In the era of big data and artificial intelligence,how to use the existing computer,intelligent fabrics and wearable technology To help improve the serious situation of physical and mental health, and provide a better way of life and living environment for people, Is the current hot spot of common concern in the field of computer and biomedicine.

1. “
1
I-FABRIC
HEERA COLLEGE OF ENGINEERING AND TECHNOLOGY

2. CONTENTS
2
1. INTRODUCTION
2. BLOCK DIAGRAM
3. CLASSIFICATION
4. SAMPLE DIAGRAM
5. SYSTEM ARCHITECTURE
6. SYSTEM MODEL
7. APPLICATIONS
8. ADVANTAGES
9. DISADVANTAGES
10. EXPERIMENTAL ANALYSIS
11. CONCLUSION
12. REFERENCES

3. “
• In the era of big data and artificial intelligence,how to use the existing
computer,intelligent fabrics and wearable technology
• To help improve the serious situation of physical and mental health,
and provide a better way of life and living environment for people,
• Is the current hot spot of common concern in the field of computer
and biomedicine.
• By combining wearable fabrics with sensors, artificial intelligence and
other technologies, the new intelligent fabrics create an intelligent,
• Flexible and adaptive performance, meeting people’s needs better
and becoming more acceptable to users than traditional fabrics.
• Present intelligent fabrics has some shortcomings ,such as
insufficient interactive ability ,the narrow scope of applications.
• The proposed system builds a comprehensive and sustainable health
monitoring and guidance ecosystem.
3
INTRODUCTION

4. 4
Si
No
Title Author Advantage Disadvantage Technology
Used
1 Wearable Affective
Robot
Jun yang,
Guangming
Tao,Jun Zhou
Can improve
human health
Not
concentrating on
a particular
person
Microcontrolle
r
2 Textile Fiber Optic
Microbend Sensor Used
for Heartbeat and
Respiration Monitoring
2021
Xiufeng
Yang,Zhihao
Chen,Ju
Teng Teo
Can measure
heart beat and
respiration rate
Comfortable to
wear
No phsycological
data can
measured
Micro
controller
3 Living with I-
Fabric:Smart living
powered by intelligent
fabric and deep analysis
Min
Chen,Yingyin
Jiang,Nadra
Guizani
Measures
phsyological
datas
Multiple smart
accessories
and cognitive
devices
Time delay Micro
controller

5. “
PROPOSED SYSTEM
5
 To acquire long term user data like ECG,temperature etc..
 To collect physiologiacal and psychological datas.
 Data analysis with multi-level cloud collaboration and intelligent
interactive feedback.
 To collect environmental data and emotion analysis

6. 6
BLOCK DIAGRAM

7. WORKING
• Built mainly utilizing the data acquired by GPS and Camera
embedded in Ifabrics.
• Methods
• 1.Obstacle Detection
• 2.Move mode analysis
• Through these analyses ,environment value is determined
• Obstacle detection algorithm : provides warnings against
dangers in real time
• Eg: Warning to avoid the car moving at full speed
•
• Move model algorithm: Provides an individualized
recommendation to user and improves users life quality. 7

8. • Used to determine users experience value of smart living.
• Experience value of smart living consists of two parts
1. Health value
2. Environmental value
Health value – reflects health status of a user
• Calculated using Physiological and psychological data of user.
Environmental value –reflect the environmental conditions perceived by a
user .
• Calculated using modelling based on obstacle detection& moving
trajectory data
8

9. 9
1.Sensors : devices that detect and measure physical properties
Eg:temperature sensors
2.Actuators: are electronic components that perform physical actions
based on instructions from microcontroller
.
Eg:LED, motor
3.Powersupply : Provides necessary electrical energy to the circuit
4.Microcontroller: Serves as CPU, controls and coordinates various
functions and features of the fabrics
5.Antenna: It is a device designed to transmit or receive electromagnetic
waves.
MATERIAL AND METHOD FOR EXPERIMENT

10. 10
Processes
1.Multi –Dimensional and multimodal data collection layer
2.Data analysis layer with multi-level cloud collaboration
3.Intelligent interactive feedback layer

11. 11
1. Multidimensional and
multimodal data
collection layer
1. Physiological data
• To monitor and acquire long term user data
• Eg: ECG,EMG
2. Psychological data
• To acquire users voice data for emotion analysis
3 Environmental information collection
• To acquire environmental data
• Eg:temperature, climate
• Use of GPS Sensor

