## 2 Network Architecture
An object detection and high resolution image acquisition via a two-tiered heterogeneous sensor network is presented in [9] that uses stereo image sensor nodes at the lower tier and high resolution actuated cameras at the upper tier of the network. The low-cost, low-power, non-actuated resource constrained stereo image sensors are used to compute the 3-D object location after detecting it in order to adjust the pan/tilt/zoom settings for the high imaging actuated platforms, Canon PTZ camera (VC-C4R). The work shows that the use of two-tiered network has a significant effect in reducing energy consumption and minimizing loss in detection of high resolution image acquisition systems comparing to single-tiered system. Two Cyclops platforms are used as stereo camera node and configured to continuously monitor the network after they finish from the process of camera calibration. If an object is detected, by using simple frame differencing, then one of the Cyclops pair will start the process of computing the 3-D location of the detected object and adjusting the associated pan/tilt/zoom settings of the high resolution actuated camera at the upper-tier. Finally, the adjusting information computed by the lower-tier platforms is transmitted to the upper tier platform which is actuated accordingly to start capturing high resolution images of the object. A multi-tier multi-modal network, using different sensing modalities and capabilities, is presented in [10] for environmental monitoring. The network is self-organized into three tiers of distinct sensor nodes, where the first tier is equipped with passive infrared (PIR) sensors that are capable of detecting objects in the sensing field as a first task in an environmental monitoring or tracking application. The second tier is equipped with smart visual camera sensors that can identify objects in their FoV by determining the object's predominant color. The third tier is equipped with visual sensors that are capable for computing the location of identified objects and their moving path and responsible for target tracking, as they move through the network after identifying them by the second tier sensors. During the network operation, the PIR sensors in the first tier are always active, as they are low power sensors, and monitoring the network. In case they detect any object, they alert the camera sensors in the second tier and wake them up to start capturing images for the detected objects and try to identify them. In case of successfully identifying the objects by their predominant color, the camera sensors in the second tier will wake up the powerful visual sensors in the third tier in order to track them. In [11], an integrated mobile surveillance system of two-tiers for WMSN called (iMouse) is presented, which uses static and mobile wireless sensors for detecting and analyzing unusual events. The system consists of several static sensor nodes, some mobile sensors, and an external server or base station. The static nodes (MICAz-type nodes) form a typical WSN to monitor the environment and collect three types of data (light, sound, and temperature) and notify the base station of unusual events. The locations of these sensors are assumed to be known using GPS or any localization system. The mobile sensors (composed of Lego car and Stargate board connected with wireless mote, webcam, and WLAN card) move to event location when they are notified by the base station to capture images and transmit them to base station. If the number of detected events is less than or equal to the number of mobile nodes, the base station schedules mobile nodes to visit the emergency sites using the maximum matching technique in a bipartite graph to conserve their energy as much as possible. But if the number of detected events is more than the number of mobile nodes, the base station first clusters the emergency sites before it schedules the mobile nodes to each cluster.