Multimedia Internet of Things: A Comprehensive Survey <s> 4) AUTHENTICATION AND CRIME DETECTION <s> The emerging Internet of Things (IoT) that effectively integrates cyber-physical space to create smart environments will undoubtedly have a plethora of applications in the near future. Meanwhile, it is also the key technological enabler to create smart cities, which will provide great benefits to our society. In this paper, four different IoT network architectures spanning various smart city applications are presented and their corresponding network Quality of Service (QoS) requirements are defined. Furthermore, as the beneficiary of smart city, we have the responsibility to actively participate in its development as well. A new network paradigm, participatory sensing, is thus discussed as a special case to highlight the way people may be involved in the information acquisition-transmission-interpretation-action loop. <s> BIB001 </s> Multimedia Internet of Things: A Comprehensive Survey <s> 4) AUTHENTICATION AND CRIME DETECTION <s> Internet of Things concept as a possibility to combine different devices from different areas results in exchange of different data types through different networks. Possibilities and major features of different data exchange and services binding using Internet of Things are described in this paper. An implementation of Internet of Things device and system for vehicle toll payment through the Internet is presented and described. Major advantages of using such a system for beforehand vehicle toll payment are considered and described in this paper. Technologies used to realize such a system as well as embedded application of such solution is described in this paper. Results of vehicle toll payment system using Internet of Things application are presented and described. Performance impact results of the device embedded application for vehicle toll payment system on Internet of Things device is presented and shown. <s> BIB002 </s> Multimedia Internet of Things: A Comprehensive Survey <s> 4) AUTHENTICATION AND CRIME DETECTION <s> Autonomous taxies are in high demand for smart city scenario. Such taxies have a well specified path to travel. Therefore, these vehicles only required two important parameters. One is detection parameter and other is control parameter. Further, detection parameters require turn detection and obstacle detection. The control parameters contain steering control and speed control. In this paper a novel autonomous taxi model has been proposed for smart city scenario. Deep learning has been used to model the human driver capabilities for the autonomous taxi. A hierarchical Deep Neural Network (DNN) architecture has been utilized to train various driving aspects. In first level, the proposed DNN architecture classifies the straight and turning of road. A parallel DNN is used to detect obstacle at level one. In second level, the DNN discriminates the turning i.e. left or right for steering and speed controls. Two multi layered DNNs have been used on Nvidia Tesla K 40 GPU based system with Core i-7 processor. The mean squared error (MSE) for the detection parameters viz. speed and steering angle were 0.018 and 0.0248 percent, respectively, with 15 milli seconds of real-time response delay. <s> BIB003
IP Multimedia System (IMS) based M2M metropolitan platform for traffic management to restrict vehicles entering the prohibited area is detailed in  . Authors in BIB003 , proposed a Deep Neural Network (DNN) based autonomous Taxi model for a smart city. Authors in  presented a novel concept of M-IoT based crime detection in a smart city by analyzing human emotions and CCTV videos. After detection and identification of crime, it is stored in the database and visualized using a Geographic Information System (GIS). As the smart city is the set of heterogeneous devices and networks, various network architecture supporting heterogeneity, e.g., Information-Driven Architecture (IDRA), participatory sensing in building the smart city is high lightened in BIB001 . Automatic toll tax payments are one of the essential features in a smart city. Beforehand payments based on source and destination location, and authentication based on license plate reading as JavaScript Object Notation (JSON) data are described in BIB002 . A detailed survey on M-IoT based road traffic surveillance and accident detection is presented in  .