A novel RFID multi-tag anti-collision protocol for dynamic vehicle identification

Abstract

In order to obtain the information of the vehicle tags in adverse traffic conditions, we proposed a novel reservation framework named reservation to cancel idle-dynamic frame slotted ALOHA (RTCI-DFSA) algorithm. Firstly, the framework employed reservation mechanism to remove idle slot, and thus improve the system identification efficiency. Secondly, the vehicle information was identified by the tag serialization polling identification method. The experimental results showed that the proposed RTCI-DFSA algorithm performed better than the traditional frame slotted ALOHA (FSA) and dynamic frame slotted ALOHA (DFSA) algorithms. More specifically, the tag loss rate of the proposed framework is significantly lower than the frame length fixed and conventional dynamic vehicle identification algorithms. In addition, the experimental results demonstrated that the throughput rate of the proposed algorithm increased from 0.368 to 0.6. Besides, the identification efficiency and applicability of the proposed framework were both higher than other tag identification algorithms.

Availability of an RFID Object-Identification System in IoT Environments

“…At the same time, the probabilities associated with multiframe detection increase significantly, denoting a greater impact of two- and three-frame detection, respectively. Compared to other studies [ 18 , 19 , 20 , 21 ], we proved that an FSA anticollision algorithm achieving maximal throughput (i.e., each frame slot occupied by a single tag) has a low probability.…”

“…As the inquiry frame has L = 16 slots, the probability that a RFID tag selects a slot is equal to [ 18 , 20 ]. The probability that a slot is selected by multiple RFID tags is described through the following binomial distribution [ 18 , 28 ]: where represents the total number of tags in the range of the RFID reader, and represents the number of tags that select a slot for transmitting their UID.…”

“…By introducing the cost function, this process becomes identifying the lowest cost that has the highest possible associated occurrence probability. Having the number of tags equal to the number of slots in a frame yields the highest throughput (i.e., the smallest cost) if all tags are read in one frame [ 18 , 20 , 28 ]. As Section 3 shows, such a scenario has a small probability of occurrence, but there is also large variation in the time needed to identify all tags in the system.…”

“…There are studies in the literature that analyze identifying objects through RFID technology, but they focus on determining the maximal throughput that can be obtained on the basis of the number of slots present in a query frame and the number of tags present within the range of the RFID reader’s antenna [ 18 , 19 , 20 , 21 ]. Depending on the type of analysis, throughput can be either the number of queries per second or the number of tags identified in an amount of time.…”

Vehicle detection and tracking based on UAV

“…In terms of vehicle detection, Qu, Z., et al [4] . Factors affecting the efficiency of tagging recognition are studied and a new algorithm (RTCI-DFS algorithm) for vehicle recognition is therefore proposed accelerating the communication between tags and readers.…”