IJSMT Journal

International Journal of Science, Strategic Management and Technology

An International, Peer-Reviewed, Open Access Scholarly Journal Indexed in recognized academic databases · DOI via Crossref The journal adheres to established scholarly publishing, peer-review, and research ethics guidelines set by the UGC

ISSN: 3108-1762 (Online)
webp (1)

Plagiarism Passed
Peer reviewed
Open Access

AI-BASED CROWD PREDICTION SYSTEM

AUTHORS:
Lathika S
Mentor
I.Ajitha
Affiliation
Department of CT Dr.N.G.P Arts and Science College    Dr.N.G.P Arts and Science CollegeCoimbatoreCoimbatore
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

The AI Crowd Prediction System is designed to analyze crowd size and predict possible safety risks during events. The system allows users to enter event details such as expected crowd count, event type, and time slot to generate crowd density and risk predictions. It also supports image-based crowd estimation using computer vision techniques.Based on the crowd size, the system classifies the situation as Low, Medium, or High density and provides safety recommendations such as increasing security if needed. It also predicts short-term crowd movement trends and displays results using charts. All predictions are stored for future reference and analysis.This system helps in better event management, public safety monitoring, and decision-making

Keywords
Article Metrics
Article Views
23
PDF Downloads
1
HOW TO CITE
APA

MLA

Chicago

Copy

S, L. (2026). AI-Based Crowd Prediction System. International Journal of Science, Strategic Management and Technology, 02(03). https://doi.org/10.55041/ijsmt.v2i3.298

S, Lathika. "AI-Based Crowd Prediction System." International Journal of Science, Strategic Management and Technology, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i3.298.

S, Lathika. "AI-Based Crowd Prediction System." International Journal of Science, Strategic Management and Technology 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i3.298.

References
1.Viola, P., & Jones, M. (2001). Rapid Object Detection using a Boosted Cascade of Simple Features. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 511–518

2.Bradski, G., & Kaehler, (2008). Learning OpenCV: Computer Vision with the OpenCV Library. O'Reilly Media, USA.

3.Zhang, Y., Zhou, D., Chen, S., Gao, S., & Ma, Y. (2016). Single-Image Crowd Counting via Multi-Column Convolutional Neural Network. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

4.Li, , Zhang, X., & Chen, D. (2018). CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. IEEE Conference on Computer Vision and Pattern Recognition.

5.Redmon, , Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

6.Szeliski, (2010). Computer Vision: Algorithms and Applications. Springer Science & Business Media.

7.Rosebrock, (2017). Deep Learning for Computer Vision with Python. PyImageSearch Publications.

8.McKinney, (2012). Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. O'Reilly Media.

9.Grinberg, (2018). Flask Web Development: Developing Web Applications with Python. O'Reilly Media.

10.SQLite Development         (2023).     SQLite    Documentation.      Retrieved           from https://www.sqlite.org

 
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
Indexed In
Similar Articles
Wildlife in Kabini National Park: Flora and Fauna Present in Kabini National Park
string(18) "Spandana Rameshwar" Rameshwar, S.et al.
(2026)
DOI: 10.55041/ijsmt.v2i3.342
Strengthening India’s GI Ecosystem in the E-Commerce Era: Opportunities for Innovation and Inclusive Development
string(13) "Ankita Kumari" Kumari, A.
(2026)
DOI: 10.55041/ijsmt.v2i3.334
Stegovaultpro: Secure Multi-Format Steganography for Confidential Data Hiding
string(19) "Sarjun Chanakya S.K" S.K, S. C.
(2026)
DOI: 10.55041/ijsmt.v2i3.088
Scroll to Top