IoT Based Automatic Women’s Safety Device for Enhanced Personal

Security

Arati Nilesh Kane

1,2

, Tabassum Maktum

, Vanita Mane

and Namita Pulgam

Ramrao Adik Institute of Technology, D Y Patil Deemed to be University, Navi Mumbai, India

Bharati Vidyapeeth’s Colleg of Engineering, New Delhi, India

Keywords:

IoT Technology, Women Safety Device, Raspberry Pi, Pulse Sensor, Temperature Sensor, Machine

Learning, GSM, Electric Shock.

Abstract:

Women’s security is a worldwide important concern in today’s scenario which needs urgent attention

of all the concerns of the society to provide enhanced safety to women. This paper

presents

development and deployment of automatically operated women safety

device based on IoT technology

with improved features meant for giving added layer of security and safety to women

. In this paper IoT

based device is developed with Raspberry pi technology. The automatic triggering of electric shock

mechanism is provided using machine learning algorithm for detecting emergency condition based on of

user’s body parameters. It sends message and current location to the registered contact number.

1 INTRODUCTION

Even in today’s scenario, women’s security is the

serious global concern which needs urgent attention.

The women are integral part of the society and for

the progress of the society active participation of

the women is necessary. Today women lead every

sector of the world including social, political,

economic and cultural. Although constitution

provides equal rights to women in society but

there is still discrepancy exist in the society. The

violence against women is increasing both in urban

and rural areas in every country across the globe.

per the report of WHO (World Health Organization)

30% women worldwide have faced the violence (UN

News, 2020). According to NFHS (National Family

Health Survey) 32% of married women in India have

faced the violence (IIPS, 2021). National Crime

Records Bureau of India, showed an increase in

crime against women by 15.3% in 2021 in

comparison with the year 2020 (NCRB, 2021).

These figures indicate the seriousness of the

situation.

The significant rise in the crimes against

women necessitates the development of effective

solution to provide the complete safety to the women.

This work aims at developing the women safety

device which requires study of existing women

safety devices f o r identifying gaps to develop the

hardware.

The advanced technology can be utilized to

develop the women safety device. Internet of Things

(IOT) is a new technology which has brought a

paradigm shift in the modern world. IOT provides

the physical network of connected devices and the

exchange of data between these devices and cloud.

2 RELATED WORK

Several

research papers are published on women

safety devices to address the women safety issue.

The safety devices are based on Internet of

Things (IoT) technology.

Most of the devices are

wearable devices where different sensors are used to

measure the biometric parame

ters to detect the

emergency situation. Some devices require human

intervention to operate the device. Most of the

devices use GPS/GSM technology to send the alert

messages to saved contacts. IoT based women

safety device developed in (Sathyashri B., 2019)

device with attack mechanism. This device has

electric shock generator circuit which can generate

the voltage around 1200mV and current of 3

microampere. A smart device with android app de-

veloped in one research work (Penchalaiah N., 2021)

in which device provides the user the location nearest

safe zone. This device is activated by emergency

Kane, A. N., Maktum, T., Mane, V. and Pulgam, N.

IoT Based Automatic Women’s Safety Device for Enhanced Personal Security.

DOI: 10.5220/0013423600004646

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Cognitive & Cloud Computing (IC3Com 2024), pages 46-51

ISBN: 978-989-758-739-9

button and upon activation of the device it sends the

users location to local police station and volunteer. A

machine learning based device developed in other re-

search work (Muskan, 2018) using IOT technology

wherein temperature and heartbeat signals are used as

measuring parameter for operating the device. Then

this device is customized by applying machine

learning algorithm to learn the specific pattern of

temperature and pulse rate in normal and panic

situation. A smart device with online and offline

working flexibility is developed in one research work

(Anusha,D.C. 2022) which sends the location of de-

vice to saved contact in online and offline mode. A

self defense device is developed in (Srishkumar Mani

J., 2023) where pepper spray is used for attacking

purpose. After pressing spray button the mobile app

gets activated which shares the location of user. A

smart device with automatic activation is developed

(

D. K. M. Anand Kumar

, 2020). This device

doesn’t require human intervention for triggering

of the device. The device has pressure sensors

which send the data to machine learning algorithm

for detecting the emergency condition. A smart

band designed in (Bhate A., 2019) with

accelerometer and temperature sensor with

machine learning technique to detect the alarming

condition. It is based on Arduino controller with

GPS/GSM system for communication.

