Design And Implementation Of ZigBee Positioning System In Smart Home

With the rapid development of ZigBee technology,the intelligent housing system gets a more broad application.People's demand for the intelligent housing indoor positioning services is also increasing day by day.Due to the complex indoor environment,outdoor positioning technolog y,such as Beidou and GPS,is difficult to meet the requirements of indoor positioning.The conventional positioning technology using infrared,ultrasonic and Wi-Fi has technical defects or high development costs,leading to the failure of popularization a nd application.For this purpose,it is very meaningful to design a positioning system suitable for indoor positioning environment with high positioning accuracy.Aiming at the problems of traditional indoor location algorithm,such as low positional accuracy and big position error,fingerprint localization algorithm was supposed basing on BP neural network.The theory of multi-pattern set and BP neural network was used to improve the localization accuracy of the algorithm.The improved algorithm is proved to have higher positioning accuracy compared with the traditional fingerprint localization algorithm through MATLAB simulation experiment.The indoor positioning system with CC2530 microprocessor as the core was designed.The corresponding assistant commu nication module was carried upon different communication node on the basis of its function.To realize the efficient and orderly communication among the modules in the whole system,a unified communication protocol was designed for exchanging data orderly and efficiently.The upper computer monitoring software of the positioning system was developed using LabVIEW 2016 platform.The data packet loss rate and the effect of obstacles on the positioning accuracy of the localization node were tested.The result showed that data packet transmission would not be lost within the range of 20 m in the case of communication nodes with and without obstacle s.The packet loss rate increased with obstacles outside the range of 20 m,and obstacles also reduced the positioning accuracy of the system.In order to verify the stability and reliability of the positioning system,the positioning system designed was tested in a practical environment of 12m×11.5m.The results showed that the average error of the traditional fingerpr int database localization algorithm was 2.03 m,meanwhile,the average error of the improved localization algorithm was about 0.984 m.The BP neural network fingerprint localization algorithm has the advantages of small error and high accuracy,and the designed localization system can run stably for a long time.The positioning system studied in this paper achieved the expected research purpose.It can meet the needs of indoor positioning well and realize the precise positioning function of nodes in th e intelligent housing.It's a system that has low cost,low power consumption,and is easy to achieve.Figure[43]table[7]reference[58]...