| 1. |
- Belloni, Valeria, et al.
(author)
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Crack Monitoring from Motion (CMfM) : Crack detection and measurement using cameras with non-fixed positions
- 2023
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In: Automation in Construction. - : Elsevier BV. - 0926-5805 .- 1872-7891. ; 156
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Journal article (peer-reviewed)abstract
- The assessment of cracks in civil infrastructures commonly relies on visual inspections carried out at night, resulting in limited inspection time and an increased risk of crack oversight. The Digital Image Correlation (DIC) technique, employed in structural monitoring, requires stationary cameras for image collection, which proves challenging for long-term monitoring. This paper describes the Crack Monitoring from Motion (CMfM) methodology for automatically detecting and measuring cracks using non-fixed cameras, combining Convolutional Neural Networks and photogrammetry. Through evaluation using images obtained from laboratory tests on concrete beams and subsequent comparison with DIC and a pointwise sensor, CMfM demonstrates accurate crack width computation within a few hundredths of a millimetre when compared to the sensor. This method exhibits potential for effectively monitoring temporal crack evolution using non-fixed cameras.
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| 2. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
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Architecture, computing, and design assistance
- 2013
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In: Automation in Construction. - : Elsevier. - 0926-5805 .- 1872-7891. ; 32, s. 161-164
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Journal article (peer-reviewed)abstract
- Design is one of the most complex of human endeavors requiring an enormous number of often conflicting criteria to be contemplated when identifying optimal solutions. Design is constrained by guidelines, codes, and standards applicable to the specific cultural and locational context that the design will be sited. Furthermore, a design has to be created within a collaborative team consisting of many professionals focused on specific subsystems and expert preferences that provide unique functionality to the overall design. The increasing use and capability of software tools involved in the creation and processing of such spatial information has also led to elevated levels of complexity that spurred a need to structure, query and reason about multiple spatial representations of buildings and their components in new ways.
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| 3. |
- Borngrund, Carl, 1992-, et al.
(author)
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Deep-learning-based vision for earth-moving automation
- 2022
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In: Automation in Construction. - : Elsevier. - 0926-5805 .- 1872-7891. ; 133
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Research review (peer-reviewed)abstract
- Earth-moving machines are heavy-duty vehicles designed for construction operations involving earthworks. The tasks performed by such machines typically involve navigation and interaction with materials such as soil, gravel, and blasted rock. Skilled operators use a combination of visual, sound, tactile and possibly motion feedback to perform tasks efficiently. We survey the literature in this research area and analyse the relative importance of different sensor system modalities focusing on deep-learning-based vision and automation for the short-cycle loading task. This is a common and repetitive task that is attractive to automate. The analysis indicates that computer vision, in combination with onboard sensors, is more critical than coordinate-based positioning. Furthermore, we find that data-driven approaches, in general, have high potential in terms of productivity, adaptability, versatility and wear and tear with respect to automation system solutions. The main knowledge gaps identified relate to loading non-fine heterogeneous material and navigation during loading and unloading.
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| 4. |
- Brozovsky, Johannes, et al.
(author)
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Digital technologies in architecture, engineering, and construction
- 2024
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In: Automation in Construction. - : Elsevier BV. - 0926-5805 .- 1872-7891. ; 158
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Research review (peer-reviewed)abstract
- Digitalization in the architecture, engineering, and construction (AEC) sector is slow due to significant challenges in technology adoption. The study aims to promote technology adoption by advancing the understanding of digital technologies in the AEC sector. This article presents the findings from a quantitative scoping review, encompassing 3950 technology-related abstracts retrieved from the Scopus database, providing a preliminary assessment of literature size, geographic innovation hotspots, research gaps, and key concepts in the AEC field. The results show that Building Information Modelling (1852 studies) dominates the literature, while topics like 3D Printing (311) and Internet of Things (227) are gaining traction. China (687 publications) and the United States (566) produce most research articles. Despite the increasing interest in emerging technologies, their implementation often necessitates acquiring specific skill sets. Academia needs to put a stronger focus on these technologies in education and tighter collaboration with the industry is needed.
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| 5. |
- Dadhich, Siddharth, 1987-, et al.
(author)
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Field test of neural-network based automatic bucket-filling algorithm for wheel-loaders
- 2019
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In: Automation in Construction. - : Elsevier. - 0926-5805 .- 1872-7891. ; 97, s. 1-12
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Journal article (peer-reviewed)abstract
- Automation of earth-moving industries (construction, mining and quarry) require automatic bucket-filling algorithms for efficient operation of front-end loaders. Autonomous bucket-filling is an open problem since three decades due to difficulties in developing useful earth models (soil, gravel and rock) for automatic control. Operators make use of vision, sound and vestibular feedback to perform the bucket-filling operation with high productivity and fuel efficiency. In this paper, field experiments with a small time-delayed neural network (TDNN) implemented in the bucket control-loop of a Volvo L180H front-end loader filling medium coarse gravel are presented. The total delay time parameter of the TDNN is found to be an important hyperparameter due to the variable delay present in the hydraulics of the wheel-loader. The TDNN network successfully performs the bucket-filling operation after an initial period (100 examples) of imitation learning from an expert operator. The demonstrated solution show only 26% longer bucket-filling time, an improvement over manual tele-operation performance.