A device

embedded in necklace is developed in (Chowdhuri A.

N. ,2023) with attack mechanism and recording

system. In this system the device is embedded in

necklace with emergency button. The device has

camera module which captures the picture when the

press button is pressed. A smart device with attack

mechanism is developed in (K.S. Sagar Reddy, 2023)

which requires manual activation of electric shock

circuit for attack. A device with monitoring and

messaging system is developed in (Uganya G.,

2023). It is based on

microcontroller, GSM modem

and a GPS receiver. Another device for women safe-

ty developed in

(Tayal S. , 2021) us

ing NodeMCU,

GSM, and GPS modules with manual control. A

tracking device developed in

(C.Priya, 2022)

for

women security with manual activation mechanism.

The device traces the movements using GPS and

posts messages to saved contact umbers using GSM.

The currently available women safety devices

don’t have all features of safety. Some devices

require human intervention for their activation which

is not helpful in the situation when women are not

able to manually activate the device. Some devices

are automatic which detects the physical parameters

of women’s body to trigger the device automatically

but they don’t have attack mechanism. The aim of

this work is to develop an automatic women safety

device with attack, defense and message delivery

mechanism.

3 PROPOSED WORK

The major features of proposed device are shown

in Fig. 1.

The proposed system can be a carry in the

bag device or a wearable device with following

major features:

•

IoT based system with sensors: IoT device will

be integrated with smart sensors

such as pulse

rate sensor, accelerometer and sound detector

to sense abrupt change

in the pulse rate or

sound or movement. These sensors provide the

identification of emergency situation

condition.

•

Self Defense and Attack Mode: It will prevent the

incidence by giving attack and defense power to

the user. It includes the electric shock, hitting

rod or pepper spray which will impede the

attacker and give time to the user to escape.

•

Alert for Assistance : It will generate high

decibel alarm or blinding flash light which

can alert and attract the attention of nearby

people for immediate help.

•

Communication Mechanism: It will send

emergency message and location to the saved

contact numbers and authorities.

Figure 1: Major features of proposed women safety device.

The developed system will be in the form of

standalone device which will automatically

IoT Based Automatic Women’s Safety Device for Enhanced Personal Security

activate the device and send the message without

need of internet

3.1 Architecture of Women Safety

Device

Fig.2 shows architecture of proposed system. It

consists of sensing system, communication

system, alert system and defense and attack

system. An array of sensors is used

to detect the

parameters such as pulse rate, temperature and light.

The temperature sensor DS18B20 is used to

measure temperature. The DS18B20 is a digital

thermometer which gives 9-bit to 12-bit Celsius

temperature measurements with user-programmable

alarm feature at high and low temperature set points.

The DS18B20 needs one data line for

communication over 33 a 1-Wire bus with a central

microprocessor. Additionally it don’t require

external power supply as it takes the power from

data line (parasite power). The heart-rate monitoring

sensor used to measure heart rate based on

spectrophotometry principle. It has red light and

infrared light emitting LEDs and photo detector.

This sensor is placed on the finger and the amount of

light absorbed by the blood is measured. The

BH1715 ambient light sensor is used to detect the

light of surrounding environment. The sensor data

will be

transferred to controller for further

processing. Raspberry pi controller is

be used to

coordinate and control the various devices connected

to women safety system.

Controller is programmed

such that it can read the sensor data and detect the

true safe and unsafe condition based on the values

of sensor data. Machine learning algorithm is

implemented to detect the true condition for

triggering of device in order to avoid false

triggering of the device.

Figure 2 .Architecture of women safety device.

