Special Issue Engineering in General Information Sciences Others

A Study on the Development of a Traffic Volume Counting Method by Vehicle Type and Direction Using Deep Learning

The turning movement count is investigated to understand the traffic conditions at intersections and identify bottleneck locations. In recent years, methods utilizing probe data and AI-based analysis of video images have been developed to streamline the survey process. Existing methods can count vehicles as they pass but struggle to classify vehicle types. Therefore, the objective of this study is to develop a method for counting turning movement count by vehicle type using deep learning. In this method, YOLOv8 is used to detect cars, buses, and trucks in video images, and BoT-SORT is used for tracking. When a vehicle being tracked crosses the cross-sectional lines and auxiliary lines at the intersection captured in the video images, it is counted by class. In this case, the entry direction of vehicles that cannot be determined upon entering the intersection is estimated based on accurately counted vehicles. Additionally, the entry direction is inferred from a series of vector information within the detection bounding boxes. The results of the verification experiment showed that the proposed method can count the directional traffic volume with an accuracy of over 95.0% and classify the three vehicle classes—car, bus, and truck—with an accuracy of over 90.0%.

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Special Issue Engineering in General Information Sciences Others

Detecting Near-Miss Actions and Estimating Physical Fatigue among Construction Workers Using Wearable Sensors

Labor shortages in the construction industry have become a serious issue in developed countries, particularly in Japan, where workforce aging and declining recruitment of young workers are significant challenges. In this context, ensuring worker safety has become increasingly critical. While occupational accidents in Japan's construction industry have decreased annually due to proper safety measures, the construction industry still has the highest number of fatalities among all industries. Falls from height and falls on the same level are the leading causes of injuries and fatalities. Therefore, detecting near-miss incidents (such as tripping and slipping) that precede falls, along with physical fatigue, could help prevent occupational accidents. This study investigated the feasibility of detecting near-miss incidents and estimating fatigue levels using wearable sensors suitable for continuous monitoring at construction sites. We conducted validation experiments simulating near-miss actions and fatigue conditions. Results showed that applying a Convolutional Neural Network (CNN) to data collected from an iPhone® placed in workers' trouser pockets achieved an F1-score of 0.95 in detecting near-miss actions. Additionally, by comparing body sway magnitudes before and after fatigue, we confirmed the potential for estimating physical fatigue.

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Article Engineering in General

Evaluation of Revitalization Measures for Central City Areas Considering Changes in Human Flows

In recent years, a declining population and an aging and decline have led to a reduction in the vibrancy and economic activity of the city. Various regional cities have taken measures to revitalize their central city areas. However, they have yet to develop a method to quantify the effects of these measures. In this study, using a device equipped with Internet of Things (IoT), we obtained basic data on the number of visitors before the COVID-19 to quantify pedestrian traffic along Kokusai Street. Our findings revealed that the implementation of revitalization strategies led to a notable increase in the number of individuals visiting the area, as well as in the average duration of their stay. This suggests that the implemented measures have the potential to contribute to the revitalization of the area, thereby fostering the creation of a vibrant town center.

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Secondary Publication Engineering in General Information Sciences

An e-Management Method and Self-Driving Frame of on-Demand-to-Supply Robot Type using Ternary/Pair-Map

Our study on 3M&I-artifacts body looks at the (intangible) problems from the traditional Taylor-style static to dynamic (cock-pit) e-management approaches. Since the invention of pair-map (1983) at profit max, we are attempting to advance the on (moving-space)-management by pair (accelerator, brake) matrix approach. This attempt could be now characterized as the problem of profit max by pair (revenue, cost) method, and would be visualized and digitalized such as such a heliocentric vs. geocentric science as mobile “enterprise x computer” robots of SW (middle initiative) base. Finally, a static vs. moving-space automobile-like case on the pair-typed driving map is graphically given and discussed toward the shedding of classic pair-map at 2-center type since 1983.

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Technical Article Engineering in General Information Sciences

Development of Technology for Generating Panorama and Visualization Using Two-viewpoint Images

Research on tracking and performance analysis of athletes using video images has been actively conducted with the aim of improving athletes' competitive performance. However, when filming plays in field sports, it is difficult to capture the entire field with a single camera without filming from a specific point, such as a spectator's seat on the corner side, because the field is long sideways. Even if the entire field is captured, the players at the back of the field appear small, making analysis difficult. Other issues include the fact that since many coaches and analysts film where the play is progressing, it is hard for them to track the ball seamlessly when the position of play changes significantly depending on the position of ball. To solve this problem, we develop in this study a technology to automatically generate panoramic video images that cover the entire field by using two video cameras. Using this technology, we aim to generate panoramic images of the entire field that makes it possible to surely measure and analyze all players and the ball.

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Secondary Publication Architecture Business & Management Economics Engineering in General Information Sciences Interdisciplinary Sciences

Nature versus Artifacts Body: One-Leaf Hyperboloid Type, Pair-Map Microcosm and Nested Economics

Toward digital-era, there is more increasing the portion of artifacts on the earth, and is attainable to the global environment of nature versus artifacts bodies. At the paper, we first suppose One-leaf Hyperboloid and the typical cases:Social (or enterprise) and Physical bodies as the base of nature vs. artifacts bodies. Second, the traditional pair-map is here developed, is semi-finalized at a generalization including Nash’s zone, and its 3D-like body is visually embodied as the two illustrations. Third, for a fractal(nested) mother of pair-map and its Nash’s zone, the shared equilibrium problem of 3D-type is discussed on the Trickle-down effort vs. Modern money theory (up) at Mt. Fuji type in the economic society. Finally, it is remarked that the latter might be better than the former at income distribution.

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