The Research On Estimating The Number Of Tags Of Radio Frequency Identification In Inventory Management

As a kind of automatic identification technology, Radio FrequencyIdentification (RFID) has been widely employed in so many areas such asinventory management, logistics transportation, traffic monitoring, assetstracking and so on. RFID can read many objects with high speed at the sametime, and can be quickly recognized with no obstacle. It also has thecharacteristics of a large capacity of data. When used RFID into inventorymanagement, it can obtain data automatically, and improve its process, as aresult, the efficiency of inventory management has been greatly improved. Afterthe goods into the warehouse, monitoring and management of goods ininventory management is a problem to be solved. Due to the large number andmess kinds of goods, the company can decide whether or not replenish theirstocks according to the number of existing goods. So companies need to keepabreast of the situation in stock goods, then to facilitate the management.In large RFID systems, there are a lot of works that have been focused onestimating the number of tags. However, these methods are only consideredtime-efficiency, that is to say, the less time it takes during the process ofestimation under the condition of the precision given by user, the better. Butwhen the active tags are used in modern inventory management, the energy isalso an important indicator. The prior works do not take energy consumption into account, so the energy consumed by each tag differs far one by one,resulting to shorten the life of the system. Thus, an approach that balance theenergy consumed by each tag is very important in warehouse management.In this paper, we propose an algorithm of energy balance estimation (EBE)based on active RFID system according to actual need of inventory management.This algorithm consists of two phases—an initialization phase and an iterativephase. When the estimated result satisfies the accuracy requirement, we reducethe responses of the tags as much as possible and make the responses of everytag reach an average level. Through the theoretical analysis and simulationresults, we can draw the conclusion that EBE has reached our respected effect inthe respect of energy balance. Finally, we analyze the shortcoming of EBE, andput forward an algorithm of generalized energy balance estimation (GEBE)based on EBE. GEBE increase the number of slots in a frame, thus it effectivelyavoid the conflict of tags and make greater progress in saving energy. Simulationresults also show its superiority.