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| 6. |
- Dadhich, Siddharth, et al.
(author)
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Key challenges in automation of earth-moving machines
- 2016
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In: Automation in Construction. - : Elsevier BV. - 0926-5805 .- 1872-7891. ; 68, s. 212-222
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Journal article (peer-reviewed)abstract
- A wheel loader is an earth-moving machine used in construction sites, gravel pits and mining to move blasted rock, soil and gravel. In the presence of a nearby dump truck, the wheel loader is said to be operating in a short loading cycle. This paper concerns the moving of material (soil, gravel and fragmented rock) by a wheel loader in a short loading cycle with more emphasis on the loading step. Due to the complexity of bucket-environment interactions, even three decades of research efforts towards automation of the bucket loading operation have not yet resulted in any fully autonomous system. This paper highlights the key challenges in automation and tele-remote operation of earth-moving machines and provides a survey of different areas of research within the scope of the earth-moving operation. The survey of publications presented in this paper is conducted with an aim to highlight the previous and ongoing research work in this field with an effort to strike a balance between recent and older publications. Another goal of the survey is to identify the research areas in which knowledge essential to automate the earth moving process is lagging behind. The paper concludes by identifying the knowledge gaps to give direction to future research in this field.
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| 7. |
- Dave, Bhargav, et al.
(author)
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A framework for integrating BIM and IoT through open standards
- 2018
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In: Automation in Construction. - : Elsevier. - 0926-5805 .- 1872-7891. ; 95, s. 35-45
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Journal article (peer-reviewed)abstract
- The built environment provides significant opportunities for IoT (Internet of Things) deployment, and can be singled out as one of the most important aspects for IoT related research. While the IoT deployment in the built environment is growing exponentially, there exists a gap in integrating these two in a systematic way through open standards and systems. From technological perspective, there is a need for convergence of diverse fields ranging from Building Information Systems and Building Services to Building Automation Systems, and IoT devices and finally the end user services to develop smart, user oriented applications.This paper outlines the efforts to develop a platform that integrates the built environment data with IoT sensors in a campus wide, web based system called Otaniemi3D that provides information about energy usage, occupancy and user comfort by integrating Building Information Models and IoT devices through open messaging standards (O-MI and O-DF) and IFC models. The paper describes the design criteria, the system architecture, the workflow and a proof of concept with potential use cases that integrate IoT with the built environment. Initial results show that both the end users and other research groups can benefit from such platforms by either consuming the data in their daily life or using the data for more advance research.
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| 8. |
- Edrees, Tarek, et al.
(author)
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Comfort level identification for irregular multi-storey building
- 2015
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In: Automation in Construction. - : Elsevier BV. - 0926-5805 .- 1872-7891. ; 50, s. 40-49
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Journal article (peer-reviewed)abstract
- In this article, the System Identification approach is being used to identify the vertical frequencies of the top storey in a multi-storey building prefabricated from reinforced concrete in Stockholm. Before building construction, detailed investigation indicated that the building will not be affected by train vibrations from the nearby railway yard. After building completion, disturbing vibrations were observed in the building. Three measurement types namely: ambient vibration test, forced vibration test on the rails, and forced vibration test have been performed in order to specify the probable reasons for these vibrations.Five methods of structural identification approach, specifically: ARX, ARMAX, BJ, OEand State Space Models have been implemented for the identification process in this study usingthe tests' results. All the test types and model structures utilized have identified a concentration inthe floor only, which is close to the frequencies of human body parts. Furthermore, the article concludes that the ARMAX model and the Output Error model have indicated an excellent performance to predict the mathematical models of vibration's propagation in the building, when compared with other models used from the three types of tests.In addition, the results of the aforementioned system identification methods, implemented for this study, have indicated that there are no other reasons for the disturbing vibrations still observed in the building. Furthermore, the results confirmed the correctness of the previous theoretical and experimental results obtained by different specialists, who stated that the values of floor acceleration are within the acceptable limits, and the probable reason for any disturbance is the resonance between the generated low frequencies and the human body parts’ frequencies.
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| 9. |
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| 10. |
- Fredriksson, Anna, 1979-, et al.
(author)
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Construction related urban disturbances : Identification and linking with an IoT-model
- 2022
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In: Automation in Construction. - : Elsevier. - 0926-5805 .- 1872-7891. ; 134
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Journal article (peer-reviewed)abstract
- While being a significant part of the urban development, construction projects disturb different stakeholders in various ways. There are three problems associated with construction disturbances: (i) most of these disturbances are not recognised by the people causing them, (ii) they are not monitored and (iii) if they are to be monitored, data is spread among stakeholders. This paper defines what a disturbance is, presents a list of disturbances, linking disturbances to stakeholders and, categorising them based on their distance from construction sites (responding to (i)). Next, a IoT domain model is developed, demonstrating how IoT in construction needs to be combined with the sensors of smart cities to capture the primitives of these disturbances (responding to (iii)). This is a first step towards enabling large-scale data-gathering of construction transport disturbances (responding to (ii)), which is a necessity to predict them and allow better construction transport planning to decrease disturbances.
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