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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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An Integrated Approach to Home Security and Safety Systems (Hardcover)
Loot Price: R3,172
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An Integrated Approach to Home Security and Safety Systems (Hardcover)
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This book provides an integrated solution for security and safety
in the home, covering both assistance in health monitoring and
safety from strangers/intruders who want to enter the home with
harmful intentions. It defines a system whereby recognition of a
person/stranger at the door is done using three modules: Face
Recognition, Voice Recognition and Similarity Index. These three
modules are taken together to provide a percentage likelihood that
the individual is in the "known" or "unknown" category. The system
can also continuously monitor the health parameters of a vulnerable
person living alone at home and aid them in calling for help in an
emergency. The authors have analyzed a number of existing biometric
techniques to provide security for an individual living alone at
home. These biometric techniques have been tested using MATLAB (R)
image processing and signal processing toolboxes, and results have
been calculated on the basis of recognition rate. A major
contribution in providing security is a hybrid algorithm proposed
by the author named PICA, which combines features of both PCA
(Principle Component Analysis) and ICA (Independent Component
Analysis) algorithms. This hybrid approach gives better performance
recognition than either system alone. The second proposed hybrid
algorithm for voice recognition is named as a MFRASTA algorithm by
combining features of MFCC (Mel Frequency Cepstral Coefficient) and
RASTA-PLP (RelAtive SpecTrA-Perceptual Linear Prediction)
algorithm. After performing experiments, results are collected on
the basis of recognition rate. The authors have also proposed a
third technique named as a Similarity Index to provide trust-based
security for an individual. This technique is text independent in
which a person is recognized by pronunciation, frequency, tone,
pitch, etc., irrespective of the content spoken by the person. By
combining these three techniques, a high recognition rate is
provided to the person at the door and high security to the
individual living independently at home. In the final contribution,
the authors have proposed a fingertip-based application for health
monitoring by using the concept of sensors. This application is
developed using iPhone 6's camera. When a person puts their
fingertip on a camera lens, with the help of brightness of the
skin, the person's heartbeat will be monitored. This is possible
even with a low-quality camera. In case of any emergency, text
messages will be sent to the family members of the individual
living alone by using 3G Dongle and MATLAB tool. Results show that
the proposed work outperforms all the existing techniques used in
face recognition, voice recognition, and health monitoring alone.
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