The innovative on-demand bus system is developed and the result of field tests shows that the system is valid for different city types. On-demand is a demand-responsive transit service where the vehicles transport users after they reserve their seats, and the vehicle does not move if there is no reservation. On-demand bus is an existing technology and it runs all over the world, but the high running cost is a problem. The aim of the developed system is practical introduction of the system from cost viewpoint. Local government can start the service in low cost with cloud computing technology. In order to build up the cloud computing system, schedule calculation system and the communication device in the car are required. In order to validate the developed system, simulation and field test are held. The result of computer simulation shows that the developed calculation algorithm works well as designed. The result of field test shows that the on-demand bus service in three different type cities are provided through the Internet with cloud computing technology and it is evaluated to enable new public transportation system.

Various industries are undergoing transformation given recently available pervasive sensors, low-cost and low-latency digital communication, and distributed control technologies. The objective of this paper is to support the introduction of Internet of things (IoT) technologies in the maritime industry. The maritime industry is analyzed as a system of systems to define performance criteria and functions to be modeled and analyzed through simulation. In this case, the simulation of a shipping system includes models of operation, cargo loading, fuel loading, and docking for maintenance. In the simulation, various kinds of IoT technologies are defined by several input parameters. By changing the parameters, the simulator evaluates the impact of those technologies quantitatively. As a case study, 11 IoT technologies are evaluated and compared. The result reveals several insights that weight of the ship is the most impactful for the profit, controlling damage of the ship’s hull by operation is the most important for safety, and improvement in efficiency at ports is the key to reducing delay time in operation. Moreover, this paper shows that the sensitivity analysis by changing the input parameters can support the decision making of how much investment will be effective in considering the technologies’ levels.

This paper seeks to propose a brand new system for tacit knowledge elicitation in curved shell plates' manufacturing process. By virtualising the manufacturing process and automatically suggesting manufacturing plans, the system would allow the knowledge-interrelated information more specific and understandable. Five areas are studied: 1) the extraction of a curved shell plate's real shape from the point cloud measured by laser scanner; 2) the virtualisation of a curved shell plate's wooden template; 3) the automatic suggestion of the manufacturing plan; 4) the virtualisation of the manufacturing environment; 5) the knowledge elicitation using ripple-down-rules based on the virtualised manufacturing environment and the evaluation result of the system's suggested manufacturing plan. The system which integrates the proposed approaches above is evaluated by conducting a series of experiments in the shipyard. The tacit knowledge existent in the curved shell plate's different situations during the manufacturing process are effectively elicited and represented.