Dr. D. Y.
Patil Educational Federation’s
DR. D. Y. PATIL COLLEGE OF ENGINEERINGAND INNOVATION
Department of Artificial Intelligence and Data Science
Paper Title “An Android towards Women’s Safety”
Presented By
Varun Bhagwat [S401230280]
Pratik Ahire [S401230275]
Om Dange [S401230287]
Gaurav Pawar 1 [S401230329]
Harshal Ahire [S401230274]
Under the Guidance
Mr. Aashutosh Chandgude
Department of Artificial Intelligence and Data Science 1
Varale, Talegaon, Pune
Outline
Introduction
Research Gap Identification
Literature Survey
Problem Statement
Aim, Motivation and Objectives
Methodology ( Proposed system architecture, module names, algorithms)
Future Scope
Conclusion 2
References
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Introduction
Women’s safety has become a critical concern, especially in
urban areas where cases of harassment and assault are rising.
Traditional safety methods often lack timely response,
highlighting the need for tech-driven solutions. This project
proposes an Android-based Women Safety App that sends
emergency alerts via SMS and GPS, triggered by gestures
like phone shaking. It also offers access to medical, legal,
and psychological support, and uses AI with crowd-sourced
data to identify unsafe zones. The app aims to provide real-
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time help while promoting long-term safety and
empowerment.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Research Gap Identification
Study/Source Research Gaps
Identified Gaps in Existing Women Safety S.No. App Name
(Author Year)
Key Features
Identified
Solutions Doria et al.
Location-based Limited
safety audits, integration with
• Limited Functionality 1 MySafetyPin (2021) personal alarms, emergency
ResearchGate crowd-sourced services; lacks
Most applications are restricted to basic features such as panic scoring real-time alerts.
buttons or location tracking, without offering complete Does not offer
Location-based
support systems. Doria et al.
services, personal
direct
2 Saven (2021) communication
• Lack of Integrated Support Services alarms, crowd-
ResearchGate with authorities;
sourced data
There is no unified platform that combines legal aid, medical no AI detection.
Location-based
support, and psychological counseling within a single app. Doria et al. alerts, panic
Limited
customization;
• Absence of Smart Emergency Triggers 3 My Keeper (2021) button, crowd-
lacks healthcare
ResearchGate sourced hazard
Very few solutions implement features like shake detection integration.
mapping
for hands-free emergency alerts. Doria et al.
Self-defence tips, No real-time
Women Safety safety alerting; missing
• Inadequate Use of Data and AI 4 (2021)
Totem SOS information, legal support
ResearchGate
Existing apps do not effectively utilize crowd-sourced data or panic alerts features.
Six-friend
artificial intelligence to identify and flag high-risk areas. Blayney et al. network alerts, Low real-world
• Delayed Response Mechanisms 5 Circle of 6 (Co6) (2018) discreet icons, adoption; limited
JMU - JMIR mH GPS-enabled contexts for use.
Many systems do not provide real-time alert delivery, which ealth and uHealth help requests
limits their effectiveness during actual emergencies.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Literature Survey
•1.A Mobile-Based Women Safety Application” – International Journal of Computer Applications, 2016This paper
presents a mobile application that helps women in distress send their location to predefined contacts through a single
click. It uses GPS and SMS services. However, it lacks features like background services or shake/volume button
detection, making it less effective during sudden threats.
•2. “Smartphone Based Women Safety Application (I Safe)” – IJRASET, 2018The authors proposed an app that
sends an emergency alert using a button. Though user-friendly, the reliance on UI interaction makes it vulnerable in
real-time emergencies where accessing the screen is not possible.
3. “Android App for Women Safety” – International Journal of Engineering and Techniques, 2017This paper
discusses an app integrated with Google Maps to send a location to contacts and nearby police stations. However, the
system lacks stealth activation or background service, which is essential for real-time protection.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Problem Statement
The increasing incidence of crimes against women, including harassment, assault, and
stalking, has created a pressing need for real-time safety solutions. Traditional safety
measures, such as helplines and manual reporting systems, often fail to provide timely
assistance in critical situations. This gap between risk and response time highlights the
necessity for smarter, technology-driven safety interventions. Current mobile solutions
often lack comprehensive integration, offering only limited functionalities like panic
buttons or GPS tracking,
Our Women Safety Application aims to bridge this gap by providing instant emergency
alerts, location tracking, and integrated support services in a user-friendly and
responsive mobile platform.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Aim, Motivation and Objectives
• Aim
To develop a Women Safety Application that provides real-time emergency alerts, instant
location tracking, and access to medical, psychological, and emergency support services,
empowering women to feel safer in both public and private spaces.
