Home / Journals / JAI / Vol.1, No.1, 2019
  • Open Access

    ARTICLE

    Intelligent Mobile Drone System Based on Real-Time Object Detection

    Chuanlong Li1,2, Xingming Sun1,2,*, Junhao Cai3,*
    Journal on Artificial Intelligence, Vol.1, No.1, pp. 1-8, 2019, DOI:10.32604/jai.2019.06064
    Abstract Drone also known as unmanned aerial vehicle (UAV) has drawn lots of attention in recent years. Quadcopter as one of the most popular drones has great potential in both industrial and academic fields. Quadcopter drones are capable of taking off vertically and flying towards any direction. Traditional researches of drones mainly focus on their mechanical structures and movement control. The aircraft movement is usually controlled by a remote controller manually or the trajectory is pre-programmed with specific algorithms. Consumer drones typically use mobile device together with remote controllers to realize flight control and video transmission. Implementing different functions on mobile… More >

  • Open Access

    ARTICLE

    Underground Disease Detection Based on Cloud Computing and Attention Region Neural Network

    Pinjie Xu2, Ce Li1,2,*, Liguo Zhang3,4, Feng Yang1,2, Jing Zheng1,5, Jingwu Feng2
    Journal on Artificial Intelligence, Vol.1, No.1, pp. 9-18, 2019, DOI:10.32604/jai.2019.06157
    Abstract Detecting the underground disease is very crucial for the roadbed health monitoring and maintenance of transport facilities, since it is very closely related to the structural health and reliability with the rapid development of road traffic. Ground penetrating radar (GPR) is widely used to detect road and underground diseases. However, it is still a challenging task due to data access anywhere, transmission security and data processing on cloud. Cloud computing can provide scalable and powerful technologies for large-scale storage, processing and dissemination of GPR data. Combined with cloud computing and radar detection technology, it is possible to locate the underground… More >

  • Open Access

    ARTICLE

    Remaining Useful Life Prediction of Rolling Bearings Based on Recurrent Neural Network

    Yimeng Zhai1, Aidong Deng1,*, Jing Li1,2, Qiang Cheng1, Wei Ren3
    Journal on Artificial Intelligence, Vol.1, No.1, pp. 19-27, 2019, DOI:10.32604/jai.2019.05817
    Abstract In order to acquire the degradation state of rolling bearings and achieve predictive maintenance, this paper proposed a novel Remaining Useful Life (RUL) prediction of rolling bearings based on Long Short Term Memory (LSTM) neural net-work. The method is divided into two parts: feature extraction and RUL prediction. Firstly, a large number of features are extracted from the original vibration signal. After correlation analysis, the features that can better reflect the degradation trend of rolling bearings are selected as input of prediction model. In the part of RUL prediction, LSTM that making full use of the network’s memory in time… More >

  • Open Access

    ARTICLE

    Ship Trajectory Prediction Based on BP Neural Network

    Hai Zhou1,2,*, Yaojie Chen1,2, Sumin Zhang3
    Journal on Artificial Intelligence, Vol.1, No.1, pp. 29-36, 2019, DOI:10.32604/jai.2019.05939
    Abstract In recent years, with the prosperity of world trade, the water transport industry has developed rapidly, the number of ships has surged, and ship safety accidents in busy waters and complex waterways have become more frequent. Predicting the movement of the ship and analyzing the trajectory of the ship are of great significance for improving the safety level of the ship. Aiming at the multi-dimensional characteristics of ship navigation behavior and the accuracy and real-time requirements of ship traffic service system for ship trajectory prediction, a ship navigation trajectory prediction method combining ship automatic identification system information and Back Propagation… More >

  • Open Access

    ARTICLE

    Research on Robot Control Technology Based on Vision Localization

    Ruijiao Yin1, Jie Yang1,*
    Journal on Artificial Intelligence, Vol.1, No.1, pp. 37-44, 2019, DOI:10.32604/jai.2019.05815
    Abstract Based on the understanding of machine vision localization technology at home and abroad, this paper outlines the overall design of the system, and analyses the working principle and workflow of the robot with vision system in workpiece grinding. The hardware design of the system is introduced. The process of image processing is analyzed in detail, and the results of image processing are given. The basic parameters of camera imaging are taken as internal parameters. The camera calibration is obtained by rotation matrix R and translation parameter T. The coordinate transformation of camera coordinate system and world coordinate system is analyzed.… More >

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