Iot and Biometrics applications

1. National level Webinar
(21st – 24th June 2020)
O R G A N I ZI N G S E C R E TA RY
D R . R . G U N AVAT H I ,
H E A D & A S S O C I AT E P R O F E S S O R ,
P G & R E S E A RC H D E PA RT M E N T O F
C O M P U T E R A P P L I C AT I O N S
PG & Research Department of Computer Applications
organized
IoT – Applications and Machine Learning

2. GOKUL RAJAN V
Assistant Professor ,
School of CSE
Galgotias University, Uttar Pradesh
Gokulrajan.v@gmail.com ,
+91 8012 880 991.
IoT with Biometrics

3. Agenda
 What is IoT?
 What is Biometrics?
 IoT with biometrics
 Architecture
 Applications
 Conclusion
 Feature Works
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4. IoT Definition
 Wikipedia
The IoT refers the uniquely identifiable object and their
virtual representation in an internet like structure.
 Cisco
IoT is network of physical object accessed through the
internet as defined by technology analysts and visionaries.
These objects contain enabled technology to interact with
internal states or external environment. In other words, when
objects can sense and communicate, it changes how and where
decisions are made, and who makes them.
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5. Cont…
 ITU
The IoT can be viewed as a global infrastructure for the
information society, enabling advanced services by
interconnecting (physical and virtual) things based on
existing and evolving interoperable information and
communication technologies (ICT).
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6. History
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7. Why IoT
 Ubiquitous Connectivity
 Widespread Adoption of IP
 Computing Economics
 Miniaturization
 Advances in Data Analytics
 Rise of Cloud Computing
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8. Characteristics of IoT
 Interconnectivity: With regard to the IoT, anything can be
interconnected with the global information and communication
infrastructure.
 Heterogeneity: The devices in the IoT are heterogeneous as based on
different hardware platforms and networks. They can interact with other
devices or service platforms through different networks.
 Dynamic changes: The state of devices change dynamically, e.g.,
sleeping and waking up, connected and/or disconnected as well as the
context of devices including location and speed. Moreover, the number
of devices can change dynamically.
 Enormous scale: The number of devices that need to be managed and
that communicate with each other will be at least an order of magnitude
larger than the devices connected to the current Internet. The ratio of
communication triggered by devices as compared to communication
triggered by humans will noticeably shift towards devicetriggered
communication.
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9. Architecture
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10. Arduino Block Diagram
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11. Applications
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12. Cont…
 Smart Home
 Wearable's - Fit Bits, heart rate monitors and smart watches
 Smart City
 Connected car
 Healthcare
 Smart retails
 Smart farming
 agriculture
 Ambient Umbrella – Weather forecasting
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13. Disadvantages
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 Lack of security and privacy
If all of our information is stored on the internet, people could hack into it
 Losing control of your life
No system is robust and fault-free
 The loss of jobs
Automation of IoT

14. Biometrics
 Biometrics refers to the automatic identification of a
person based on his or her physiological and behavioral
characteristics
 Physiological biometrics
Fingerprint, Fingers/ Hand vain, Hand geometry, Iris, Retina, Face, Ear,
voice, Thermography, DNA, etc.
 Behavioral biometrics
Gait, Lip Movement, Signature, Key stroke, etc.
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15. History
 1858 – First systematic capture of hand images for identification purposes is
recorded
 1883 – Twain writes about fingerprints in “Life on the Mississippi”
 1870 – Bertillon develops anthropometries to identify individuals
 1892 – Galton develops a classification system for fingerprints
 1896 – Henry develops a fingerprint classification system
 1903 – NY State Prisons begin using fingerprints
 1903 – Bertillon System collapses
 1936 – Concept of using the iris pattern for identification is proposed
 1960s – Face recognition becomes semi-automated
 1960 – First model of acoustic speech production is created
 1965 -Automated signature recognition research begins
 1969 – FBI pushes to make fingerprint recognition an automated process
 1970 – Behavioral components of speech are first modeled
 1976 – First prototype system for speaker recognition is developed– Face
Recognition takes another step towards automation
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 1985 – Concept that no two irides are alike is proposed
 1985 – Patent for vascular pattern recognition is awarded to Joseph Rice
 1986 – Patent is awarded stating that the iris can be used for identification
 1988 – First semi-automated facial recognition system is deployed
 1992 – Biometric Consortium is established within US Government
 1994- First iris recognition algorithm is patented
 1994 – Palm System is benchmarked
 1998- FBI launches COOlS (DNA forensic database)
 2000 – First Face Recognition Vendor Test (FRVT 2000) is held
 2002 – ISO/IEC standards committee on biometrics is established
 2008 – U.S. Government begin coordinating biometric database use
 2013 – Apple includes fingerprint scanners into consumer-targed smart
phones

17. Why Biometrics
 Most Secure
 Cant be stolen, borrowed or forgotten
 Convenient
 Passwords are not user friendly
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18. Characteristics
 Uniqueness
 Universality
 Permanence
 Measurability
 User friendliness
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19. Applications
 Verification
“one-to-one” biometric comparison
 Identification
“one-to-many” comparison
 Duplicate checking
whether there are individuals represented more than once in a database
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20. Cont…
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 Law enforcement and public security (criminal/suspect
identification)
 Military (enemy/ally identification)
 Border, travel,
and migration control (traveller/migrant/passenger
identification)
 Civil identification (citizen/resident/voter identification)
 Healthcare and subsidies (patient/beneficiary/healthcare
professional identification)
 Physical and logical
access (owner/user/employee/contractor/partner identification)
 Commercial applications (consumer/customer identification)

21. Process of Recognition
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22. Biometrics towards IoT
 Biometric Attendance System
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23. Futures
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 Smart Fridge
Your fridge contacts a
supermarket and orders
vegetables, which you are
running out of. And it also
sends you a message regarding
the order.
Here are some scenarios that may sound like fiction, but
are possible with IoT. So, have a look:

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 Smart Car
Your car sends a message
when you are heading back to
your home in order to switch
on the lights, tune the TV to
your liked channel so that you
feel welcomed after reaching
your house.

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 Smart Alarm
After waking you up, your alarm clock sends a signal to the
geyser to heat water at your preferred temperature or conveys a
message to your coffee maker with regard to brewing coffee

26. Cont…
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 Smart ID cards
Unlike conventional biometric
processes, the "Match-on-
Card" algorithm allows
fingerprints to be matched
locally with a reference frame
thanks to a microprocessor
built into the biometric ID card
without having to connect to a
central biometric database (1:1
matching)

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