## 2 Node Hardware Components in WVSNs  
The hardware components of the visual sensor node consist of the image capturing device, processing unit, memory, radio and power supply. The image capturing device could be a CCD webcam (e.g., Meerkats [3], Panopes [4]) or a CMOS imaging device (e.g., Vision Motes [5], Cyclops [6]). The processing unit could be a non-programmable logic or a programmable logic unit. The radio module could be IEEE 802.15.4 (e.g., MeshEye [7], Cyclops [6]), Bluetooth (e.g., MicrelEye [8]) or WiFi (e.g., Meerkats [3]). Basically, CMOS imaging devices are smaller and cheaper than CCD webcams, however, the image quality of CMOS is not as good as that of a CCD webcam. For example, the Cyclops [6] embeds the Agilent ADCM-1700 CMOS imaging device with a resolution 355 \(\times\) 288. The Meerkats [3] equips the Logitech 4000 USB webcam with a resolution 640 \(\times\) 480. In general, better image resolution means larger image size and implies more processing and transmission power. The tradeoff between the visual data quality and system resource consumption depends on the requirements of the application. For applications that require higher image quality (e.g., face recognition in security surveillance), a CCD webcam is a better choice. For applications that requires capturing many images but do not require high resolution (e.g., object tracking in wildlife observation), a CMOS is a better imaging device. Besides the requirements of the application, the imaging device selection depends on the tradeoff between the cost, size, power consumption and visual data resolution. The non-programmable logic unit is usually designed for a specific application so it has better performance and lower power consumption. With mass production, the unit cost could be even lower. For an application that requires high volume of nodes, a non-programmable logic unit is preferable because of its low manufacturing cost. However, the drawback is that the processing unit cannot be altered to meet another function. In programmable logic units (usually FPGAs), the design can be altered for other application. In WVSNs, this flexibility is important because often one needs to change the parameters or the vision computation algorithm to obtained the optimized performance in different environmental settings (e.g., luminance). This flexibility makes programmable logic unit dominate the processing units in WVSNs. The memory and storage requirements for a WVSN is much higher than for a WSN because the sensor nodes needs to capture, process and transmit visual data instead of scalar data. This stringent memory and storage requirement makes most of the existing WSN platforms not applicable for WVSNs. The well-known WSN mote, Mica2 [9] is equipped with 4 KB RAM and 128 KB FLASH to sense and process the scalar data. Cyclops [6] captures low resolution CIF (355 \(\times\) 288) images to perform object detection tasks. It is equipped with 64 KB SRAM and 512 KB FLASH. For the standard VGA (640 \(\times\) 480) image and 24 color bits for each pixel captured by the webcam, the image size is 921.6 K bytes without compression. The required memory and storage requirement is at least 2 MB to have enough space for image processing. Meerkats [3], has 32 MB FLASH and 64 MB DRAM that could process the VGA (640 \(\times\) 480) images to perform object tracking. In summary, the memory requirements for the sensor nodes in WVSNs are at least ten times more than in WSNs. In WVSNs, like in WSNs, most of the sensor nodes are powered batteries and it is often difficult to recharge or replace the battery on the sensor node. Therefore, energy efficient mechanisms have become important research topics in WVSNs to prolong the lifetime of the WVSN. Sophisticated energy efficient mechanisms rely on the understanding the battery discharging behavior in the WVSN. In [10, 11, 12], the detailed battery discharging process is well studied.