Abstract
A mobile asset with a sensor node in a mobile asset tracking system moves around a monitoring area, leaves it, and then returns to the region repeatedly. The system monitors the in/out status of the mobile asset. Due to the continuous movement of the mobile asset, the system may generate an error for the in/out status of the mobile asset. When the mobile asset is inside the region, the system might determine that it is outside, or vice versa. In this paper, we propose a method to detect and correct the incorrect in/out status of the mobile asset. To solve this problem, our approach uses data about the connection state transition and the battery lifetime of the mobile node attached to the mobile asset. The connection state transition is used to classify the mobile node as normal or abnormal. The battery lifetime is used to predict a valid working period for the mobile node. We evaluate our method using real data generated by a medical asset tracking system. The experimental results show that our method, by using the estimated battery life time or by using the invalid connection state, can detect and correct most cases of incorrect in/out statuses generated by the conventional approach.
Highlights
The development of information technology has created a demand for small sized computing devices
We investigate the reason for the generation of false reports in the mobile asset tracking system described in [10] and determine that they are generated by incorrect in/out status reports of the mobile nodes attached to the mobile medical assets
We develop a framework to detect and correct the incorrect in/out status of a mobile node in a mobile asset tracking system based on the properties of mobile nodes
Summary
The development of information technology has created a demand for small sized computing devices. This paper describes how to recognize and correct the incorrect in/out status of a mobile node on an application server that is located outside the WSN. We detect two failures that cause incorrect in/out status of the mobile node: abnormal connection state and exhausted battery. The contributions of this paper are as follows: We develop a framework to detect and correct the incorrect in/out status of a mobile node in a mobile asset tracking system based on the properties of mobile nodes. This method is applicable to many mobile asset tracking applications.
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