Biblio

With advances in information and communication technologies, cities are getting smarter to enhance the quality of human life. In smart cities, safety (including security) is an essential issue. In this paper, by reviewing several safe city projects, smart city facilities for the safety are presented. With considering the facilities, a design for a crime intelligence system is introduced. Then, concentrating on how to support police activities (i.e., emergency call reporting reception, patrol activity, investigation activity, and arrest activity) with immersive technologies in order to reduce a crime rate and to quickly respond to emergencies in the safe city, smart policing with augmented reality (AR) and virtual reality (VR) is explained.

The traditional smart-home is designed to integrate the concept of the Internet of Things(IoT) into our home environment, and to improve the comfort of home. It connects electrical products and household goods to the network, and then monitors and controls them. However, this paper takes home safety as the main axis of research. It combines the past concept of smart-home and technology of machine learning to improve the whole system of smart-home. Through systematic self-learning, it automatically figure out whether it is normal or abnormal, and reports to remind building occupants safety. At the same time, it saves the cost of human resources preservation. This paper make a set of rules table as the basic criteria first, and then classify a part of data which collected by traditional Internet of Things of smart-home by manual way, which includes the opening and closing of doors and windows, the starting and stopping of motors, the connection and interruption of the system, and the time of sending each data to label, then use Support Vector Machine(SVM) algorithm to classify and build models, and then train it. The executed model is applied to our smart-home system. Finally, we verify the Accuracy of anomaly reporting in our system.