Despite various economic crisis situations around the world, the courier and delivery service market continues to be revitalized. The parcel shipping volume in Korea is currently 3.37 billion parcels, achieving a growth rate of about 140% compared to 2012, and 70% of parcels are from metropolitan areas. Given the above statistics, this paper focused on the development of an underground logistics system (ULS), in order to conduct a study to handle the freight volume in a more eco-friendly manner in the center of metropolitan areas. In this paper we first analyzed the points at which parcel boxes were damaged, based on a ULS. After collecting image data of the parcel boxes, the damaged parcel boxes were detected and classified using computerized methods, in particular, a convolutional neural network (CNN), MobileNet. For image classification, Google Colaboratory notebook was used and 4882 images were collected for the experiment. Based on the collected dataset, when conducting the experiment, the accuracy, recall, and specificity of classification for the testing set were 84.6%, 82% and 88.54%, respectively,. To validate the usefulness of the MobileNet algorithm, additional experiments were performed under the same conditions using other algorithms, VGG16 and ResNet50. The results show that MobileNet is superior to other image classification models when comparing test time. Thus, in the future, MobileNet has the potential to be used for identifying damaged boxes, and could be used to ensure the reliability and safety of parcel boxes based on a ULS.

Today, a lot of research on autonomous driving technology is being conducted, and various vehicles with autonomous driving functions, such as ACC (adaptive cruise control) are being released. The autonomous vehicle recognizes obstacles ahead by the fusion of data from various sensors, such as lidar and radar sensors, including camera sensors. As the number of vehicles equipped with such autonomous driving functions increases, securing safety and reliability is a big issue. Recently, Mobileye proposed the RSS (responsibility-sensitive safety) model, which is a white box mathematical model, to secure the safety of autonomous vehicles and clarify responsibility in the case of an accident. In this paper, a method of applying the RSS model to a variable focus function camera that can cover the recognition range of a lidar sensor and a radar sensor with a single camera sensor is considered. The variables of the RSS model suitable for the variable focus function camera were defined, the variable values were determined, and the safe distances for each velocity were derived by applying the determined variable values. In addition, as a result of considering the time required to obtain the data, and the time required to change the focal length of the camera, it was confirmed that the response time obtained using the derived safe distance was a valid result.

Recently, as air pollution and particulate matter worsen, the importance of a platform that can monitor the air environment is emerging. Especially, among air pollutants, nitrogen dioxide (NO₂) is a toxic gas that can not only generate secondary particulate matter, but can also derive numerous toxic gases. To detect such NO₂ gas at low concentration, we fabricated a GNWs/NiO-WO₃/GNWs heterostructure-based gas sensor using microwave plasma-enhanced chemical vapor deposition (MPECVD) and sputter, and we confirmed the NO₂ detection characteristics between 10 and 50 ppm at room temperature. The morphology and carbon lattice characteristics of the sensing layer were investigated using field emission scanning electron microscopy (FESEM) and Raman spectroscopy. In the gas detection measurement, the resistance negative change according to the NO₂ gas concentration was recorded. Moreover, it reacted even at low concentrations such as 5–7 ppm, and showed excellent recovery characteristics of more than 98%. Furthermore, it also showed a change in which the reactivity decreased with respect to humidity of 33% and 66%.

We conducted experiments to improve the electrical properties of the CNW (carbon nanowall), which has lower electrical properties than other carbon allotropes such as graphene and CNT (carbon nanotube), and report the results through this article. The carbon nanowall has an amorphous buffer layer, leading to low electrical properties, and MWCNT (multi-walled carbon nanotube) was used as a buffer layer to improve this issue, and then a CNW was grown on it by CVD (chemical vapor deposition). Then, the content of MWCNT was adjusted to 30 µL, 50 µL, and 70 µL to analyze the electrical properties accordingly. Alteration in carrier concentration, carrier mobility and resistivity were observed as electrical properties. Dramatic changes in electrical properties with MWCNT content were identified. The ohmic contact state between the MWCNT-based buffer layer and the CNW was investigated by analysis of the I-V and I-R characteristics and the electrical stability according to the linearity of the curve.

With the growth of the online market, demand for logistics and courier cargo is increasing rapidly. Accordingly, in the case of urban areas, road congestion and environmental problems due to cargo vehicles are mainly occurring. The joint courier logistics system, a plan to solve this problem, aims to establish an efficient logistics transportation system by utilizing one joint logistics delivery terminal by several logistics and delivery companies. However, several courier companies use different types of courier invoices. Such a system has a problem of information data transmission interruption. Therefore, the data processing process was systematically analyzed, a practically feasible methodology was devised, and delivery invoice information processing standards were established for this. In addition, the importance of this paper can be emphasized in terms of data processing in the logistics sector, which is expected to grow rapidly in the future. The results of this study can be used as basic data for the implementation of the logistics joint delivery terminal system in the future. And it can be used as a basis for securing the operational reliability of the joint courier logistics system.

This study evaluated the development and validation of an integrated operational model for the Underground Logistics System (ULS) in South Korea’s metropolitan area, aiming to address challenges in urban logistics and freight transportation by highlighting the potential of innovative logistics systems that utilize underground spaces. This study used conceptual modeling to define the core concepts of ULS and explored the system architecture, including cargo handling, transportation, operations and control systems, as well as the roles of cargo crews and train drivers. The ULS operational scenarios were verified through model simulation, incorporating both logical and temporal analyses. The simulation outcomes affirm the model’s logical coherence and precision, emphasizing ULS’s pivotal role in boosting logistics efficiency. Thus, ULS systems in Korea offer prospects for elevating national competitiveness and spurring urban growth, underscoring the merits of ULS in navigating contemporary urban challenges and championing sustainability.