Ai-Driven Video Surveillance for Safety Using Yolo with Iot Integration and Intelligent Alerts

The operational role of ensuring safety in dynamic and high-risk scenarios is an important task in the area of security threats or emergencies, particularly in areas with high risk of human crime. The proposed system for surveillance uses AI-based and Internet of Things (IoT) technologies to continuously monitor human behaviors through camera and sensor networks and uses it for detection of dangerous objects and recognition of aggressive or hostile physical behavior normally associated with violent confrontation or security risk. Thus the solution can be automatically designed to address threats promptly. One of the main functionality of this system is the application of a high-performance object detection model with high accuracy and low latency processing live video data. The training process has been carried out on this model to reliably detect unsafe objects and suspicious human behavior. These traits help to make immediate threat identification easy. When detecting danger, the system automatically initiates a multitiered emergency response strategy including alarming the situation and sending instantaneous alerts to designated security officials. The solution also uses IoT-based devices such as smart sirens that emit high-pitched auditory signals to alert surrounding people to possible danger. A specific novel feature in the proposed system is its dual-alert mechanism whereby auditory signals are deployed simultaneously at the incident site and at a second remote monitoring station. This way security personnel are better aware of the situation and reduced response time. To extend emergency preparedness, the system also enables automated email notifications to designated medical emergency responders, including ambulance services.

Authors

Institutions

Publication Details

Published
2025-04-17
DOI
https://doi.org/10.1109/icdsbs63635.2025.11031601
Primary Topic
Video Surveillance and Tracking Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ai-Driven Video Surveillance for Safety Using Yolo with Iot Integration and Intelligent Alerts

S. Latha, Asan Saheb Fasiha, M Janusri
Video Surveillance and Tracking Methods
article

Ai-Driven Video Surveillance for Safety Using Yolo with Iot Integration and Intelligent Alerts

S. Latha, Asan Saheb Fasiha, M Janusri
article en

Abstract

The operational role of ensuring safety in dynamic and high-risk scenarios is an important task in the area of security threats or emergencies, particularly in areas with high risk of human crime. The proposed system for surveillance uses AI-based and Internet of Things (IoT) technologies to continuously monitor human behaviors through camera and sensor networks and uses it for detection of dangerous objects and recognition of aggressive or hostile physical behavior normally associated with violent confrontation or security risk. Thus the solution can be automatically designed to address threats promptly. One of the main functionality of this system is the application of a high-performance object detection model with high accuracy and low latency processing live video data. The training process has been carried out on this model to reliably detect unsafe objects and suspicious human behavior. These traits help to make immediate threat identification easy. When detecting danger, the system automatically initiates a multitiered emergency response strategy including alarming the situation and sending instantaneous alerts to designated security officials. The solution also uses IoT-based devices such as smart sirens that emit high-pitched auditory signals to alert surrounding people to possible danger. A specific novel feature in the proposed system is its dual-alert mechanism whereby auditory signals are deployed simultaneously at the incident site and at a second remote monitoring station. This way security personnel are better aware of the situation and reduced response time. To extend emergency preparedness, the system also enables automated email notifications to designated medical emergency responders, including ambulance services.

B.S. Abdur Rahman Crescent Institute of Science & Technology (IN)
Openalex Percentile: Top 88%
Video Surveillance and Tracking Methods
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.

Ai-Driven Video Surveillance for Safety Using Yolo with Iot Integration and Intelligent Alerts — S. Latha, Asan Saheb Fasiha, et al. · (2025) | TGRS Research Map | TGRS