Smart Sensing Technology

2022 ◽  
pp. 333-366
Author(s):  
S. Palanivel Rajan ◽  
T. Abirami
2020 ◽  
Vol 2 ◽  
pp. 100030
Author(s):  
Sawaid Abbas ◽  
Coco Yin Tung Kwok ◽  
Karena Ka Wai Hui ◽  
Hon Li ◽  
David C.W. Chin ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5340
Author(s):  
Ching-Yuan Chang ◽  
En-Chieh Chang ◽  
Chi-Wen Huang

This study uses machine vision, feature extraction, and support vector machine (SVM) to compose a vibration monitoring system (VMS) for an in situ evaluation of the performance of industrial motors. The vision-based system respectively offers a spatial and temporal resolution of 1.4 µm and 16.6 ms after the image calibration and the benchmark of a laser displacement sensor (LDS). The embedded program of machine vision has used zero-mean normalized correlation (ZNCC) and peak finding (PF) for tracking the registered characteristics on the object surface. The calibrated VMS provides time–displacement curves related to both horizontal and vertical directions, promising remote inspections of selected points without attaching additional markers or sensors. The experimental setup of the VMS is cost-effective and uncomplicated, supporting universal combinations between the imaging system and computational devices. The procedures of the proposed scheme are (1) setting up a digital camera, (2) calibrating the imaging system, (3) retrieving the data of image streaming, (4) executing the ZNCC criteria, and providing the time–displacement results of selected points. The experiment setup of the proposed VMS is straightforward and can cooperate with surveillances in industrial environments. The embedded program upgrades the functionality of the camera system from the events monitoring to remote measurement without the additional cost of attaching sensors on motors or targets. Edge nodes equipped with the image-tracking program serve as the physical layer and upload the extracted features to a cloud server via the wireless sensor network (WSN). The VMS can provide customized services under the architecture of the cyber–physical system (CPS), and this research offers an early warning alarm of the mechanical system before unexpected downtime. Based on the smart sensing technology, the in situ diagnosis of industrial motors given from the VMS enables preventative maintenance and contributes to the precision measurement of intelligent automation.


2004 ◽  
Vol 11 (4) ◽  
pp. 349-368 ◽  
Author(s):  
B. F. Spencer ◽  
Manuel E. Ruiz-Sandoval ◽  
Narito Kurata

Proceedings ◽  
2017 ◽  
Vol 1 (8) ◽  
pp. 807
Author(s):  
Olimpiu Hancu ◽  
Ciprian Rad ◽  
Ciprian Lapusan ◽  
Marius Cristian Luculescu ◽  
Attila Boer

Author(s):  
Dr. Deepak Sonker ◽  
Dr. Vishal Khatri ◽  
Dr. Ranjeeta ◽  
Ms. Ambooj Yadav

Opening the door and closing the door by hands is very dangerous ,it may be the cause of getting virus if someone opens the door by his/her infected hands so, Automatic Door opening without pulling the door or pushing the door is an important aspect, it can be done by placing the sensors near by the door areas from where Sensors can detect the movement of an object within the range of sensors, after that a signal is sent to the microcontroller of Arduino by the sensors which controls the servo motor to open the gate and close the gate. We can place these kinds of sensors in Hotels, Malls, Theatres where a person needs to open the door by some other person hands or himself after installing this technology we don’t need to open the door by hands but the doors will automatically opens/close by sensing the objects within the range of infrared rays, and Ultrasonic sensors. This results shows that implementation of this smart sensing technology is cheap, effective and reliable for the systems like Hotels, Malls , shopping centers etc, it can also be used at our home .


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