Complementary Cooperation of CCTV and UAV Systems for Tourism Security and Sustainability

The meaning of sustainability is very broad and has many pillars such as the economy, environment and society. In the tourism industry, another important pillar is security. Tourism security affects the satisfaction and pleasure of tourists on a trivial level, and life and injuries on a significant level. Thus, unless security is guaranteed, tourists will not be able to fully enjoy the attractions and will not even consider the travel itself. Such tourist behavior has a significant impact on short-term and long-term tourism sustainability. Therefore, to enhance tourism security, many policies and frameworks have been suggested and announced in recent years. However, without efficient guidelines for the installation and operation of security devices, it may be hard to obtain actual effectiveness. To support real implementation of security systems in the tourism industry, this study quantitatively addresses the installation and operation issue of security devices in an optimal manner. A complementary cooperation of Closed-Circuit Television (CCTV) and Unmanned Aerial Vehicles (UAV) is suggested to efficiently monitor the key locations of tourism destinations and improve the security. Two mathematical models are developed to derive the optimal location of CCTVs, and the optimal operation schedule of UAVs over multiple time periods. Security requirements, service range, and budget are considered as realistic constraints. The validity of the models is demonstrated through a realistic case study of Nice, France.

Reactive Scheduling Based on Adaptive Manipulator Operations in a Job Shop Configuration with Two Machines

Manufacturing systems are affected by uncertainties, such as machine failure or tool breakage, which result in system downtime and productivity deterioration. In machining processes, system downtime must be reduces. This study aims to establish an automated scheduling technique that flexibly responds to unforeseen events, such as machine failure, based on adaptive operations of the handling manipulator instead of an operation schedule for the machine tools. We propose an “adaptive manipulation” procedure for establishing a reactive revision policy. The reactive revision policy modifies a portion of the manipulator operation sequence, followed by the machine operation sequence. We conduct a physical scheduling simulation on a material-handling manipulator system imitating a job-shop manufacturing system. Through simulations involving machine breakdown scenarios, the applicability of the reactive revision policy based on adaptive manipulation is demonstrated.

Noisy Optimization of Dispatching Policy for the Cranes at the Storage Yard in an Automated Container Terminal

In this paper, we claim that the operation schedule of automated stacking cranes (ASC) in the storage yard of automated container terminals can be built effectively and efficiently by using a crane dispatching policy, and propose a noisy optimization algorithm named N-RTS that can derive such a policy efficiently. To select a job for an ASC, our dispatching policy uses a multi-criteria scoring function to calculate the score of each candidate job using a weighted summation of the evaluations in those criteria. As the calculated score depends on the respective weights of these criteria, and thus a different weight vector gives rise to a different best candidate, a weight vector can be deemed as a policy. A good weight vector, or policy, can be found by a simulation-based search where a candidate policy is evaluated through a computationally expensive simulation of applying the policy to some operation scenarios. We may simplify the simulation to save time but at the cost of sacrificing the evaluation accuracy. N-RTS copes with this dilemma by maintaining a good balance between exploration and exploitation. Experimental results show that the policy derived by N-RTS outperforms other ASC scheduling methods. We also conducted additional experiments using some benchmark functions to validate the performance of N-RTS.

Optimization Method for Operation Schedule of Microgrids Considering Uncertainty in Available Data

Operation scheduling in electric power grids is one of the most practical optimization problems as it sets a target for the efficient management of the electric power supply and demand. Advancement of a method to solve this issue is crucially required, especially in microgrids. This is because the operational capability of microgrids is generally lower than that of conventional bulk power grids, and therefore, it is extremely important to develop an appropriate, coordinated operation schedule of the microgrid components. Although various techniques have been developed to solve the problem, there is no established solution. The authors propose a problem framework and a solution method that finds the optimal operation schedule of the microgrid components considering the uncertainty in the available data. In the authors’ proposal, the objective function of the target problem is formulated as the expected cost of the microgrid’s operations. Since the risk of imbalance in the power supply and demand is evaluated as a part of the objective function, the necessary operational reserve power is automatically calculated. The usefulness of the proposed problem framework and its solution method was verified through numerical simulations and the results are discussed.

FLEX-IoT: Secure and Resource-Efficient Network Boot System for Flexible-IoT Platform

In an internet of things (IoT) platform with a copious number of IoT devices and active variation of operational purpose, IoT devices should be able to dynamically change their system images to play various roles. However, the employment of such features in an IoT platform is hindered by several factors. Firstly, the trivial file transfer protocol (TFTP), which is generally used for network boot, has major security vulnerabilities. Secondly, there is an excessive demand for the server during the network boot, since there are numerous IoT devices requesting system images according to the variation of their roles, which exerts a heavy network overhead on the server. To tackle these challenges, we propose a system termed FLEX-IoT. The proposed system maintains a FLEX-IoT orchestrater which uses an IoT platform operation schedule to flexibly operate the IoT devices in the platform. The IoT platform operation schedule contains the schedules of all the IoT devices on the platform, and the FLEX-IoT orchestrater employs this schedule to flexibly change the mode of system image transfer at each moment. FLEX-IoT consists of a secure TFTP service, which is fully compatible with the conventional TFTP, and a resource-efficient file transfer method (adaptive transfer) to streamline the system performance of the server. The proposed secure TFTP service comprises of a file access control and attacker deception technique. The file access control verifies the identity of the legitimate IoT devices based on the hash chain shared between the IoT device and the server. FLEX-IoT provides security to the TFTP for a flexible IoT platform and minimizes the response time for network boot requests based on adaptive transfer. The proposed system was found to significantly increase the attack-resistance of TFTP with little additional overhead. In addition, the simulation results show that the volume of transferred system images on the server decreased by 27% on average, when using the proposed system.

Optimized Physical Properties of Electrochromic Smart Windows to Reduce Cooling and Heating Loads of Office Buildings

The concept of smart windows that can change the properties of windows and doors in response to external stimuli has recently been introduced. Smart windows provide superior energy savings and control of indoor environments. This concept can advance sustainable architecture, and it will make it possible to connect with the fourth industry, which has developed recently. However, unlike the relevant hardware, is advancing rapidly, research on methods of adjusting smart windows is slow. Therefore, in this study, an analysis of energy use over time was conducted on electrochromic windows, one of the main types of smart windows. Through this analysis, the optimal properties of electrochromic smart windows were identified, and an operation schedule was created. In addition, energy saving rates were derived through a comparison with existing architectural windows.