Search Results (40)

Building information modeling (BIM) and thermal imaging from drone flyovers present innovative opportunities for enhancing building energy efficiency. This study examines the integration of BIM models with thermal data collected using unmanned aerial vehicles (UAVs) to assess and manage energy performance throughout a building’s lifecycle. By leveraging BIM’s structured data and the concept of the digital twin, thermal analysis can be automated to detect thermal bridges and inefficiencies, facilitating data-driven decision-making in sustainable construction. The paper examines methodologies for combining thermal imaging with BIM, including image analysis algorithms and artificial intelligence applications. Case studies demonstrate the practical implementation of UAV-based thermal data collection and BIM integration in an educational facility. The findings highlight the potential for optimizing energy efficiency, improving facility management, and advancing low-emission building practices. The study also addresses key challenges such as data standardization and interoperability, and outlines future research directions in the context of smart city applications and energy-efficient urban development. Full article

Amid intensifying climatic threats, university campuses are increasingly vulnerable. Morphological resilience offers a practical pathway to strengthen disaster response in higher-education institutions. However, research on University Campus Morphological Resilience (UCMR) remains underexplored, with gaps in theory, quantitative methodology, and empirical application. The study established a theoretical framework and an assessment system for UCMR, focusing on four core resilience attributes—robustness, redundancy, connectivity, and diversity—in three common disaster scenarios: earthquakes, flooding, and extreme heat. The Weijinlu (WJL) and Beiyangyuan (BYY) campuses of Tianjin University were selected as case studies. We used Unmanned Aerial Vehicle (UAV) photogrammetry to collect morphological data at a high spatial resolution of 0.1 m. UCMR was evaluated for each disaster scenario, followed by a multi-scenario cluster coupling analysis. The results indicate that, first, the WJL Campus exhibited a lower overall UCMR across various disaster scenarios compared to the BYY Campus, particularly during earthquakes and flooding, with less pronounced differences observed under extreme heat. Second, both campuses demonstrate significant spatial heterogeneity in UCMR across three disaster scenarios. Third, the WJL Campus performs better in redundancy and diversity but worse in connectivity, with lower robustness under earthquakes and flooding, and higher robustness under extreme heat. Fourth, UCMR in BYY Campus displayed consistent spatial patterns characterized by high-resilience clusters, while UCMR in WJL Campus presented greater variability across the three disaster scenarios, showcasing complex multi-scenario cluster types and spatial fragmentation. Based on the above findings, we developed tailored UCMR optimization strategies. The study offers a scientific reference for resilience-oriented campus planning and disaster risk management. Full article

Research on the dynamic mechanisms driving the accumulation of anthropogenic marine debris (AMD) in highly dynamic environments, such as extensive sandy beaches, remains limited. Unmanned aerial vehicles (UAVs) can be used to map macro-marine litter in these environments over large temporal and spatial scales, but several challenges remain in their interpretation. In this study, secondary school students participated in a citizen science initiative, during which they identified, marked, and classified waste items using a series of UAV orthophotos collected along an 800 m extended Italian beach in different seasons. A specific training program and a collection of working tools were developed to support these activities, which were carried out under the constraints imposed by the COVID-19 pandemic. The accuracy of the citizen science approach was evaluated by comparing its results with standard in situ visual census surveys conducted in the same area. This methodology not only enabled an analysis of the temporal dynamics of AMD accumulation but also served an important educational function. The effectiveness of the learning experience was estimated using pre- and post-activity questionnaires. The results indicate a clear improvement in the students’ knowledge, interest, and awareness regarding marine litter, highlighting the potential of citizen science to both support environmental monitoring and promote sustainability education among younger generations. Full article

