Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

Designing of Environmental Information Acquisition and Reconstruction System Based on Compressed Sensing

  • @INPROCEEDINGS{10.1007/978-3-030-00557-3_58,
        author={Qiuming Zhao and Bo Li and Hongjuan Yang and Gongliang Liu and Ruofei Ma},
        title={Designing of Environmental Information Acquisition and Reconstruction System Based on Compressed Sensing},
        proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings},
        proceedings_a={MLICOM},
        year={2018},
        month={10},
        keywords={Compressed sensing Reconstruction Environmental information collection Visualization Orthogonal matching pursuit algorithm},
        doi={10.1007/978-3-030-00557-3_58}
    }
    
  • Qiuming Zhao
    Bo Li
    Hongjuan Yang
    Gongliang Liu
    Ruofei Ma
    Year: 2018
    Designing of Environmental Information Acquisition and Reconstruction System Based on Compressed Sensing
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-00557-3_58
Qiuming Zhao1,*, Bo Li1,*, Hongjuan Yang1,*, Gongliang Liu1,*, Ruofei Ma1,*
  • 1: Harbin Institute of Technology
*Contact email: qiumingzhaohit@163.com, libo1983@hit.edu.cn, hjyang@hit.edu.cn, liugl@hit.edu.cn, maruofei@hit.edu.cn

Abstract

At present, the collection of environmental information is mostly accomplished by sensors. In order to reduce the redundancy of sensor data collection, reduce the energy consumption of nodes, improve the service life of sensors and reduce the cost of the system, a system that combines compressed sensing reconstruction with sensors is proposed in this paper to collect and reconstruct environmental information. The designed system collects the environment information with a limited number of nodes. Compressed sensing reconstructs all the data of the required area through the optimized OMP algorithm. The final information is displayed by the software based on C# designing. The final result shows that the verification system proposed in this paper can realize the accurate reconstruction of the original environmental information, and it is effective to the collection and processing of complex environmental information.