• Motivation
The increasing frequency of crimes against women, including harassment, stalking, and
assault, has highlighted the need for quick, accessible, and technology-driven safety solutions.
Traditional methods like helplines are often inadequate when immediate action is needed. The
widespread availability of smartphones and internet connectivity presents an opportunity to
create a responsive, user-friendly safety app that 7 bridges the gap between incident
occurrence and timely help.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Aim, Motivation and Objectives
• Objectives
1. Develop a user-friendly application for real-time emergency alerts and assistance.
2. Integrate real-time GPS tracking to share location with trusted contacts during
emergencies.
3. Implement shake detection functionality for effortless activation of safety features.
4. Utilize AI and crowdsourced data to identify and map unsafe zones in real time,
contributing to safer urban environments.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Methodology
2. Key Modules
1. Development Tools & Technologies
• User Authentication Module – Secure login using
• Android Studio – App development username/password.
environment using Java. • Shake Detection Module – Detects distress signal via
accelerometer sensor.
• Firebase – Backend services for authentication • Emergency Alert Module – Sends SMS with location to pre-set
and real-time database. emergency contacts.
• Location Tracking Module – Uses Fused Location Provider for
• Google Maps API – Location tracking and map real-time positioning.
services. • Support Services Access – Provides emergency contact numbers
and helplines.
• Figma – Used for designing UI/UX prototypes.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Methodology
• Activity diagram of Signup! • Activity diagram of Login!
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Methodology
1. System Architecture
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Future Scope
•Integration with Wearable Devices • Parental Control Integration
Enable the app to function with smartwatches or fitness bands to
Add features that allow parents or guardians to monitor
trigger emergency alerts directly from the wearable without
key safety data such as real-time location, alert history, and
accessing the phone.
battery status of the user’s device.
•AI-Based Unsafe Zone Detection
Option to receive notifications if the app is deactivated or if
Use artificial intelligence and machine learning algorithms to
analyze real-time data (e.g., crowd reports, time of day, past the user enters a predefined unsafe zone.
incidents) and proactively warn users about potentially unsafe areas.
•Audio/Video Evidence Capture
Future updates may include features to automatically start
audio/video recording during an emergency, which can serve as
crucial evidence if needed.
•Cloud Backup and Sync
Add cloud-based user data backup, allowing emergency contacts
and preferences to be restored across devices.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
Conclusion
The development of the Women Safety Application addresses a critical need for real-time, accessible, and
technology-driven safety solutions. By leveraging mobile technology, GPS tracking, and shake-triggered
emergency alerts, the app empowers women to act swiftly in distress situations. Its simple and responsive
interface ensures usability even under stress, while features like location sharing and emergency SMS offer
immediate support.
Although the app currently focuses on emergency alerts, psychological support, and location tracking, its
future potential lies in integrating advanced capabilities like wearable device support, AI-driven unsafe
zone prediction, and parental monitoring tools.
This project is a step toward creating safer environments and giving women greater freedom of
movement, confidence, and autonomy—anytime, anywhere.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
References
• [1] S. Gupta, S. Ranjan, and S. Kumar, "Research Paper on Women Safety System," International Journal for Research in
Applied Science and Engineering Technology (IJRASET), vol. 12, no. 5, pp. 191–195, May 2024.
• [2] P. Y. Gonde and P. B. Ghewari, "Women Safety System using Raspberry Pi," International Research Journal of Engineering
and Technology (IRJET), vol. 8, no. 1, pp. 134–142, Jan. 2021.
• [3] G. V. Gouripriya, N. Paul, and A. K. R., "Are Women Safe in Public Places in India? To Study and Analyze Women's Fear and
Perception of Men," International Journal of Engineering Research & Technology (IJERT), vol. 10, no. 11, pp. 1–5, Nov. 2022
• [4] S. M. Shaikh, "Women's Safety in India: Issues and Challenges," International Journal of Advanced Research in Engineering
Science and Management (IJARESM), vol. 10, no. 6, Jul. 2023.
• [5] S. Shanbhagam, P. Praveen Kumar, T. S. Ganesh, T. C. Prabhath, and V. S. Nayak, "Analysis of Women Safety in Indian Cities
Using Machine Learning on Tweets," International Journal of. Mechanical Engineering Research and Technology (IJMERT),
vol. 16, no. 2, pp. 147–153, Apr2024.
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Varale, Talegaon, Pune Department of Artificial Intelligence and Data Science
