scholarly journals Performance Analysis of Analog Passive Detectors in Target Tracking Wireless Sensor Networks

2021 ◽  
Vol 10 (1) ◽  
pp. 417-422
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Environmental Parameters ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Surveillance Systems ◽  
Real Time System ◽  
Outdoor Environments ◽  
Human Sensing ◽  
Indoor And Outdoor Environments

The development of surveillance systems for indoor and outdoor environments using currently available wireless sensor technology without violating privacy issues is a challenging task. Passive Infrared (PIR) detectors are suitable for such systems provided solutions to the technical limitations are implemented. In the proposed work, the development of a human tracking system using analogue PIR detectors and currently available wireless sensor technology is presented. Performance is evaluated by conducting real-time tests in different environmental scenarios. Analysis of experimentalresults of human sensing signals indicates that performance is affected by environmental parameters. These findings will be helpful for the researchers while implementing a real-time system in the field

A Real-Time System for Pedestrian Detection Based on GMM and HOG

2011 ◽  
Vol 403-408 ◽  
pp. 2723-2727
Author(s):  
Feng Li ◽  
Yi Feng Zou ◽  
He Qin Zhou ◽  
Guan Jun Pei
Keyword(s):  
Real Time ◽  
Moving Objects ◽  
Tracking System ◽  
Pedestrian Detection ◽  
Gaussian Mixture ◽  
Video Sequences ◽  
Surveillance Systems ◽  
Real Time System ◽  
Efficient System ◽  
Histograms Of Oriented Gradients

The detection of pedestrian which has been widely used in digital surveillance systems is a popular topic in computer vision. This paper mainly discusses a system of pedestrian detection in video sequences captured from a stationary camera hanging in a public scene. We describe an efficient system combining background subtraction based on Gaussian Mixture Model (GMM) and object classification based on Histograms of Oriented Gradients (HOG). We first process moving objects segmentation using GMM. Then a HOG detector is used to classify the moving objects into person and none-person. Experimental results on video sequences have demonstrated that the real-time tracking system can process 15 to 30 frames per second robustly with a high accuracy.

scholarly journals Real-Time Heart Pulse Monitoring Technique Using Wireless Sensor Network and Mobile Application

2018 ◽  
Vol 8 (6) ◽  
pp. 5118 ◽  
Author(s):  
Nabeel Salih Ali ◽  
Zaid Abdi Alkaream Alyasseri ◽  
Abdulhussein Abdulmohson
Keyword(s):  
Real Time ◽  
Mobile Application ◽  
Electronic Circuit ◽  
Healthcare Services ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Medical Monitoring ◽  
Monitoring Technique ◽  
Arduino Microcontroller ◽  
User Friendly

Wireless Sensor Networks (WSNs) for healthcare have emerged in the recent years. Wireless technology has been developed and used widely for different medical fields. This technology provides healthcare services for patients, especially who suffer from chronic diseases. Services such as catering continuous medical monitoring and get rid of disturbance caused by the sensor of instruments. Sensors are connected to a patient by wires and become bed-bound that less from the mobility of the patient. In this paper, proposed a real-time heart pulse monitoring system via conducted an electronic circuit architecture to measure Heart Pulse (HP) for patients and display heart pulse measuring via smartphone and computer over the network in real-time settings. In HP measuring application standpoint, using sensor technology to observe heart pulse by bringing the fingerprint to the sensor via used Arduino microcontroller with Ethernet shield to connect heart pulse circuit to the internet and send results to the web server and receive it anywhere. The proposed system provided the usability by the user (user-friendly) not only by the specialist. Also, it offered speed andresults accuracy, the highest availability with the user on an ongoing basis, and few cost.

scholarly journals An Autonomous Path Controller in a System on Chip for Shrimp Robot

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 441 ◽  
Author(s):  
Sergio Barrios-dV ◽  
Michel Lopez-Franco ◽  
Jorge D. Rios ◽  
Nancy Arana-Daniel ◽  
Carlos Lopez-Franco ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Trajectory Tracking ◽  
Neural Control ◽  
Tracking System ◽  
Kinematic Model ◽  
System On Chip ◽  
Optimal Controller ◽  
Real Time System ◽  
On Chip

This paper presents a path planning and trajectory tracking system for a BlueBotics Shrimp III®, which is an articulate mobile robot for rough terrain navigation. The system includes a decentralized neural inverse optimal controller, an inverse kinematic model, and a path-planning algorithm. The motor control is obtained based on a discrete-time recurrent high order neural network trained with an extended Kalman filter, and an inverse optimal controller designed without solving the Hamilton Jacobi Bellman equation. To operate the whole system in a real-time application, a Xilinx Zynq® System on Chip (SoC) is used. This implementation allows for a good performance and fast calculations in real-time, in a way that the robot can explore and navigate autonomously in unstructured environments. Therefore, this paper presents the design and implementation of a real-time system for robot navigation that integrates, in a Xilinx Zynq® System on Chip, algorithms of neural control, image processing, path planning, and inverse kinematics and trajectory tracking.

scholarly journals Real Time System for Human Identification and Tracking from Surveillance Videos

2018 ◽  
Vol 7 (3.12) ◽  
pp. 244 ◽  
Author(s):  
D Vishaka Gayathri ◽  
Shrutee Shree ◽  
Taru Jain ◽  
K Sornalakshmi
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Training Data ◽  
Live Streaming ◽  
Data Sets ◽  
Surveillance Systems ◽  
Real Time System ◽  
Detection Techniques ◽  
Current Location ◽  
Viable System

The need for intelligent surveillance systems has raised the concerns of security. A viable system with automated methods for person identification to detect, track and recognize persons in real time is required. The traditional detection techniques have not been able to analyze such a huge amount of live video generated in real-time. So, there is a necessity for live streaming video analytics which includes processing and analyzing large scale visual data such as images or videos to find content that are useful for interpretation. In this work, an automated surveillance system for real-time detection, recognition and tracking of persons in video streams from multiple video inputs is presented. In addition, the current location of an individual can be searched with the tool bar provided. A model is proposed, which uses a messaging queue to receive/transfer video feeds and the frames in the video are analyzed using image processing modules to identify and recognize the person with respect to the training data sets. The main aim of this project is to overcome the challenges faced in integrating the open source tools that build up the system for tagging and searching people.  

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