scholarly journals Live Human Detection Robot in Earthquake Conditions

2021 ◽  
Author(s):  
R. Kabilan ◽  
K. Lakshmi Narayanan ◽  
M. Venkatesh ◽  
V. Vikram Bhaskaran ◽  
G.K. Viswanathan ◽  
...  
Keyword(s):  
Human Body ◽  
Temperature Sensor ◽  
Humidity Sensor ◽  
Thermal Image ◽  
Search Method ◽  
Human Detection ◽  
Intelligent Robot ◽  
Experimental Setting ◽  
Detection And Tracking ◽  
Difficult Challenge

This report outlines a human searching device that takes the form of a robotic car and serves as a backup mechanism for saving lives in the event of a disaster. The temperature sensor, in general, detects the thermal image of the human body, and there has been extensive research into human searching with the gas and humidity sensor. In the intelligent robot device’s study, achieving accurate and reliable human detection and tracking is a difficult challenge. The architecture of human detection and tracking mechanisms over non-overlapping field of views is examined in this paper. To compensate for their respective flaws, a search method is proposed. The proposed method’s rate and accuracy of human detection was tested in an experimental setting. We may guide the robot’s movement by commanding it to move left, right, forward, or backward. We plan to equip the robot with sensors that will enable us to track and detect humans behind the wall.

scholarly journals Thermal vision based intelligent system for human detection and tracking in mobile robot control system

2016 ◽  
Vol 20 (suppl. 5) ◽  
pp. 1553-1559 ◽  
Author(s):  
Ivan Ciric ◽  
Zarko Cojbasic ◽  
Danijela Ristic-Durrant ◽  
Vlastimir Nikolic ◽  
Milica Ciric ◽  
...  
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Robot Control ◽  
Thermal Image ◽  
Human Detection ◽  
Intelligent Algorithms ◽  
Detection And Tracking ◽  
Mobile Robot Control ◽  
Thermal Vision ◽  
Robot Platform

This paper presents the results of the authors in thermal vision based mobile robot control. The most important segment of the high level control loop of mobile robot platform is an intelligent real-time algorithm for human detection and tracking. Temperature variations across same objects, air flow with different temperature gradients, reflections, person overlap while crossing each other, and many other non-linearities, uncertainty and noise, put challenges in thermal image processing and therefore the need of computationally intelligent algorithms for obtaining the efficient performance from human motion tracking system. The main goal was to enable mobile robot platform or any technical system to recognize the person in indoor environment, localize it and track it with accuracy high enough to allow adequate human-machine interaction. The developed computationally intelligent algorithms enables robust and reliable human detection and tracking based on neural network classifier and autoregressive neural network for time series prediction. Intelligent algorithm used for thermal image segmentation gives accurate inputs for classification.

Home Automation Using Bluetooth

2020 ◽  
pp. 675-678
Author(s):  
Mukesh Mahajan ◽  
Astha Dubey ◽  
Samruddhi Desai ◽  
Kaveri Netawate
Keyword(s):  
Temperature Sensor ◽  
Humidity Sensor ◽  
The Other ◽  
Automation System ◽  
Home Automation ◽  
Wireless Devices ◽  
Home Appliances ◽  
Home Automation System ◽  
Condition Systems

This paper reviews basically about Bluetooth based home automation system. It is controlled by PIC microcontroller. Home automation can be defined as the ability to perform tasks automatically and monitor or change status remotely. These include tasks such as turning off lights in the room, locking doors via smartphone, automate air condition systems and appliances which help in the kitchen. Now a days several wireless devices are available such as Bluetooth, Zigbee and GSM. Since Bluetooth is low in cost than the other two and hence is used more. In this paper we have described the methods of automating different home appliances using Bluetooth and pic microcontroller. Different sensors are involved in this system to advance and make it smarter. Sensors such as temperature sensor, liquid sensors, humidity sensor etc. can be used.

scholarly journals Privacy-Aware Human-Detection and Tracking System Using Biological Signals

2019 ◽  
Vol E102.B (4) ◽  
pp. 708-721
Author(s):  
Toshihiro KITAJIMA ◽  
Edwardo Arata Y. MURAKAMI ◽  
Shunsuke YOSHIMOTO ◽  
Yoshihiro KURODA ◽  
Osamu OSHIRO
Keyword(s):  
Tracking System ◽  
Human Detection ◽  
Detection And Tracking ◽  
Biological Signals

scholarly journals Effect of Peak Tracking Methods on FBG Calibration Derived by Factorial Design of Experiment

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6169
Author(s):  
Nazila Safari Yazd ◽  
Jennifer Kawakami ◽  
Alireza Izaddoost ◽  
Patrice Mégret
Keyword(s):  
Factorial Design ◽  
Humidity Sensor ◽  
Calibration Procedure ◽  
Search Method ◽  
Effect Of Temperature ◽  
Bragg Wavelength ◽  
Peak Tracking ◽  
Peak Search ◽  
Python Programming ◽  
Temperature Strain

We present a calibration procedure for a humidity sensor made of a fiber Bragg grating covered by a polyimide layer. FBGs being intrinsically sensitive to temperature and strain, the calibration should tackle three variables, and, therefore, consists of a three-variable, two-level factorial design tailored to assess the three main sensitivities, as well as the five cross-sensitivities. FBG sensing information is encoded in the reflection spectrum from which the Bragg wavelength should be extracted. We tested six classical peak tracking methods on the results of the factorial design of the experiment applied to a homemade FBG humidity sensor. We used Python programming to compute, from the raw spectral data with six typical peak search algorithms, the temperature, strain and humidity sensitivities, as well as the cross-sensitivities, and showed that results are consistent for all algorithms, provided that the points selected to make the computation are correctly chosen. The best results for this particular sensor are obtained with a 3 dB threshold, whatever the peak search method used, and allow to compute the effective humidity sensitivity taking into account the combined effect of temperature and strain. The calibration procedure presented here is nevertheless generic and can thus be adapted to other sensors.

scholarly journals Convolutional Neural Network Using Kalman Filter for Human Detection and Tracking on RGB-D Video

2018 ◽  
Vol 12 (2) ◽  
pp. 105 ◽  
Author(s):  
Jovin Angelico ◽  
Ken Ratri Retno Wardani
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Convolutional Neural Network ◽  
Human Detection ◽  
Detection Accuracy ◽  
Tracking Accuracy ◽  
Lighting Condition ◽  
Detection And Tracking ◽  
Computation Efficiency ◽  
The Impact

The computer ability to detect human being by computer vision is still being improved both in accuracy or computation time. In low-lighting condition, the detection accuracy is usually low. This research uses additional information, besides RGB channels, namely a depth map that shows objects’ distance relative to the camera. This research integrates Cascade Classifier (CC) to localize the potential object, the Convolutional Neural Network (CNN) technique to identify the human and nonhuman image, and the Kalman filter technique to track human movement. For training and testing purposes, there are two kinds of RGB-D datasets used with different points of view and lighting conditions. Both datasets have been selected to remove images which contain a lot of noises and occlusions so that during the training process it will be more directed. Using these integrated techniques, detection and tracking accuracy reach 77.7%. The impact of using Kalman filter increases computation efficiency by 41%.

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