Despite traditional knowledge’s (TK’s) potential to mitigate climate-induced vulnerabilities across diverse climates, cold-region communities remain critically understudied. To bridge that gap, this study adopts the pressure–state–response (PSR) framework to analyze how Indigenous knowledge in China’s Jinjiang Chalet Village—a 300-year-old cold-region settlement—embodies dynamic resilience across ecological, climatic, social, and economic dimensions. Combining semi-structured interviews with Indigenous Elders, UAV-based multispectral analysis, and environmental simulations, we identify strategies rooted in sustainable wisdom: ecosystem stewardship, climate-responsive architecture, community governance, and adaptive economic practices. A key innovation lies in the Eco-Wisdom Laboratory—a pilot project operationalizing TK through modern passive design and participatory education, demonstrating how traditional woodcraft and microclimate management can be integrated with contemporary technologies to achieve scalable, low-carbon solutions. Crucially, we advance the concept of living inheritance by showcasing how such hybrid practices decolonize static preservation paradigms, enabling communities to codify TK into tangible, future-oriented applications. This study provides a replicable framework for embedding TK into global sustainability agendas, particularly for severe cold regions facing similar stressors. Our findings advocate for policy reforms centering Indigenous agency in climate adaptation planning, offering actionable insights for architects, policymakers, and educators working at the nexus of cultural heritage and ecological resilience. Full article

This study presents a comprehensive digital documentation and preservation effort for the Sellman Tenant House, a historic structure once part of the 18th-century Sellman Plantation in Maryland, USA. This research employs an array of digital technologies, including Terrestrial Laser Scanning (TLS), digital photogrammetry, Unmanned Aerial Vehicles (UAVs), 3D virtual tours, and Heritage Building Information Modeling (HBIM), to document and analyze the construction techniques and historical evolution of the house. Given the absence of written records detailing its original construction, this study utilizes data from these digital documentation methods to explore the building’s structure and determine its construction timeline and methods. Additionally, this research investigates the potential of HBIM as an educational platform to enhance public understanding of heritage buildings by creating interactive and accessible digital models. The findings highlight the effectiveness of combining digital tools to decode vernacular construction and showcase the potential of HBIM in preserving and interpreting historic buildings for diverse audiences, especially for educational purposes. This research contributes to the growing field of digital heritage preservation by showcasing a case study of integrating multiple digital technologies to study, preserve, and promote understanding of a culturally significant yet understudied structure. Full article

The technologies grouped under the term Extended Reality (XR) are constantly evolving. Only fifty years ago, they were delegated to the science fiction strand and were not feasible except in the distant future; today, they are successfully used for personnel training, diagnostic maintenance, education, and more. This article focuses on one such technology: Augmented Reality (AR). In particular, it aims to present an improvement of a software created to monitor the values of Fiber Bragg Grating (FBG) sensors for aeronautical applications. The ability to overlay the status of various network-connected smart elements allows the operator to evaluate actual conditions in a highly intuitive and seamless manner, thus accelerating various activities. It was evaluated in a controlled environment to perform strain and temperature measurements of an Unmanned Aerial Vehicle (UAV), where it demonstrated its usefulness. Full article

This paper provides a comprehensive guide for educators on how multirotor UAV platforms can be utilized to achieve various learning outcomes in undergraduate mechatronics education. This study is based on a PX4 ecosystem combined with the MATLAB Simulink programming environment, covering both hardware and software aspects to support engineering education. The paper explains (i) which learning outcomes can be obtained, (ii) how mathematical models can be derived and implemented in simulation software, (iii) which hardware components are essential, their approximate costs, and possible upgrades based on available budgets, and (iv) which experiments students can perform using the UAV platform. A proposed educational prototype integrates airframe parts produced using additive manufacturing technologies with standard multirotor components. Additionally, a series of experiments were designed, including extensive testing of the multirotor control module. Three learning outcomes related to UAV hardware were incorporated into the engineering curriculum, while two software-related outcomes were addressed through student workshops. Future plans include the implementation of multiple UAV platforms in the educational process to further enhance learning outcomes. Full article

This paper presents methods for a UAV-based survey of the site “Kuklica” near Kratovo, North Macedonia. Kuklica is a rare natural complex with earth pyramids, and because of its exceptional scientific, educational, touristic, and cultural significance, it was proclaimed to be a Natural Monument in 2008. However, after the proclamation, the interest in visiting this site and the threats in terms of its potential degradation rapidly grew, increasing the need for a detailed survey of the site and monitoring. Given the site’s small size (0.5 km²), the freely available satellite images and digital elevation models are not suitable for comprehensive analysis and monitoring of the site, especially in terms of the individual forms within the site. Instead, new tools are increasingly being used for such tasks, including UAVs (unmanned aerial vehicles) and LiDAR (Light Detection and Ranging). Since professional LiDAR is very expensive and still not readily available, we used a low-cost UAV (DJI Mini 4 Pro) to carry out a detailed survey. First, the flight path, the altitude of the UAV, the camera angle, and the photo recording intervals were precisely planned and defined. Also, the ground markers (checkpoints) were carefully selected. Then, the photos taken by the drone were aligned and processed using Agisoft Metashape software (v. 2.1.4), producing a digital elevation model and orthophoto imagery with a very high (sub-decimeter) resolution. Following this procedure, more than 140 earth pyramids were delineated, ranging in height from 1 to 2 m and to 30 m at their highest. At this stage, a very accurate UAV-based 3D model of the most remarkable earth pyramids was developed (the accuracy was checked using the iPhone 14 Pro LiDAR module), and their morphometrical properties were calculated. Also, the site’s erosion rate and flash flood potential were calculated, showing high susceptibility to both. The final goal was to monitor the changes and to minimize the degradation of the unique landscape, thus better protecting the geosite and its value. Full article

