The Research On Missing Tag Detection Algorithm In Large Smart Warehouse

As a key technology to promote the development of information technology and industrial renewal,the Internet of Things(Io T)organically connects things with people and things with things through ubiquitous sensor nodes.Things can identify each other through the bridge of radio frequency identification(RFID)technology.With the rapid development of sharing economy and express industry,fragmented large-scale orders promote the warehouse management industry to become more automatic and more intelligent.The large intelligent storage not only collect the commodity information,but also supervise the goods.RFID technology can realize the monitoring of tagged items,for instance,it can detect the missing items through detecting missing tags.However,in the case of large-scale intelligent storage with massive RFID tags,the tag reply collision and the existence of unknown tags will affect the missing tag detection.Therefore,this thesis studied the missing tags detection algorithm in large-scale RFID systems.The existing researches on missing tag detection used Bloom,hash function,polling and other methods.However,the existing algorithms cannot solve the problems of tag reply collision and unknown tags interference effectively.The time cost of basic polling protocol is too high.Using the hash method will lead to tag slot collision and false positive problems.Bloom idea will lead to a large proportion of frame slot collision when the tags number is large.To solve the above problems,this thesis carried out deep research on RFID technology,and studied the working principle of the RFID system.After compared with the different international standards,this thesis studied the missing tag detection algorithms and parameter setting.Finally,the two algorithms were proposed:(1)In order to detect missing tags,this thesis proposed missing tag detection algorithm in multi-area to detect the abnormal tag sets and divide them into missing tags and shifting tags,and then processed the detection data.In this algorithm,the background server optimizes the reader location selection according to the region shape characteristics.After that,the reader implements the missing tag detection algorithm at each position to obtain the abnormal tag set.The background server calculates the numbers of abnormal tags reply slots in each frame to form the slot distribution map.Compared with the actual slot distribution map of the reader executing,the missing tags and the shifting tags can be obtained.Finally,by processing the data,the internal logistics structure of intelligent storage can be optimized.(2)In order to identify the missing tags,this thesis proposed a group-based missing tag identification algorithm for large-scale RFID system.The core of this algorithm is to assign the tags reply slot number by tag grouping and reader broadcast vector to avoid the slot collision caused by hash calculation,Moreover,tags use 1bit short reply to reply reader,so the execution time of the algorithm is reduced significantly.In addition,the algorithm has better performance in the identification of missing tags in specific groups.