Intelligent Environmental Monitoring System Based on Multi-Sensor Data Technology

被引:6
|
作者
Liu, Qiuxia [1 ]
机构
[1] Heze Univ, Heze, Peoples R China
关键词
Algorithm; Data Fusion; DS Evidence Theory; Environmental Parameters; Wireless Transmission;
D O I
10.4018/IJACI.2020100104
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Using multi-sensor data fusion technology, ARM technology, ZigBee technology, GPRS, and other technologies, an intelligent environmental monitoring system is studied and developed. The SCM STC12C5A60S2 is used to collect the main environmental parameters in real time intelligently. The collected data is transmitted to the central controller LPC2138 through the ZigBee module ATZGB-780S5, and then the collected data is transmitted to the management computer through the GPRS communication module SIM300; thus, the real-time processing and intelligent monitoring of the environmental parameters are realized. The structure of the system is optimized; the suitable fusion model of environmental monitoring parameters is established; the hardware and the software of the intelligent system are completed. Each sensor is set up synchronously at the end of environmental parameter acquisition. The method of different value detection is used to filter out different values. The authors obtain the reliability of the sensor through the application of the analytic hierarchy process. In the analysis and processing of parameters, they proposed a new data fusion algorithm by using the reliability, probability association algorithm, and evidence synthesis algorithm. Through this algorithm, the accuracy of environmental monitoring data and the accuracy of judging monitoring data are greatly improved.
引用
收藏
页码:57 / 71
页数:15
相关论文
共 50 条
  • [31] Personnel Identification and Intelligent Management System Based on Multi-sensor and Foxtable
    Qian, Chenghui
    Huang, Wanyu
    Liu, Xiyang
    Xin, Yusong
    2015 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, 2015, : 2542 - 2546
  • [32] An Intelligent Actuator of an Indoor Logistics System Based on Multi-Sensor Fusion
    Wang, Pangwei
    Wang, Yunfeng
    Wang, Xu
    Liu, Ying
    Zhang, Juan
    ACTUATORS, 2021, 10 (06)
  • [33] A Multi-Sensor Data Fusion System for Laser Welding Process Monitoring
    Deng, Fuqin
    Huang, Yongshen
    Lu, Song
    Chen, Yingying
    Chen, Jia
    Feng, Hua
    Zhang, Jianmin
    Yang, Yong
    Hu, Junjie
    Lam, Tin Lun
    Xia, Fengbin
    IEEE ACCESS, 2020, 8 : 147349 - 147357
  • [34] Information data flow in AWAKE multi-sensor driver monitoring system
    Polychronopoulos, A
    Amditis, A
    Bekiaris, E
    2004 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 2004, : 902 - 906
  • [35] Wind Turbine Condition Monitoring using Multi-Sensor Data System
    Abdulraheem, Khalid F.
    Al-Kindi, Ghassan
    INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH, 2018, 8 (01): : 15 - 25
  • [36] Wind turbine condition monitoring using multi-sensor data system
    Abdulraheem, Khalid F. (kabdulraheem@soharuni.edu.om), 2018, International Journal of Renewable Energy Research (08):
  • [37] STUDY ON MULTI-SENSOR DATA FUSION TECHNOLOGY FOR AUTOMOTIVE DRIVING SYSTEM
    Wang, Wei
    Shi, Hongbin
    Ogai, Harutoshi
    2011 3RD INTERNATIONAL CONFERENCE ON COMPUTER TECHNOLOGY AND DEVELOPMENT (ICCTD 2011), VOL 1, 2012, : 729 - 733
  • [38] Multi-sensor data fusion technology for the early landslide warning system
    Chen M.
    Cai Z.
    Zeng Y.
    Yu Y.
    Journal of Ambient Intelligence and Humanized Computing, 2023, 14 (08) : 11165 - 11172
  • [39] The Research of Multi-sensor Data Fusion Technology
    Jiao, Wen-cheng
    Han, Shuai
    Cui, Pei-zhang
    Wang, Xin
    INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE (AICS 2016), 2016, : 294 - 299
  • [40] Integrated multi-sensor and data compressing technology
    Li, MT
    Wu, YX
    Fu, WJ
    Ren, JH
    ICEMI'99: FOURTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 1999, : 447 - 451