## 2 Related Work
### Wireless Multimedia Sensor Networks and Its Applications  
In WMSN, each sensor node is equipped with visual and audio information collection modules such as microphones and video cameras. These nodes can retrieve multimedia content from the networks at variable rates and deliver the captured information through multi-hop communication to the sink. As compared to typical WSN, there are many research challenges that must be addressed such as high packet loss rate, shared channel, limited bandwidth, high variable delays, and lack of fixed infrastructure in WMSN. To overcome the mentioned deficiency, lots of research have been conducted in the aspects of algorithms, protocols, and hardware for the development of WMSN. Moreover, WMSN is expected to be employed increasingly for the potential applications such as surveillance and monitoring applications.  
Among them, object tracking, which has been widely used and deployed in many applications, consists of object detection, object classification, and object reporting schemes. Considering these functions, wireless sensor networks (WSNs) become the potential architecture on which to implement object tracking. This is because WSNs are capable of detection and delivery at the same time in a cost efficient way. In addition, there are many applications on the WMSN such as road traffic monitoring, health-care applications, and area monitoring, etc. Road traffic monitoring [8; 9] is defined as monitoring the behavior of vehicles on the road. Road traffic forecasting is important to the safety of the driver, traffic management and also fuel saving. As a promising application for real-time application, power plant [10] and port docks [11] can be monitored through deploying wireless multimedia sensor networks as well as real-time streaming to deal with emergency. Through the health-care applications [12; 13], doctors and caregivers could monitor the patients' condition and activities, remotely. These two tracking and monitoring application can be applied into industrial environment by preventing unexpected events and accidents in an efficient way. As an example, [PERSON] et al. [14] proposed a new SchedEx-GA, integrated cross-layer framework, to admit a network configuration. Moreover, [PERSON] et al. [15] proposed end-to-end data delivery reliability (E2E-DDR) to estimate and optimize the reliability in industrial sensor networks. They introduce a new mapping function with the packet reception ratio, background noise, and received signal strength by modeling background noise and path loss model. On the other hand, [PERSON] et al. [16] proposed an energy-efficient QoS routing algorithm along reliable path by classifying the industrial sensing data into three data types and setting their priority. This classification is used to establish forwarding node set and strategies to guarantee QoS in the aspects of reliability and real-time.  
There are some research work to enhance the performance of WMSN. At first, [PERSON] and [PERSON] [17] presented how to utilize background subtraction and compression techniques to reduce data. They analyzed the previous work in the aspects of computation and communication energy, time, and quality and provide quantitative experimental results for packet loss on the Android platform. In addition, [PERSON] et al. [18] proposed how to improve system performance through multiple input multiple output along with compressive sensing. With their help, reduced energy consumption and acceptable image quality are achieved.