# Classification between Failed Nodes and Left Nodes in Mobile Asset Tracking Systems +
## 1 Introduction  
With the development of various embedded computing platforms and low power sensing components, a diverse set of applications using wireless sensor networks (WSN) has been implemented in the past decade. These applications can be divided into two categories based on the type of sensor nodes that they use. These are static sensor networks and mobile sensor networks. Static sensor networks are composed of many stationary nodes, and these sensor nodes are located at various positions to sense local phenomena around them. These nodes have the characteristic that their positions rarely change. Such systems are used in applications, such as environmental monitoring [1; 2], structural health monitoring [3; 4; 5], industrial asset monitoring [6], building automation [7; 8], static asset management [9] and traffic monitoring applications [10]. On the other hand, mobile sensor networks are composed of many mobile nodes. In these networks, one or more mobile nodes are attached to a mobile object to monitor its movement and current location in real time. Such systems can be applied to healthcare systems [11; 12; 13], mobile asset tracking [14; 15; 16; 17] and human monitoring applications [18]. Among various applications where WSN devices are applied, one important application that these systems can benefit is the application of mobile asset tracking. By attaching miniature sized wireless devices, the location and presence of various high-cost mobile assets can be tracked. As an example, in the hospital environment, while patients are encouraged to access different types of devices that are provided for their convenience, the problem of burglary is a major issue. In a recent report, hospitals face yearly losses of $150,000 dollars due to such unpredicted losses of assets [19]. Currently, designated personnel monitor such assets manually, but the use of wireless systems can easily and effectively minimize such incidents. To provide such a wireless system, a mobile asset tracking system was developed and installed at the emergency room of a medical center with the objective of reducing nurses' workloads. This experience also served the purpose of validating the performance of the asset tracking system in a real application environment. In the system, mobile assets (e.g., wheelchairs and syringe pumps) move within the emergency room, freely move out of the tracking area and then can choose to come back to the region, as well. A mobile node is attached to a target asset, and the system tracks the current location of the node using the characteristics of the RF (radio frequency) signals. Specifically, this system is used for two different tasks: asset discovery and asset management. For asset discovery, the approximate location of each mobile medical asset is required; on the other hand, for asset management, the accurate quantity of assets both inside and outside of the target region needs to be known. This system displays the current location of various mobile assets and classifies them as either an inside asset or an outside asset based on the assets' current location and the connection status of the wireless node attached to the mobile asset. Each medical asset with a mobile node is shown in Figure 1.  
The challenge in designing such a system is the fact that wireless nodes can fail, and it is difficult for the system to distinguish nodes that left the coverage area from the nodes that failed to provide effective service. The main reason behind this complication is the fact that these two types of activities show similar behavior: disconnection from the network. Empirically, during the initial studies with the mobile asset tracking system, several reports regarding this issue were generated. As the outcome of radio dis-connectivity from the network is the same for the two cases, the previous patterns of the wireless connection are carefully investigated to devise an efficient classification method.