Radio Frequency Identification (RFID), as typical information carrier in Internet of Things, is widely applied in advanced manufacture, logistics management and identification. However, according to the complex environment of practical applications, there are many challenges in the deployment of large-scale RFID application. The RFID system optimization is one of the important topics in the deployment of RFID applications, which aims to solve the low read rate problem in RFID applications, especially in the applications which need to identify multiple objects simultaneously. Firstly, by using a scene of portal RFID application, a novel method of modeling the RFID system in the context of multi-object identification under the application constraints is put forward. Different from the RFID benchmarking test, in the proposed method, all the complex effects of the environment factors are treated as the disturbance of the RFID system, then Support Vector Machine (SVM) is employed to learn the model of multi-object identification RFID system. The proposed method can build a performance prediction model by using as less RFID data as possible. And the model built above can bring high accurate prediction data under a range of disturbance, which gives the theoretical support for the optimization of RFID system in real applications. Secondly, a Mixture-Reality (MR) RFID simulation system based on the learnt RFID model is contributed. This simulation system can substitute the real RFID system to be used for designing the deployment of the real RFID application system, as well as for testing the reliability of the RFID application software system. The simulating method learns the model online. It can achieve 90% prediction accuracy with 90% reduction in both time and storage space compared with the test performance of system with real hardware and environment. It provides technical support to enhance the efficiency of RFID system deployment in real applications. Thirdly, this paper applies the RFID model learnt above to the multi-antenna placement of the RFID system. A redundancy antenna placement method based on genetic algorithm (GA) is proposed, which is used to optimize the read range of the RFID antennas. In this algorithm we use the prediction results of learnt model as the fitness of the individual, and optimize the search-space using heuristic search method. Then the designed GA is applied to optimize the RFID portal system with three reader antennas. C...
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