This survey provides a comprehensive comparison of prominent open-source unmanned aerial vehicle (UAV) autopilots, focusing on their hardware compatibility, software features, and communication protocols. Additionally, it assesses the impact of these autopilots on research and education by examining their potential for integration with companion computers, compatibility with robot operating system (ROS) middleware and the MATLAB/Simulink environment, and the availability of simulation-in-the-loop (SITL) and hardware-in-the-loop (HITL) simulation tools. The paper concludes with a discussion of the advantages and disadvantages of these leading open-source autopilots. Full article

This paper introduces a drone-based surrogate project aimed at serving as a preliminary educational platform for undergraduate students in the Electrical and Computer Engineering (ECE) fields. Utilizing small Unmanned Aerial Vehicles (sUAVs), this project serves as a surrogate for the inspection of wind turbines using scaled-down pedestal fans to replace actual turbines. This approach significantly reduces the costs, risks, and logistical complexities, enabling feasible and safe on-campus experiments. Through this project, students engage in hands-on applications of Python programming, computer vision, and machine learning algorithms to detect and classify simulated defects in pedestal fan blade (PFB) images. The primary educational objectives are to equip students with foundational skills in autonomous systems and data analysis, critical for their progression to larger scale projects involving professional drones and actual wind turbines in wind farm settings. This surrogate setup not only provides practical experience in a controlled learning environment, but also prepares students for real-world challenges in renewable energy technologies, emphasizing the transition from theoretical knowledge to practical skills. Full article

The aim of this paper is to identify the possibilities of the implementation of the Innovative Management Framework for Intelligent Horticulture (IMFIH) by farmers with the aim of deepening the dynamics of innovation and technologic transfer processes related to the integration of the aerial work capability offered by mini UAV systems in precision horticulture. Starting from an aerial system for intelligent monitoring and smart horticulture applications, the research methodology is designed to understand the specific processes of this transfer of innovation in a field characterized by evolutionary dynamics and in the context of a lack of data. Thus, it is considered to be a mix of both quantitative and qualitative methods used in order to identify the needs and opinions of farmers regarding the possible use of the capabilities of mini UAV systems and especially how to access this capability. The obtained results showed the profile of the farmers interested in mini UAV systems for monitoring field crops and also the relevant factors for initiating/accessing them: specialized education, entrepreneurial education, area owned, ability to create partnerships, intention to access/develop mini UAV systems, and the existence of an integrated framework for analyzing the opportunities and restrictions of implementing mini UAV systems in precision horticulture applications. The integration of the Hype Cycle Paradigm (HCP) into the proposal of IMFIH led to the creation of the IMFIH-HCP as an innovative framework capable of stimulating the dissemination and transfer of knowledge and technology in the case of future horticultural applications of precision in an emerging market. Full article

Smallholder farmers play an important role in ensuring world food security. In addition to food security, small-scale farming also provides numerous other direct and indirect environmental, social, cultural, and economic benefits by improving crop diversification, job security, and self-sufficiency. However, small-scale agriculture faces several challenges which are further exacerbated by climate change, population increase, water scarcity, and soil degradation. Agriculture has seen a lot of technological advancements in the last few decades. However, access to these advancements has not always been economically viable for small or medium farm operations. This article aimed to review the major barriers to small-scale farming and to review the status and potential opportunities offered by advanced technologies that can benefit small-scale holders. Based on the review, we found that economics, marketing, climate change, lack of awareness, educational resources, infrastructure, information, and technology are the major challenges to small-scale farming. Technologies such as unmanned aerial vehicles (UAVs), the IoT (internet of things), irrigation automation, and the use of smartphones are already becoming mainstream in small-scale farming and other technologies like robotics, artificial intelligence (AI), yield monitoring, and food traceability have potential opportunities to solve the challenges that hamper the success of small-scale growers. Full article

