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Accurate earthwork quantity estimation is essential for effective project planning and cost management in the Architecture, Engineering, and Construction (AEC) industry. Traditional methods for quantity takeoff are often time-consuming and susceptible to human error, particularly when working with unstructured datasets such as CAD drawings. This study introduces the Earthwork Network Architecture (ENA), a novel deep learning framework that incorporates Large Language Models (LLMs), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM) networks, and Transformers to automate and enhance the accuracy of earthwork quantity estimation. We assume that if LLMs can be trained effectively using such unstructured construction dataset, the effects such as improved accuracy and the challenges of LLMs can be clearly examined. Among the architectures tested, the LLM-based ENA demonstrated superior performance, achieving faster convergence, greater loss reduction, and higher classification accuracy, with a Quantity Takeoff Classification accuracy of 97.17%. However, the LLMs required significantly more computational resources compared with other models. These findings suggest that LLMs, typically used in natural language processing, can be effectively adapted for complex AEC datasets. This study lays the groundwork for future AI-driven solutions in the AEC industry, underscoring the potential of LLMs and Transformers to automate the quantity takeoff process and manage multimodal data in construction projects.

This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud Data (PCD) of Airborne Laser Scanning (ALS). Advanced scanning techniques capture detailed geometry from the physical site and generate high-resolution point clouds, which are processed to create 3D models for GIS integration. The critical contribution of this research lies in a scalable Scan to BIM mapping process, which can be used for generating building footprints and masses, including attributes, on 3D GIS. The resulting integrated BIM–GIS dataset provides an accurate building mass, facade information, facility asset management, and architectural design and facilitates improved decision-making in urban planning based on enhanced visualization, analysis, and simulation. This study suggests a flexible Scan to BIM mapping process description based on use cases, including algorisms. Through prototype development, a case study demonstrates the effectiveness of the process approach, the automatic generation of BIM on a 3D GIS platform, and reducing the manual efforts. The proposed method automatically creates DEM, SHP, GeoJSON, IFC, and coordinate system information from scan data and can effectively map building objects in 3D GIS.

The dissolved gas concentration in a stirred tank has significant importance in the chemical and biological processing industries as mass transfer from the injected gas to an aqueous solution must occur for the gas to be usable. As the solubility of the gas in the solution is low and there are no probes for measuring dissolved gas concentration, a volumetric mass transfer coefficient is selected as a criterion of design for the scale-up of stirred reactors. However, it is difficult to accurately predict the non-equilibrium state dissolved gas distribution using only the volumetric mass transfer coefficient. In this study, computational fluid dynamics (CFD)-based numerical analysis was conducted to systematically evaluated the effects of mass transport by convective flow on the distribution of dissolved carbon monoxide in a stirred tank. The dissolved carbon monoxide distribution and the volumetric mass transfer coefficient were compared at various rotational speeds of the impellers. At a rotational speed of 900 RPM, the Pearson correlation coefficient was about 0.52, which denotes a moderate correlation. In contrast, Pearson correlation coefficients less than 0.20 were obtained for speeds less than 700 RPM, indicating a weak correlation. By considering the dissolved carbon monoxide transport that occurs during convective flow in stirred tanks, we can provide more accurate information about the dissolved carbon monoxide distribution.

The number of scan-to-BIM projects that convert scanned data into Building Information Modeling (BIM) for facility management applications in the Mechanical, Electrical and Plumbing (MEP) fields has been increasing. This conversion features an application purpose-oriented process, so the Scan-to-BIM work parameters to be applied vary in each project. Inevitably, a modeler manually adjusts the BIM modeling parameters according to the application purpose, and repeats the Scan-to-BIM process until the desired result is achieved. This repetitive manual process has adverse consequences for project productivity and quality. If the Scan-to-BIM process can be formalized based on predefined rules, the repetitive process in various cases can be automated by re-adjusting only the parameters. In addition, the predefined rule-based Scan-to-BIM pipeline can be stored and reused as a library. This study proposes a rule-based Scan-to-BIM Mapping Pipeline to support application-oriented Scan-to-BIM process automation, variability and reusability. The application target of the proposed pipeline method is the plumbing system that occupies a large number of MEPs. The proposed method was implemented using an automatic generation algorithm, and its effectiveness was verified.

A technology for low-power high data-rate digital capsule endoscopy with human body communication (CEHBC) is presented in this paper. To transfer the image data stably with low power consumption, the proposed system uses three major schemes: Frequency selective digital transmission (FSDT) modulation with HBC, the use of an algorithm to select electrode pairs, and the LineSync algorithm. The FSDT modulation supports high-data rate transmission and prevents the signal attenuation effect. The selection algorithm of the electrode pair finds the best receiving channel. The LineSync algorithm synchronizes the data and compensates for data polarity during the long data transmission section between the capsule endoscope and the receiver. Because all the major functional blocks of the CEHBC transmitter can be implemented as digital logics, they can be easily fabricated using the field programmable gate array (FPGA). Moreover, this CEHBC transmitter can achieve low power-consumption and can support a relatively high data rate in spite of using its clock a few tens of MHz slower. The proposed CEHBC-TXD is the digital portion of the CEHBC transmitter that provides low-power (3.7 mW) and high data-rate (6 Mbps) performance while it supports a high-resolution image (480 × 480 byte) at 3.13 fps.

This paper presents an energy management integrated circuit for multiple energy harvesters in wireless body area network applications. The electrical power acquired from a single energy harvester around a human body is limited to micro watts, which is insufficient to drive a wearable electronic device. To increase this small amount, the energy from a number of harvesters has to be combined. By combining the energy from multiple distributed harvesters, each one producing negligible energy, significant energy for wearable devices can be obtained. In designing an energy management circuit for a wearable device, there are two issues to be resolved. The first is related to the power consumption of the circuit, and the second issue is related to the methods needed to manage the wide range of power that occurs as the energy input changes during harvesting. In this paper, an energy management circuit that resolves the two issues above is described. The circuit was integrated using 0.13 µm Taiwan Semiconductor Manufacturing Company complementary metal-oxide-semiconductor technology. The energy management circuit is designed to combine up to three sources of harvested energy with more than 90% operating efficiency over the entire power range of the energy harvested.