The device has the feature of automatic triggering

activation such that initially manual button is used

when the women travels alone or at night or when

she enters in unknown area. After activation of

manual button,

the device will monitor the sensor

signal, device will also consider the environment

factors

including time, location etc. If

the machine

learning algorithm detects the abnormal situation, the

device activates its automated response system which

includes activation of shock circuit, sending

messages to predefined contacts and authorities and

triggering an alarm.

3.2 User Interface of Women Safety

Device

Fig. 3 demonstrates the

user interface of a women's

safety device. It is equipped with pulse rate and

temperature sensors, an alarm, flash light, shock

circuit, web data monitoring, and SMS functionality

to notify emergency contacts involves creating an

intuitive and user-friendly experience for the wearer.

The functionality of women safety device from

user point of view is explained in this pictorial

diagram. An a

larm and shock circuit will get

a c t i v a t e d i f t h e e m e r g e n c y s i t u a t i o n i s d e t e c t e d b y

the device. It will also send message and location

details to registered contacts along with measured

body parameters.

Figure 3. User interface of women safety device.

3.3 Working of Women Safety Device

The working process of women safety device is

illustrated by the flow chart as shown in Fig. 3.6.

Initially push button and shock circuit are

switched off. The device continuously monitors

the pulse rate and temperature of the user in real

time. T

his physiological data serves as critical

indicators of the wearer's well-being and can

potentially reveal signs of distress or emergency

situations.

The dataset is generated by data collection

method and this data is provided to machine learning

algorithm. The machine learning algorithm is

embedded in Raspberry pi. The dataset is used to

train the algorithm which has certain relationship

IC3Com 2024 - International Conference on Cognitive & Cloud Computing

among the given parameters of data set. The

algorithm takes care of all inputs and compares the

incoming data with the already stored dataset. Upon

detecting a potential emergency situation, the

algorithm triggers the activation of the electric shock

circuit.

The electric shock circuit is designed to deliver a

non-lethal electric shock to potential assailants or

attackers, providing the wearer with a means of self-

defense and a deterrent against further harm. This

feature aims to empower individuals in distressing

situations and create a window of opportunity to

escape or seek help. Additionally, the device sends

the message to alert the emergency contacts or

authorities. It also transmits the wearer's location

information and physiological parameters to

emergency contacts. It generates audible alarms and

flashlight to attract attention and aid in rescue

efforts.

The electric shock circuit give a high voltage and

low amperage charge to the body. The voltage level

is in the range of 200-230V DC voltage and current

is 5mA which causes no harm to the attacker. This

current level is safe and do not pose a significant

health risk to attacker and provides a wearer with a

means of self-defense and a deterrent against further

harm. This feature aims to empower individuals in

distressing situations and create a window of

opportunity to escape or seek help. Additionally, the

device sends the message to alert the emergency

contacts or authorities. It also transmits the wearer's

location information and physiological parameters to

emergency contacts. It generates audible alarms and

flashlight to attract attention and aid in rescue

efforts.

The women safety device will work in two modes

in normal condition and in emergency condition

Normal conditio

In normal condition the pulse

rate, temperature is continuously monitored by

machine learning algorithm.

Abnormal Condition. In abnormal condition the

s h o c k d e l i v e r y m e c h a n i s m a n d a n a l a r m will be

activated and alert message along with location

details sent to registered contact no. Following steps

will be followed:

•

Shock circuit activation

•

Alarm activation

• Alert messages to registered contact nos

3.4 Design of Women Safety Device

The implementation of a women's safety device

integrating temperature, pulse rate, GPS, and a

shock circuit interfacing with a Raspberry Pi

involves a systematic arrangement of hardware and

software components. At the core of the system lies

the Raspberry Pi, serving as the central processing

unit. Connected to it are the various sensors and

modules crucial for monitoring and responding to

potential threats. The diagram portrays the

interconnectedness of these components. Raspberry

Pi OS is operating system for the Raspberry Pi

which is pre-installed with various programming

tools and environment. Python is one of the most

popular programming languages for Raspberry Pi

development. Since Python is open source and cross

platform language, it is used for programming in this

paper. System is designed by connecting the

components to Raspberry Pi. Fig.4 explains the

connections between Raspberry Pi and their

components of the system like pulse sensor,

temperature sensor, GPS module, electric shock

circuit. The connections are explained as follows:

