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Browsing by Author "Famili, Alireza"

Now showing 1 - 5 of 5
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    Key Assessment Criteria for Organizational BIM Capabilities: A Cross-Regional Study
    Rajabi, Mohammad Sadra; Radzi, Afiqah R.; Rezaeiashtiani, Mohammad; Famili, Alireza; Rashidi, Mohammad Emad; Rahman, Rahimi A. (MDPI, 2022-07-14)
    Building information modeling (BIM) is an emerging process for managing the design, construction, operation, and maintenance of a facility. While BIM has developed in diverse aspects, the lack of organizational BIM capabilities remains a barrier to its implementation across the global architecture, engineering, and construction (AEC) industry. Accordingly, AEC organizations need to understand their organizational BIM capabilities and those of other organizations to realize the benefits of implementing BIM. This study examines the key criteria for assessing organizational BIM capabilities across two countries—Malaysia and Iran. For this purpose, the study compares the assessment criteria for BIM capabilities among the two countries based on the following elements: (1) criticality of the criteria; (2) degree of centrality of the criteria; and (3) underlying groups of the criteria. A systematic literature review of 26 articles and semi-structured interviews with BIM professionals provided nineteen criteria. A total of 121 and 126 BIM professionals evaluated the criticality of the criteria through a survey in Malaysia and Iran. The collected data were analyzed using the contextual disparities test (Mann–Whitney U test, Kruskal–Wallis H test, and rank agreement factor), network analysis, and exploratory factor analysis (EFA). The leading key criteria in both countries are “the company has the necessary infrastructure to implement BIM”, “the company has a good attitude towards new technology”, and “the company understands its expertise”. However, the subsequent key criteria differ between countries. Furthermore, while the level of agreement on the ranking of the criteria is at a neutral level, the Mann–Whitney U test indicates that the level of criticality significantly differs between countries for most criteria. There are also changes in the level of criticality of the criteria between countries. Finally, criteria with a high degree of centrality differ between countries. On the contrary, although the criteria slightly differ between countries, the overarching groups of the criteria are similar (i.e., the criteria are related to organizational BIM capabilities and organizational capabilities). Understanding these criteria can help researchers and industry practitioners develop the optimal tool for assessing organizational BIM capabilities for the local industry.
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    OPTILOD: Optimal Beacon Placement for High-Accuracy Indoor Localization of Drones
    Famili, Alireza; Stavrou, Angelos; Wang, Haining; Park, Jung-Min (Jerry) (MDPI, 2024-03-14)
    For many applications, drones are required to operate entirely or partially autonomously. In order to fly completely or partially on their own, drones need to access location services for navigation commands. While using the Global Positioning System (GPS) is an obvious choice, GPS is not always available, can be spoofed or jammed, and is highly error-prone for indoor and underground environments. The ranging method using beacons is one of the most popular methods for localization, especially for indoor environments. In general, the localization error in this class is due to two factors: the ranging error, and the error induced by the relative geometry between the beacons and the target object to be localized. This paper proposes OPTILOD (Optimal Beacon Placement for High-Accuracy Indoor Localization of Drones), an optimization algorithm for the optimal placement of beacons deployed in three-dimensional indoor environments. OPTILOD leverages advances in evolutionary algorithms to compute the minimum number of beacons and their optimal placement, thereby minimizing the localization error. These problems belong to the Mixed Integer Programming (MIP) class and are both considered NP-hard. Despite this, OPTILOD can provide multiple optimal beacon configurations that minimize the localization error and the number of deployed beacons concurrently and efficiently.
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    Precise Geolocation for Drones, Metaverse Users, and Beyond: Exploring Ranging Techniques Spanning 40 KHz to 400 GHz
    Famili, Alireza (Virginia Tech, 2024-01-09)
    This dissertation explores the realm of high-accuracy localization through the utilization of ranging-based techniques, encompassing a spectrum of signals ranging from low-frequency ultrasound acoustic signals to more intricate high-frequency signals like Wireless Fidelity (Wi-Fi) IEEE 802.11az, 5G New Radio (NR), and 6G. Moreover, another contribution is the conception of a novel timing mechanism and synchronization protocol grounded in tunable quantum photonic oscillators. In general, our primary focus is to facilitate precise indoor localization, where conventional GPS signals are notably absent. To showcase the significance of this innovation, we present two vital use cases at the forefront: drone localization and metaverse user positioning. In the context of indoor drone localization, the spectrum of applications ranges from recreational enthusiasts to critical missions requiring pinpoint accuracy. At the hobbyist level, drones can autonomously navigate intricate indoor courses, enriching the recreational experience. As a finer illustration of a hobbyist application, consider the case of ``follow me drones". These specialized drones are tailored for indoor photography and videography, demanding an exceptionally accurate autonomous flight capability. This precision is essential to ensure the drone can consistently track and capture its designated subject, even as it moves within the confined indoor environment. Moving on from hobby use cases, the technology extends its profound impact to more crucial scenarios, such as search and rescue operations within confined spaces. The ability of drones to localize with high precision enhances their autonomy, allowing them to maneuver seamlessly, even in environments where human intervention proves challenging. Furthermore, the technology holds the potential to revolutionize the metaverse. Within the metaverse, where augmented and virtual realities converge, the importance of high-accuracy localization is amplified. Immersive experiences like Augmented/Virtual/Mixed Reality (AR/VR/MR) gaming rely heavily on precise user positioning to create seamless interactions between digital and physical environments. In entertainment, this innovation sparks innovation in narrative design, enhancing user engagement by aligning virtual elements with real-world surroundings. Beyond entertainment, applications extend to areas like telemedicine, enabling remote medical procedures with virtual