Pedestrian walking safety system based on smartphone built-in sensors

被引:18
|
作者
Li, Yantao [1 ,2 ,3 ]
Xue, Fengtao [1 ]
Fan, Xinqi [1 ]
Qu, Zehui [1 ]
Zhou, Gang [2 ]
机构
[1] Southwest Univ, Coll Comp & Informat Sci, Chongqing 400715, Peoples R China
[2] Coll William & Mary, Dept Comp Sci, Williamsburg, VA 23185 USA
[3] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210023, Jiangsu, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
pedestrians; safety; smart phones; Android (operating system); accelerometers; object detection; pedestrian walking safety system; smartphone built-in sensors; smartphone screens; smartphone usage; Android smartphone-based system; walking behaviour; pedestrian speed calculation algorithm; acceleration data; accelerometer; gravity components; greyscale image detection algorithm; OpenCV4Android;
D O I
10.1049/iet-com.2017.0502
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
People watching smartphones while walking causes a significant impact to their safety. Pedestrians staring at smartphone screens while walking along the sidewalk are generally more at risk than other pedestrians not engaged in smartphone usage. In this study, the authors propose Safe Walking, an Android smartphone-based system that detects the walking behaviour of pedestrians by leveraging the sensors and front camera on smartphones, improving the safety of pedestrians staring at smartphone screens. More specifically, Safe Walking first exploits a pedestrian speed calculation algorithm by sampling acceleration data via the accelerometer and calculating gravity components via the gravity sensor. Then, this system utilises a greyscale image detection algorithm to detect the face and eye movement modes based on OpenCV4Android to determine if pedestrians are staring at the screens. Finally, Safe Walking generates a vibration by a vibrator on smartphones to alert pedestrians to pay attention to road conditions. The authors implemented Safe Walking on an Android smartphone and evaluated pedestrian walking speed, the accuracy of eye movement, and system performance. The results show that Safe Walking can prevent the potential danger for pedestrians staring at smartphone screens with a true positive rate of 91%.
引用
收藏
页码:751 / 758
页数:8
相关论文
共 50 条
  • [1] An improved pedestrian dead reckoning algorithm based on smartphone built-in MEMS sensors
    Zhao, Guiling
    Wang, Xu
    Zhao, Hongxing
    Jiang, Zihao
    [J]. AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 2023, 168
  • [2] A Pedestrian Safe Walking Detection System based on Smartphone Sensors
    Xue, Fengtao
    Hu, Hailong
    Yan, Gaoliang
    Li, Yantao
    [J]. PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON MECHATRONICS ENGINEERING AND INFORMATION TECHNOLOGY (ICMEIT 2017), 2017, 70 : 581 - 584
  • [3] Cryptographic Key Generator Candidates based on Smartphone built-in Sensors
    Marghescu, Andrei
    Teseleanu, George
    Svasta, Paul
    [J]. 2014 IEEE 20TH INTERNATIONAL SYMPOSIUM FOR DESIGN AND TECHNOLOGY IN ELECTRONIC PACKAGING (SIITME), 2014, : 239 - 243
  • [4] Smartphone built-in sensors based vehicle integrated positioning method
    Kuang, Jian
    Ge, Wenfei
    Zhang, Quan
    Dou, Zhi
    Tang, Aipeng
    Zhang, Xiaobing
    Niu, Xiaoji
    [J]. Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology, 2020, 28 (06): : 701 - 708
  • [5] Acoustic Imaging Using the Built-In Sensors of a Smartphone
    Li, Chenming
    Wang, Junchao
    Ding, Xinyi
    Zhang, Naiyin
    [J]. SYMMETRY-BASEL, 2021, 13 (06):
  • [6] Method of Pedestrian's Behavior Recognition Based on Built-in Sensor of Smartphone in Compartment Fires
    Chen, Guoliang
    Cao, Xiaoxiang
    [J]. Tongji Daxue Xuebao/Journal of Tongji University, 2019, 47 (03): : 414 - 420
  • [7] A Smartphone-Based System for Improving Pedestrian Safety
    Xia, Stephen
    de Godoy, Daniel
    Islam, Bashima
    Islam, Md Tamzeed
    Nirjon, Shahriar
    Kinget, Peter R.
    Jiang, Xiaofan
    [J]. 2018 IEEE VEHICULAR NETWORKING CONFERENCE (VNC), 2018,
  • [8] Converting context to indoor position using built-in smartphone sensors
    Khalifa, Sara
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS), 2013, : 423 - 424
  • [9] Evaluating data accuracy of built-in smartphone sensors for mobile applications
    Fanca, Alexandra
    Puscasiu, Adela
    Gota, Dan-Ioan
    Valean, Honoriu
    [J]. 2018 26TH TELECOMMUNICATIONS FORUM (TELFOR), 2018, : 879 - 882
  • [10] Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone
    He, Yi
    Li, Ye
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2013,