Secret Image Sharing Scheme Based on Compressed Sensing
Implementation of HOG Based Feature Extraction Method
Soldier Health and Position Monitoring System using GPS and IOT Technology
A Review on the Closed-Loop Strategy for Speed Control of BLDC Motors
V/F Based Speed Controller of Induction Motor using Ann Controller - A Review
Blockchain 3.0: Towards a Secure Ballotcoin Democracy through a Digitized Public Ledger in Developing Countries
Fetal ECG Extraction from Maternal ECG using MATLAB
Brief Introduction to Modular Multilevel Converters and Relative Concepts and Functionalities
Detection of Phase to Phase Faults and Identification of Faulty Phases in Series Capacitor Compensated Six Phase Transmission Line using the Norm of Wavelet Transform
A Novel Approach to Reduce Deafness in Classical Earphones: MUEAR
A novel mathematical ECG signal analysis approach for features extraction using LabVIEW
Filtering of ECG Signal Using Adaptive and Non Adaptive Filters
Application of Polynomial Approximation Techniques for Smoothing ECG Signals
A Novel Approach to Improve the Wind Profiler Doppler Spectra Using Wavelets
Implementation of HOG Based Feature Extraction Method
As digitization is continuously going to be increased, the representation of signal, its communication, storage and processing have been rapidly shifted in to digital landscape instead of analog landscape. With the advent & rapid proliferation of Digital Signal Processing devices, it is highly desirable to process much of the signal in software in digital domain, so as to reduce the analog front end & component count. An important & widely used process on signals is filtering, which is required in numerous applications. Digital filters are widely classified as Finite Impulse Response (FIR) and IIR Infinite Impulse Response (IIR) Filters, where IIR Filters with some number of coefficients exhibit more advantages over FIR Filter, however IIR filters provide some disadvantages like complex design and multimodal noise. In the present work, an Auto Adoptive IIR Filter has been developed using hybrid techniques. This hybrid technique has been composed by integrating or combining the Pth Norm Optimization with Artificial Neural Network (ANN). These two techniques have been used in such a way that the filter is designed using Pth Norm Optimization algorithm and filter's coefficients have been auto adapted using Artificial Neural Network to achieve the desired results. The simulation work is obtained using MATLAB and realtime audio capture, filtering and playback are demonstrated.
In this pandemic situation, everyone are vulnerable to COVID-19. So the necessity for safety measures checking system has become inevitable. Every measure is currently being checked separately using man power, crowded places are more susceptible for the spread of disease. Using infrared sensor and setting up a threshold crowd management is accomplished. The proposed system delivers a non contact solution by integrating sensors in order to monitor the human body temperature and environmental conditions remotely, automatically and quickly. The system completely avoids direct contact with the residents during the process of screening. Along with temperature sensing, proper sanitization is also critical. As a result, the proposed work also employs a pump motor to spray sanitization automatically and without the need for human intervention. Many companies and organizations must adjust to and protect an infected person by spotting someone who does not wear a masked face; however, this is not always possible. The proposed system also investigates the performance of detecting people wearing a face mask in a real-time situation using Machine Learning. The results show the highest precision from all input images and a camera.
This paper aims to develop a monitoring tool for farming using Hydroponic techniques. The water with nutrient solution level is detected by the Ultrasonic sensor HC-SR04 and the temperature is detected by the temperature sensor W1209 digital temperature. The pH level of water is detected by pH sensor and PH4502C for transferring the voltage generated by the sensor to the Arduino uno board. Data from the sensor will be forwarded into Arduino Uno and displayed in Liquid Crystal Display (LCD) and then the wireless fidelity (WIFI) ESP8266 module will transmit the level of water with nutrient solution, pH value and the temperature to the Android phone through ThingView app.
In this fast moving world, Technology plays a major role in the medical field too. Among Doctors, Surgeons are most importantly in need of new technologies that could make their job easier and efficient. They easily adopt to new technologies which would aid them in providing a better surgical and patient experience. Augmented Reality (AR) is a rapidly developing technology and is easily available, accessible and is also affordable. Hence they are used in healthcare systems to enhance them. We are developing a system that displays the vital information of a patient to the surgeon through an AR glass which is also automated, to give alert to the surgeon if anything is abnormal about the patient.
Crowd detection and density estimation from crowded images have a wide range of application such as crime detection, congestion, public safety, crowd abnormalities, visual surveillance and urban planning. The purpose of crowd density analysis is to calculate the concentration of the crowd in the videos of observers. The job of detecting a face in the crowd is complicated due to the variability present in human faces including color, pose, expression, position, orientation, and illumination. This paper proposes a deep learning based framework for automating the task of monitoring social distancing using surveillance video.
