Bigdata Enabled Realtime Crowd Surveillance Using Artificial Intelligence And Deep Learning

被引:4
|
作者
Rajendran, Logesh [1 ]
Shankaran, Shyam R. [1 ]
机构
[1] L&T Smart World, Chennai, Tamil Nadu, India
来源
2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2021) | 2021年
关键词
Al Based Surveillance; Crowd density; Crowd congestion detection; Crowd analysis; crowd counting; Deep learning;
D O I
10.1109/BigComp51126.2021.00032
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
India has in recent years witnessed significant tragedies related to crowds. Statistics indicate that over 70 per cent of Indian crowd-related accidents happened during religious festivities. A devastating humanitarian disaster may occur if crowd safety measures are not enforced and the massive crowds need to be given special attention. Manual crowd control requires extensive human intervention and is more vulnerable to human error and is a time-consuming activity too. In this paper we emphasize on L&T Smart World Al-based crowd management system implemented during the world's largest Kumbh Mela 2019 gathering in Prayagraj using Artificial Intelligence to solve circumstances that go beyond human capability. The data gathered provides the core for a framework for effective crowd management or evacuation strategies to minimize the risk of overwhelmed and dangerous conditions. Deep learning provides the solution to the dense crowd count and management problems. The crowd control analytics system of L&T Smart World has succeeded in maintaining the safety of 23 crore pilgrims visited during the 50 days of Holy Kumbh Mela in Prayagraj, India, demonstrates the efficacy of the solution implemented.
引用
收藏
页码:129 / 132
页数:4
相关论文
共 50 条
  • [21] Crowd aware summarization of surveillance videos by deep reinforcement learning
    Junfeng Xu
    Zhengxing Sun
    Chen Ma
    Multimedia Tools and Applications, 2021, 80 : 6121 - 6141
  • [22] Crowd aware summarization of surveillance videos by deep reinforcement learning
    Xu, Junfeng
    Sun, Zhengxing
    Ma, Chen
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (04) : 6121 - 6141
  • [23] SmartStim: An Artificial Intelligence Enabled Deep Brain Stimulation Device
    Corva, Dean M.
    Parke, Brenna
    West, Alyssa
    Doeven, Egan H.
    Adams, Scott D.
    Tye, Susannah J.
    Hashemi, Parastoo
    Berk, Michael
    Kouzani, Abbas Z.
    IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS, 2024, 6 (02): : 674 - 684
  • [24] A review of artificial intelligence based malware detection using deep learning
    Mustafa Majid A.-A.
    Alshaibi A.J.
    Kostyuchenko E.
    Shelupanov A.
    Materials Today: Proceedings, 2023, 80 : 2678 - 2683
  • [25] Artificial Intelligence using Deep Learning System for Glaucoma Suspect Detection
    Hamzah, Haslina
    Lim, Gilbert
    Quang Duc Nguyen
    Mani, Baskaran
    Hsu, Wynne
    Lee, Mong Li
    Cheng, Ching-Yu
    Wong, Tien Y.
    Ting, Daniel
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2018, 59 (09)
  • [26] Artificial Intelligence Shoe Cabinet Using Deep Learning for Smart Home
    Huh, Jun-Ho
    Seo, Kyungryong
    ADVANCED MULTIMEDIA AND UBIQUITOUS ENGINEERING, MUE/FUTURETECH 2018, 2019, 518 : 825 - 834
  • [27] The optimization of youth football training using deep learning and artificial intelligence
    Liao, Shaowei
    Fu, Chao
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [28] Smart surveillance system using Artificial Intelligence
    Budisteanu, Ionut Alexandru
    Stefanescu, Alin
    PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON VIRTUAL LEARNING, 2014, : 243 - 249
  • [29] Artificial intelligence based optimization with deep learning model for blockchain enabled intrusion detection in CPS environment
    Mansour, Romany F.
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [30] Artificial intelligence based optimization with deep learning model for blockchain enabled intrusion detection in CPS environment
    Romany F. Mansour
    Scientific Reports, 12