Iot-Enabled Autonomous Night Patrolling Robot For Enhanced Women's Safety In Urban Environments

Women’s safety remains one of the most pressing concerns in modern society, especially during nighttime in isolated or poorly monitored areas. Traditional security systems rely heavily on human patrol officers, CCTV surveillance, and emergency helplines, all of which suffer from limitations such as delayed response, limited coverage, and lack of real-time intervention. To address these challenges, this research proposes an IoTenabled autonomous night patrolling robot designed specifically to enhance women’s safety through intelligent surveillance, threat detection, and instant communication features. The robot is equipped with sensors such as PIR motion detectors, GPS, ultrasonic sensors, and a camera module capable of real-time video streaming. The system leverages IoT connectivity for remote monitoring and emergency alerts, ensuring that suspicious activities are immediately detected and reported. Using machine learning–based facial recognition and audio anomaly detection, the robot can identify potential threats and trigger automated responses. The robot navigates autonomously using path-planning algorithms while avoiding obstacles, enabling continuous monitoring of dark or restricted pathways. The proposed system is cost-effective, scalable, and suitable for deployment in campuses, residential societies, public parks, and urban streets. By integrating surveillance, communication, and automation, the robot strengthens prevention and rapid response capabilities, contributing to a safer environment for women at night.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-31
DOI
https://doi.org/10.5281/zenodo.19357348
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Iot-Enabled Autonomous Night Patrolling Robot For Enhanced Women's Safety In Urban Environments

IJAENE
Zenodo (CERN European Organization for Nuclear Research)
IoT and GPS-based Vehicle Safety Systems
article

Iot-Enabled Autonomous Night Patrolling Robot For Enhanced Women's Safety In Urban Environments

IJAENE
article en

Abstract

Women’s safety remains one of the most pressing concerns in modern society, especially during nighttime in isolated or poorly monitored areas. Traditional security systems rely heavily on human patrol officers, CCTV surveillance, and emergency helplines, all of which suffer from limitations such as delayed response, limited coverage, and lack of real-time intervention. To address these challenges, this research proposes an IoTenabled autonomous night patrolling robot designed specifically to enhance women’s safety through intelligent surveillance, threat detection, and instant communication features. The robot is equipped with sensors such as PIR motion detectors, GPS, ultrasonic sensors, and a camera module capable of real-time video streaming. The system leverages IoT connectivity for remote monitoring and emergency alerts, ensuring that suspicious activities are immediately detected and reported. Using machine learning–based facial recognition and audio anomaly detection, the robot can identify potential threats and trigger automated responses. The robot navigates autonomously using path-planning algorithms while avoiding obstacles, enabling continuous monitoring of dark or restricted pathways. The proposed system is cost-effective, scalable, and suitable for deployment in campuses, residential societies, public parks, and urban streets. By integrating surveillance, communication, and automation, the robot strengthens prevention and rapid response capabilities, contributing to a safer environment for women at night.

Zenodo (CERN European Organization for Nuclear Research)
Gender equality
Openalex Percentile: Top 7%
IoT and GPS-based Vehicle Safety Systems
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.