A Cost-Effective IoT-Driven Intruder Detection System Using Machine Learning Based Face Recognition | Chapter 1 | Mathematics and Computer Science: Contemporary Developments Vol. 6

The present study explores about Cost-Effective IoT-Driven Intruder Detection System using machine learning-based face recognition. An intruder may enter the premises without the owner's knowledge. A motion detection system using a PIR sensor is employed to detect any movement near the entrance. IoT security solutions to avoid theft require an intelligent security system that is convenient and requires minimum human effort. A USB camera is triggered to capture the intruder's image when motion is detected. This image is then processed using Machine Learning algorithms and OpenCV for face detection and recognition. The Raspberry Pi compares the detected face with a database of approved images. It processes 28 images per second and sends an email notification to the owner, indicating whether the person is authorized or unauthorized. The owner can verify the authentication via the Internet of Things.  The developed low-cost system is fast, highly accurate, gives efficient alerts, and serves as a monitoring system. It is convenient to solve security problems, which will help reduce or stop break-ins.

 

Author (s) Details

G. Mallikharjuna Rao
Department of ECE, Chaitanya Bharathi Institute of Technology, Hyderabad, India.

 

Haseena Palle
Department of ECE, Chaitanya Bharathi Institute of Technology, Hyderabad, India.

 

Pragna Dasari
Department of ECE, Chaitanya Bharathi Institute of Technology, Hyderabad, India.

 

Shivani Jannaikode
Department of ECE, Chaitanya Bharathi Institute of Technology, Hyderabad, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v6/2466

Studies on the Implementation of Remote Patient Monitoring Using Wireless Pulse Oximeter | Chapter 2 | Recent Developments in Engineering Research Vol. 7

 A Pulse Oximeter is a system used to monitor the vital elements of the patient, such as the level of oxygen in the blood and heart rate. By attaching it to an ECG monitor via cables, the pulse oximeter can also be transformed into a multiparameter patient monitor. Wireless battery-powered pulse oximeters are now available , allowing patients to continuously monitor their health. The biggest downside to the new method is that to see the readings and make final conclusions, the physician / nurse must walk all the way to the computer. Our primary objective is to develop a wireless pulse oximeter that presents its live feed on the phone of the doctor / nurse via mobile application to make this process more efficient and bring advances in its operations. The microcontroller has been programmed and designed with the aid of PSoC designer 5.4. The mobile application is an essential part, as it serves as the user 's basic interface and the application has been developed and programmed to execute the basic work with the aid of Android Studio.

Author(s) Details

T. J. Jeyaprabha

Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Chennai, Tamil Nadu, India.

Dr. G. Sumathi
Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Chennai, Tamil Nadu, India.

A. Abijith
Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Chennai, Tamil Nadu, India.

K. Guruprasanth
Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Chennai, Tamil Nadu, India.

Chiranjeevraja Thillaiganesh
Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Chennai, Tamil Nadu, India.

View Book :- https://bp.bookpi.org/index.php/bpi/catalog/book/299