guidance that matches physical reality. In light of all these examples, the imperative for an advanced high-accuracy localization system has become increasingly pronounced. The core objective of this dissertation is to address this pressing need by engineering systems endowed with exceptional precision in localization. Among the array of potential techniques suitable for GPS-absent scenarios, we have elected to focus on ranging-based methods. Specifically, our methodologies are built upon the fundamental principles of time of arrival, time difference of arrival, and time of flight measurements. In essence, each of our devised systems harnesses the capabilities of beacons such as ultrasound acoustic sensors, 5G femtocells, or Wi-Fi access points, which function as the pivotal positioning nodes. Through the application of trilateration techniques, based on the calculated distances between these positioning nodes and the integrated sensors on the drone or metaverse user side, we facilitate robust three-dimensional localization. This strategic approach empowers us to realize our ambition of creating localization systems that not only compensate for the absence of GPS signals but also deliver unparalleled accuracy and reliability in complex and dynamic indoor environments. A significant challenge that we confronted during our research pertained to the disparity in z-axis localization performance compared to that of the x-y plane. This nuanced yet pivotal concern often remains overlooked in much of the prevailing state-of-the-art literature, which predominantly emphasizes two-dimensional localization methodologies. Given the demanding context of our work, where drones and metaverse users navigate dynamically across all three dimensions, the imperative for three-dimensional localization became evident. To address this, we embarked on a comprehensive analysis, encompassing mathematical derivations of error bounds for our proposed localization systems. Our investigations unveiled that localization errors trace their origins to two distinct sources: errors induced by ranging-based factors and errors stemming from geometric considerations. The former category is chiefly influenced by factors encompassing the quality of measurement devices, channel quality in which the signal communication between the sensor on the user and the positioning nodes takes place, environmental noise, multipath interference, and more. In contrast, the latter category, involving geometry-induced errors, arises primarily from the spatial configuration of the positioning nodes relative to the user. Throughout our journey, we dedicated efforts to mitigate both sources of error, ensuring the robustness of our system against diverse error origins. Our approach entails a two-fold strategy for each proposed localization system. Firstly, we introduce innovative techniques such as Frequency-Hopping Spread Spectrum (FHSS) and Frequency-Hopping Code Division Multiple Access (FH-CDMA) and incorporate devices such as Reconfigurable Intelligent Surfaces (RIS) and photonic oscillators to fortify the system against errors stemming from ranging-related factors. Secondly, we devised novel evolutionary-based optimization algorithms, adept at addressing the complex NP-Hard challenge of optimal positioning node placement. This strategic placement mitigates the impact of geometry-induced errors on localization accuracy across the entire environmental space. By meticulously addressing both these sources of error, our localization systems stand as a testament to comprehensive robustness and accuracy. Our methodologies not only extend the frontiers of three-dimensional localization but also equip the systems to navigate the intricacies of indoor environments with precision and reliability, effectively fulfilling the evolving demands of drone navigation and metaverse user interaction.
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    Securing Your Airspace: Detection of Drones Trespassing Protected Areas
    Famili, Alireza; Stavrou, Angelos; Wang, Haining; Park, Jung-Min (Jerry); Gerdes, Ryan (MDPI, 2024-03-22)
    Unmanned Aerial Vehicle (UAV) deployment has risen rapidly in recent years. They are now used in a wide range of applications, from critical safety-of-life scenarios like nuclear power plant surveillance to entertainment and hobby applications. While the popularity of drones has grown lately, the associated intentional and unintentional security threats require adequate consideration. Thus, there is an urgent need for real-time accurate detection and classification of drones. This article provides an overview of drone detection approaches, highlighting their benefits and limitations. We analyze detection techniques that employ radars, acoustic and optical sensors, and emitted radio frequency (RF) signals. We compare their performance, accuracy, and cost under different operating conditions. We conclude that multi-sensor detection systems offer more compelling results, but further research is required.
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    Underlying Factors and Strategies for Organizational BIM Capabilities: The Case of Iran
    Rajabi, Mohammad Sadra; Rezaeiashtiani, Mohammad; Radzi, Afiqah R.; Famili, Alireza; Rezaeiashtiani, Amirhossein; Rahman, Rahimi A. (MDPI, 2022-10-31)
    Building information modeling (BIM) has a significant role in the architecture, engineering, construction, and operation (AECO) industries. Most BIM benefits have not been grasped due to the lack of organizational BIM capabilities (OBIMCs). Accordingly, organizations must develop intuitive strategies to support BIM implementation and to fulfill the promised benefits. This study investigates the impact of different capability factors on OBIMC and the underlying strategies to improve OBIMC in Iran. Particularly, this study builds a structural equation model to explain the links between the capability factors and strategies linked to OBIMC in Iran. A systematic literature review of twenty-six papers and semi-structured interviews with fifteen BIM specialists identified nineteen capability factors and fourteen strategies. A survey of 126 BIM professionals was used to assess the importance of the capability factors and strategies. To analyze the collected data, first, an Exploratory Factor Analysis (EFA) was performed. Then, Partial Least-Squares Structural Equation Modeling (PLS-SEM) was employed. The EFA generated two constructs for the capability factors: OBIMC and organizational capabilities (OCA). Furthermore, it categorized the strategies into two constructs: BIM capability requirement (BIMCR) and organizational culture (OCU). The structural equation model demonstrates that BIMCR and OCU enhance OCA and OBIMC. These two elements are also positively impacted by BIMCR. Industry professionals and policymakers can use these findings to develop strategic plans and to prioritize efforts. The significant contribution of this study is to illuminate the interrelationship between capability factors and strategies related to OBIMC in Iran.