Crowd monitoring with alerting system

The goal of this work is to explain a crowd management system that uses Raspberry Pi technology integrated with GSM and YOLOv8. This system is essential for monitoring and confronting violent behavior inside a group of people. The most recent recognized model, YOLOv8, which has a high degree of accuracy, potentially high detection speed, and low latency, is utilized by the design. Users are provided with a gateway that allows them to set boundaries and view real-time crowd activity monitoring. GSM was used to send warnings for every violent occurrence that was found. Advanced communication technologies and detection are used in the rapid and economical system solutions. The projected crowd administration scheme influences progressive electronics like Raspberry Pi, GSM, and YOLOv8 to monitor and control big crowds, specifically in surroundings place extreme action concede possibility happen. The system aims to discover, path, and put oneself in the place of another occurrence of attitude in certain-opportunity, guaranteeing improved security honestly rooms in the way that stadiums, concerts, or protests. At the center of bureaucracy is the YOLOv8 (You Only Look Once report 8) model, a newfangled object discovery invention famous for allure extreme veracity, speedy discovery speed, and reduced abeyance. YOLOv8 is particularly created to perceive and path things or groups of nation inside a crowd, recognizing severe conduct like fights, hostile gestures, or different campaigns. Its skill to process broadcast feeds from cameras attributed to a Raspberry Pi guarantees honest-period study and operation. Raspberry Pi serves as the alter center, merging accompanying cameras to capture live movie of the crowd. It acts as a cheap, adept resolution to act the difficult computational tasks wanted for object discovery. The system admits controllers to set predefined frontiers or zones inside the crowd, taking alerts when powerful act crosses these limits. Additionally, GSM (Global System for Mobile Communications) electronics is organized to please mechanical warnings to appropriate experts or crew when destructive performance is discovered. These warnings are shipped by way of manual ideas, permissive accelerated reaction to occurrence and guaranteeing unexpected mediation. Combining cheap fittings accompanying progressive discovery and ideas electronics, this crowd administration whole offers an effective, ascendable, and inexpensive answer for asserting public security.

Authors

Publication Details

Journal
International Journal of Computing and Artificial Intelligence
Published
2025-01-01
DOI
https://doi.org/10.33545/27076571.2025.v6.i1b.140
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Crowd monitoring with alerting system

Bhushan Rajani, Sachin Choudhari, Mayank Sahajramani, Nikhil Nanwani et al.
International Journal of Computing and Artificial Intelligence
Evacuation and Crowd Dynamics
article

Crowd monitoring with alerting system

Bhushan Rajani, Sachin Choudhari, Mayank Sahajramani, Nikhil Nanwani, Sujal Nawani, Sujal Bhojwani
article en

Abstract

The goal of this work is to explain a crowd management system that uses Raspberry Pi technology integrated with GSM and YOLOv8. This system is essential for monitoring and confronting violent behavior inside a group of people. The most recent recognized model, YOLOv8, which has a high degree of accuracy, potentially high detection speed, and low latency, is utilized by the design. Users are provided with a gateway that allows them to set boundaries and view real-time crowd activity monitoring. GSM was used to send warnings for every violent occurrence that was found. Advanced communication technologies and detection are used in the rapid and economical system solutions. The projected crowd administration scheme influences progressive electronics like Raspberry Pi, GSM, and YOLOv8 to monitor and control big crowds, specifically in surroundings place extreme action concede possibility happen. The system aims to discover, path, and put oneself in the place of another occurrence of attitude in certain-opportunity, guaranteeing improved security honestly rooms in the way that stadiums, concerts, or protests. At the center of bureaucracy is the YOLOv8 (You Only Look Once report 8) model, a newfangled object discovery invention famous for allure extreme veracity, speedy discovery speed, and reduced abeyance. YOLOv8 is particularly created to perceive and path things or groups of nation inside a crowd, recognizing severe conduct like fights, hostile gestures, or different campaigns. Its skill to process broadcast feeds from cameras attributed to a Raspberry Pi guarantees honest-period study and operation. Raspberry Pi serves as the alter center, merging accompanying cameras to capture live movie of the crowd. It acts as a cheap, adept resolution to act the difficult computational tasks wanted for object discovery. The system admits controllers to set predefined frontiers or zones inside the crowd, taking alerts when powerful act crosses these limits. Additionally, GSM (Global System for Mobile Communications) electronics is organized to please mechanical warnings to appropriate experts or crew when destructive performance is discovered. These warnings are shipped by way of manual ideas, permissive accelerated reaction to occurrence and guaranteeing unexpected mediation. Combining cheap fittings accompanying progressive discovery and ideas electronics, this crowd administration whole offers an effective, ascendable, and inexpensive answer for asserting public security.

International Journal of Computing and Artificial IntelligenceVol. 6(1)
Openalex Percentile: Top 90%
Evacuation and Crowd Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.