Wireless Sensor Network Based Active Logistics Status Tracking System

With the increasing complexity of modern logistics system, it is of great significance to study how to effectively control the logistics process to save labor costs by implementing real-time supervisory. The traditional logistics tracking systems usually use centralized control and optimization methods, Although these methods can optimize the operation of the logistics system in a certain extent, they are unable to meet the needs of today’s logistics system monitoring. Compared with the previous technology such as bar code and RFID, wireless sensor networks do not need the pre-deployed network infrastructure to collect and transmit the data. Equipped with the processor and memory, the sensor nodes also can perceive the status information of the goods and perform certain kinds of processing tasks,The active logistics status tracking system takes advantage of the computing capabilities of wireless sensor network. After collecting the logistics information, the wireless sensor node can do some data analyzing and decision-making. Therefore, some business logics can be performed in the wireless sensor node. The overload on the network and backend server can be reduced and the efficiency of logistics operations can be improved. Active tracking model based on finite state machine and rule-based event processing and decision-making have been proposed and implemented in the wireless sensor node. Wireless sensor nodes manage the states of the logistics objects through the active tacking model. Rule based event processing and decision-making describes how to process events and which decision-making behavior should be taken when a specific event occurs. The active logistics status tracking system can not only get the status information of the logistics process, but also make timely response to the status change.Testing result showed that sensor network based active logistics status tracking system not only collects raw data from logistics object and sends them to the background system, but also performs certain data analyzing and decision making. It can shorten the responding delay to the event occurred in the logistics process, reduce the amount of data transferred to the background system and relieve the processing burden on the background system.