir, Anas ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E. ; Crescini, Damiano ; Mnaouer, Adel BenIn view of intensified disasters and fatalities caused by natural phenomena and geographical expansion, there is a pressing need for a more effective environment logging for a better management and urban planning. This paper proposes a novel utility computing model (UCM) for structural health monitoring (SHM) that would enable dynamic planning of monitoring systems in an efficient and cost-effective manner in form of a SHM geo-informatics system. The proposed UCM consists of networked SHM systems that send geometrical SHM variables to SHM-UCM gateways. Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. The inputs of the prediction algorithm are geometrical variables, environmental variables, and payloads. The proposed SHM-UCM is unique in terms of its capability to manage heterogeneous SHM resources. This has been tested in a case study on Qatar University (QU) in Doha Qatar, where it looked at where SHM nodes are distributed along with occupancy density in each building. This information was taken from QU routers and zone calculation models and were then compared to ideal SHM system data. Results show the effectiveness of the proposed model in logging and dynamically planning SHM. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
ItemA real-time early warning seismic event detection algorithm using smart geo-spatial bi-axial inclinometer nodes for Industry 4.0 applications(MDPI AG, 2019) Tariq, Hasan ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E. ; Crescini, Damiano ; Mnaouer, Adel BenEarthquakes are one of the major natural calamities as well as a prime subject of interest for seismologists, state agencies, and ground motion instrumentation scientists. The real-time data analysis of multi-sensor instrumentation is a valuable knowledge repository for real-time early warning and trustworthy seismic events detection. In this work, an early warning in the first 1 micro-second and seismic wave detection in the first 1.7 milliseconds after event initialization is proposed using a seismic wave event detection algorithm (SWEDA). The SWEDA with nine low-computation-cost operations is being proposed for smart geospatial bi-axial inclinometer nodes (SGBINs) also utilized in structural health monitoring systems. SWEDA detects four types of seismic waves, i.e., primary (P) or compression, secondary (S) or shear, Love (L), and Rayleigh (R) waves using time and frequency domain parameters mapped on a 2D mapping interpretation scheme. The SWEDA proved automated heterogeneous surface adaptability, multi-clustered sensing, ubiquitous monitoring with dynamic Savitzky-Golay filtering and detection using nine optimized sequential and structured event characterization techniques. Furthermore, situation-conscious (context-aware) and automated computation of short-time average over long-time average (STA/LTA) triggering parameters by peak-detection and run-time scaling arrays with manual computation support were achieved. © 2019 by the authors.
ItemStructural health monitoring installation scheme using utility computing model(Institute of Electrical and Electronics Engineers Inc., 2018) Tariq, Hasan ; Al-Hitmi, Mohammed Abdulla E. ; Tahir, Anas ; Crescini, Damiano ; Touati, Farid ; Mnaouer, Adel BenIn view of intensified disasters and fatalities caused by natural phenomena, there is a pressing need for an efficient environment logging that provides structural information to administrators for a better management and urban planning. This paper proposes a novel utility model for structural health monitoring that would enable early detection of risk factors and mitigation of loss. The proposed utility computing model takes the input data in terms of 'number of occupants' in a building (i.e. MAC, International Mobile Equipment Identifier addresses and biometric attendance system installed) and SHM system data (i.e. sensors readings). It give visual representation of all the data for utility managers and experts to decide better location of SHM and number of SHM needed per zone depending on high disturbances created due to higher occupancy and number of structures per zone. Denser area with higher structures and higher population will require more precise and accurate SHM systems compared to rural areas. It also analyzes the data from SHM system and using simple machine learning algorithm give experts' suggestions for type of SHM needed at an area. It make it possible for the data of each and every device of SHM systems over several zones to be accessible by specific authorities that can be used to predict as well as forecast any natural disaster. The Structural Health Monitoring utility model is unique in terms of its heterogeneity of resource management in realizing the utility processes. Finally, a case study of Qatar University is looked at where nodes are distributed in zones along with occupant measuring is used over each building. The data was taken over simulated occupation models and mathematical models from literature for occupation and zone calculation using ideal SHM system data. It can be inferred from the data that real-time analysis data will act similar to simulated and proposed Utility Computing System will give visual data and analyze the zones as can be seen in the results. Therefore, SHM Utility Computing model is efficient and most effective system that save cost as well as prepare authorities for maintenance of a structure or crisis management due to external surroundings. © 2018 IEEE.