Figure

4. Circuit diagram of women safety device.

3.5 Machine Learning Algorithm

The machine-learning algorithm acquires perception

the sensor parameters and identifies the safe and

unsafe condition of the women. The body parameters

and environment parameters are used to classify the

women condition whether safe or unsafe. We have

selected logistic regression machine learning

algorithm for this work. Logistic regression provides

prediction of safe or unsafe condition of the women

by considering the real time variables such as pulse

rate, temperature, age, and environmental conditions.

It is statistical technique used to evaluate the proba-

bility of a women being in safe or unsafe condition

IoT Based Automatic Women’s Safety Device for Enhanced Personal Security

based on these parameters. The real time physiologi-

cal parameters such as pulse rate and temperature

gives the indication of stress which can be correlated

with the condition of body in unsafe condition. Age

is also a significant factor, as younger or older

individuals might perceive and respond to safety

concerns differently. Further, environmental

conditions includes the parameters like time of day

and lighting in surrounding environment, all of these

factors can cause a significant impact on safety

perceptions. In the logistic regression algorithm, we

use these input variables to estimate the probability

of a woman being in a safe situation. By training the

model on data that includes incidents of safety

concerns alongside corresponding measurements of

pulse rate, temperature, age, and environmental

conditions, we can establish patterns and

relationships that help predict safety outcomes.

Model is trained on the training data, after which

it is deployed to evaluate the real time data to identi-

fy the safety condition. By monitoring and

analysing these predictions, it prevents the false trig-

gering of the device. If a woman is found in unsafe

condition then it takes the action as per the

functionality of the device.

3.6 Implementation of Women Safety

Device

To assess feasibility of the proposed system, we

have implemented the system on an IoT based

testbed i.e. a Raspberry Pi series platform. Fig. 5

shows the implementation diagram of women safety

system. The electric shock circuit is connected

raspberry pi through relays. GPS, pulse and

temperature sensors are energized by raspberry pi

whereas the electric shock circuit requires the

battery to store the energy for instantaneous

discharge.

Figure 5. Prototype of women safety device.

4 RESULTS

The device generates the electric shock and buzzer

in emergency situation and sends the SMS to

registered contact numbers. The non-lethal shock is

generated which can stop the attacker and help the

women by giving opportunity to escape. The sound

of buzzer is kept high so as to attract the attention

and alert the nearby people.

Fig. 6 shows the screen shot of the message

delivered to the registered contacts when the women

has faced the emergency condition. The current

location of the women is transmitted along with

message. The location is displayed on the map for

easy identification of the area.

Figure 6. Emergency SMS snapshot.

5 CONCLUSION

This study focuses on development of women

security system that provides safety to women so

that women can use these devices as and when

required while facing social challenges.

It was observed that IoT based devices offer

innovative features, sensors for making them

smart devices. Still

there are few gaps which

affect the widespread use of these devices. To

address those gaps,

the solution is provided in this

paper to make the device more effective.

Furthermore, developed paper provide the self-

defense tool to the women to move confidently in

IC3Com 2024 - International Conference on Cognitive & Cloud Computing

the society. This device is developed by taking

into account all possible ways of attack and

possible ways for easy defense. The device is

automatically operated by continuously

monitoring pulse, temperature, lighting condition

of the surrounding which can give the indication

of emergency condition.

The device has shock

delivery mechanism which will be activated once

emergency condition is detected. Also an alarm

sound is also generated to attract the attention of

nearby people. The text messages and location

details will be sent to registered mobile no upon

activation of the device using GPS and GSM

techniques. Thus this device will provide the

enhanced protection to the women.

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IoT Based Automatic Women’s Safety Device for Enhanced Personal Security