12. 12
2.Data Analysis layer with multi-level cloud
collaboration
• Two levels of cloud structures are Edge and Remote
• Data collected from first process is sent to edge
cloud in time.
• For Simple processing and real time analysis
• Preprocesssing operations performed in edge cloud
to filter invalid data
• PCA algorithm used for feature selection and
reduction
• Remote cloud is used to check whether data is
abnormal
• Used to judge physical and mental health of a
person for a specific period of time

13. 13
3.Intelligent Interactive Feedback Layer
• Provide different interactive service to users with help of
Ifabric and smartphone
• To reduce occurrence of diseases such as Lumbar
Vertebrae and Cervical Vertebrae
• To avoid danger in advance
• For comforting depressed people
• To make fitness plan
• Use of multi-level cloud app give corresponding
suggestions to users
• App shows users the changes of various data in a period
of time.

14. HEALTH MONITORING
MODEL
14

15. 15

16. OBSTACLE DETECTION
• It is a computational process designed to identify and locate
obstacles within a given environment.
• The stereo camera is embedded in the smart hat and the
obstacles on the road are detected by the stereo vision system
using pixel matching technology
• Pixel matching technology in obstacle detection involves
comparing pixels in images or frames to identify obstacles
• This algorithm greatly reduces the time cost and is capable of
detecting both moving and static obstacles effectively
16

17. MOVE MODE ANALYSIS
• It is used to understand how individuals navigate and interact
with their surroundings
• Through the core data mining we can find the locations and
personal frequent paths that are meaningful to users
• According to historical GPS data of user the users preferred
location area is determined
• A vector km= (e1, e2,….., en) is used to represent the set of
stagnation areas of a user .
17

18. 18
• By multi source data fusion we can get the smart living
experience value of users wearing the Ifabric.
• Due to the interactive characteristics between the Ifabric and
users reasonable health protection and a good environment
• adaptation scheme can be formulated for users according to
experience value using Reinforcement learning.
• Ri = users smart living experience value
• Gi =mapping function from health monitoring and environment
cognition of user i to Ri
• The user experience of the Ifabric is continuously improved
FUSION OF SMART LIVING

19. 19
EXPERIMENTAL ANALYSIS
Figure 1
1. the experiment values obtained by the system are slightly higher than those
given by users.
1. The blue line is the absolute value of the difference between the two and
the difference tends to zero indicating that the user is satisfied with the
Interactive service of system.
Figure 2
1. the delay is relatively high
1. The average delay of two is 237.25ms and 265.8ms respectively, which
can meet the uses tolerance of delay

20. 20
The comparison of experience value

21. 21
System delay analysis

22. ADVANTAGES
• Health monitoring and wellness
• Enhanced comfort and convenience
• Future proofing
• Data-driven insights
• Environmental Sustainability
22

23. DISADVANTAGES
• Privacy concerns
• Cost
• Dependency on Internet and
power
• Limited customisation
• Complexity and maintenance
23

24. FUTURE SCOPE
24

25. 1. In Defence
● Smart fabric plays an
important role.
● It improves the location
tracking
Provides protection.
● Enables the continuous
checking of the vitals of
the person.
25

26. 2. In the field of sports
and games
● It helps to measure the heart rate
pulse rate
● The muscle movements ,the speed of
the athlete, his/her movements etc..
26

27. 3. In the field of Medical
Science and prostetics
● Smart fabrics helps to detect the
movement of muscles ,nervous system
ecg,eeg etc. ..
27

28. 28
• The proposed system combines a variety of Intelligent fabrics with
smartphones and cloud to form a comprehensive health
monitoring and guidance system
• The experimental results show that the experience value of smart
living and the delay of the system are within the acceptable range
of users
• The proposed system solved the problem of existing fabrics such
as . single application scenario and impossible to monitor both
physical and mental health simultaneously.
• Finally ,the test bed is set up to validate the effectiveness of the
proposed system.
CONCLUSION

29. 1.Langereis, G.R.; Bouwstra, S.; Chen, W. Sensors, Actuators and
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architectures and communications technologies for wearable health-
monitoring systems. Sensors 2012, 12, 13907–13946. [Google Scholar]
3.Coosemans, J.; Hermans, B.; Puers, R. Integrating wireless ECG
monitoring in textiles. Sens. Actuators A Phys. 2006, 130–131, 48–53.
[Google Scholar]
4.Linz, T.; Gourmelon, L.; Langereis, G. Contactless EMG sensors
embroidered onto textile. Proceedings of the 4th International Workshop
on Wearable and Implantable Body Sensor Networks, Aachen, Germany,
26–28 March 2007; Volume 13, pp. 29–34.
29
REFERENCES

30. THANK YOU
30