The integration of structure from motion (SFM) and unmanned aerial vehicle (UAV) technologies has allowed for the generation of very high-resolution three-dimensional (3D) point cloud data (up to millimeters) to detect and monitor surface changes. However, a bottleneck still exists in accurately and rapidly registering the point clouds at different times. The existing point cloud registration algorithms, such as the Iterative Closest Point (ICP) and the Fast Global Registration (FGR) method, were mainly developed for the registration of small and static point cloud data, and do not perform well when dealing with large point cloud data with potential changes over time. In particular, registering large data is computationally expensive, and the inclusion of changing objects reduces the accuracy of the registration. In this paper, we develop an AI-based workflow to ensure high-quality registration of the point clouds generated using UAV-collected photos. We first detect stable objects from the ortho-photo produced by the same set of UAV-collected photos to segment the point clouds of these objects. Registration is then performed only on the partial data with these stable objects. The application of this workflow using the UAV data collected from three erosion plots at the East Tennessee Research and Education Center indicates that our workflow outperforms the existing algorithms in both computational speed and accuracy. This AI-based workflow significantly improves computational efficiency and avoids the impact of changing objects for the registration of large point cloud data. Full article

Augmented Reality (AR) technology visualizes virtual objects in the real environment, offering users an immersive experience that enhances their spatial perception of virtual objects. This makes AR an important tool for visualization in engineering, education, and gaming. The Unmanned Aerial Vehicles’ (UAVs’) low-altitude public air route (Skyroad) is a forward-looking virtual transportation infrastructure flying over complex terrain, presenting challenges for user perception due to its invisibility. In order to achieve a 3D and intuitive visualization of Skyroad, this paper proposes an AR visualization framework based on a physical sandbox. The framework consists of four processes: reconstructing and 3D-printing a sandbox model, producing virtual scenes for UAVs Skyroad, implementing a markerless registration and tracking method, and displaying Skyroad scenes on the sandbox with GPU-based occlusion handling. With the support of the framework, a mobile application called SkyroadAR was developed. System performance tests and user questionnaires were conducted on SkyroadAR; the results showed that our approachs to tracking and occlusion provided an efficient and stable AR effect for Skyroad. This intuitive visualization is recognized by both professional and non-professional users. Full article

The usage of drone delivery couriers has multiple benefits over conventional methods, and it is expected to play a big role in the development of urban intelligent logistics. Many courier companies are currently attempting to deliver express delivery using drones in the hopes that this new type of tool used for delivery tasks will become the norm as soon as possible. However, most urban residents are currently unwilling to accept the use of drones to deliver express delivery as normal. This study aims to find out the reasons for the low acceptance of the normalization of drone delivery by urban residents and formulate a more reasonable management plan for drone delivery so that the normalization of drone delivery can be realized as soon as possible. A research questionnaire was scientifically formulated which received effective feedback from 231 urban residents in Jinjiang District, Chengdu City. A binary logistic model was used to determine the factors that can significantly influence the acceptance of residents. In addition, the fuzzy interpretive structural model(Fuzzy-ISM) was used to find out the logical relationship between the subfactors inherent to these influencing factors. It was concluded that when the infrastructure is adequate, increasing public awareness and education, enhancing the emergency plan, lowering delivery costs, enhancing delivery efficiency and network coverage, and bolstering the level of safety management can significantly raise resident acceptance of unmanned aerial vehicle(UAV) delivery. Given the positional characteristics of the subfactors in the interpretive structural model(ISM) and matrices impacts croises-multiplication appliance classemen(MICMAC) in this study, we should first make sure that the drone delivery activities can be carried out in a safe and sustainable environment with all the necessary equipment, instead of focusing on increasing the residents’ acceptance right away, in the future work of regularized drone urban delivery has not yet started the construction phase. There should be more effort put into building the links that will enable acceptance to be improved with higher efficiency, which will be helpful to the early realization of the normalization of drone urban delivery if there is already a certain construction foundation in the case where the drone delivery environment is up to standard and hardware conditions are abundant. Full article