The rapid development and implementation of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) in the engineering and manufacturing field have embraced a virtual identity to ensure nearly real-time adjustment. Warehouses are challenged to reassess its order fulfillment operations while simultaneously being provided with the opportunity to develop its own cloud-based CPS with the aid of IoT devices. Robotic Mobile Fulfillment System (RMFS) is a system controlling mobile robots, mobile storage rack, putaway and picking workstations, charging stations, and wireless communication infrastructure in the context of robotic-assisted warehouse. This paper addresses the value creation utilizing cloud-based CPS in RMFS. By providing an analysis of cloud services and IoT enhancement, theoretical concepts from the literatures are consolidated to solve the research que-stions on how RMFS offering better order fulfillment can gain benefits in terms of operational efficiency and system reliability. The paper also proposes a cloud-based CPS architecture, providing a comprehensive understanding on conflict avoidance strategy in the multi-layers multi-deeps warehouse layout. This research presents six conflict classifications in RMFS and provides a case study in the real-life context. Dock grid conflict is a new type of conflict appearing in multi-deeps RMFS. A scenario analysis with real customer orders is applied to present the collision detection and solution.

Heavy downpours always bring trouble to Hong Kong during the rainy season. Severe rainfalls and flooding will delay the transportation, cause the loss of property or even kill lives. However, there is limited research that investigated the problems of the drainage system and stormwater management. Regarding the Internet of Things (IoT) development and successful example of IoT application, Hong Kong has the potential to become a smart city. The smart drainage system is one of the possible research directions. A prototype IoT system is decided with hardware and software. Experiments are conducted to collect the data. The data is then used to train the Artificial Neural Network. The analysis and predictive maintenance solutions are proposed to help the stormwater and drainage management. The results show that a well-trained algorithm can predict the drainage situations. The cross-validated results showed that it is reliable and able to predict most of the testing inputs. This paper aims at benefit to Hong Kong drainage service and the society.

The purpose of this research is to investigate the effectiveness of Digital Content Marketing (DCM) on a Mixed Reality (MR) training platform environment with the consideration of online purchase intention (OPI) through social media. E-commerce today encounters several common issues that cause customers to have reservations to purchase online. With the absence of physical contact points, customers often perceive more risks when making purchase decisions. Furthermore, online retailers often find it hard to engage customers and develop long-term relationships. In this research, a Structural Equation Model (SEM) is proposed to examine the efficacy of DCM from both immediate and long-term OPI. The results examine whether adopting DCM on an MR training platform environment through social media brings positive results in OPI. Empirical research was carried out through online questionnaires collected in 2021 and 2022. A total of 374 questionnaires were qualified for data analysis in this study, conducted with IBM SPSS and AMOS. The results imply that DCM is critical to stimulating both immediate and long-term OPI. The immediate OPI is positively affected by increasing perceived value through MR in DCM. Regarding the long-term OPI, increased customer engagement with DCM under MR environment can cultivate brand trust and significantly affect the long-term OPI.

The deployment of automated guided vehicles in the automated warehouse has a great impact on the capacity in handling logistics activities. Simulation offers practical feedback and analytical solution at a designing stage of engineering applications. As for automated warehouse system, the optimal set of the combination of automated guided vehicles and workstations are highly depended on the size, dimensions, layout structure of the warehouse and working process. In this paper, the operations in the automatic warehouse were simulated to determine possible scenarios of the warehouse setting regarding the demand pattern of the packaging order. In the automatic warehouse, the racks are transferred by the automated guided vehicles to the workstations. The contribution of the study is that it not only considers the optimal number of AGV but also the optimal number of workstation for automatic warehouse. To estimate the possible setting with the highest order turn-over rate, varies scenarios were considered in the model. As a result, the estimated layout and warehouse setting were suggested.

The rapid growth of the airline industry has caused an enormous demand in the context of air transport and air traffic congestion in several hub airports. In order to alleviate this situation and resolve the imbalance between the arrival and departure rate, efficient runway usage in airport capacity management is an immediate and feasible solution as compared to airport expansion and runway construction. Air Traffic Control (ATC) operators could optimize their runway capacity by operating dynamic runway configuration in switch-mode runways based on the air and airport traffic conditions. A semi-mixed mode runway is considered in this paper, wherein some runways are configured for either landing or take-off operations, while others are operated in switch mode. The demand for arrival and departure is subject to the passenger's demand, flight availability, and timings, preferred flight schedule, and frequency of flight schedule service, and usually vary in different hours (peak and nonpeak hours). Given this feature, ATC can reconfigure the runway mode responding to the current demand for arrival and departure and further seize the runway capacity via a systematic approach. Under the semi-mixed mode situation, formulating the coordination of dynamic runway configuration planning and the Aircraft Sequencing and Scheduling Problem is proposed. The air traffic pattern in Hong Kong International Airport (HKIA) is used as a test case to evaluate the performance of this proposed model. Based on the test results, it was found that this dynamic runway configuration planning and semi-mixed runway design can utilize runway capacity more efficiently. In the numerical study, the dynamic runway configuration planning achieved 71.6%% and 37.08% reduction of flight tardiness than the two segregated runway systems (two landings and one take-off runways and one landing and two take-off runways) in HKIA.