Development of an Artificial Vision System for Real-Time Monitoring of Cow Breathing Rate

2009 ◽  
Author(s):  
Raphael Linker ◽  
Vladimir Kushnir
Keyword(s):  
Real Time ◽  
Vision System ◽  
Artificial Vision ◽  
Breathing Rate ◽  
Real Time Monitoring

Fast-response ionogel humidity sensor for real-time monitoring of breathing rate

2019 ◽  
Vol 3 (3) ◽  
pp. 484-491 ◽  
Author(s):  
Songhua Xiao ◽  
Jianxia Nie ◽  
Rou Tan ◽  
Xiaochuan Duan ◽  
Jianmin Ma ◽  
...  
Keyword(s):  
Ionic Liquids ◽  
Real Time ◽  
Humidity Sensor ◽  
Fast Response ◽  
Breathing Rate ◽  
Real Time Monitoring ◽  
Silica Network ◽  
Humidity Sensors ◽  
Human Breath

Ionogel-based chemoresistive humidity sensors have been successfully fabricated through ionothermal assembly of ionic liquids into a silica network, which exhibited superior humidity performances. Fast substantial impedance changes were observed with changing humidity for real-time monitoring of human breath.

scholarly journals Artificial vision system for object classification in real time using Raspberry Pi and a Web camera

2021 ◽  
pp. 20-25
Author(s):  
Tomás Serrano-Ramírez ◽  
Ninfa del Carmen Lozano-Rincón ◽  
Arturo Mandujano-Nava ◽  
Yosafat Jetsemaní Sámano-Flores
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Vision System ◽  
Low Cost ◽  
Artificial Vision ◽  
Maintenance Cost ◽  
Raspberry Pi ◽  
Smart Cameras ◽  
Suggested Technique ◽  
Web Camera

Computer vision systems are an essential part in industrial automation tasks such as: identification, selection, measurement, defect detection and quality control in parts and components. There are smart cameras used to perform tasks, however, their high acquisition and maintenance cost is restrictive. In this work, a novel low-cost artificial vision system is proposed for classifying objects in real time, using the Raspberry Pi 3B + embedded system, a Web camera and the Open CV artificial vision library. The suggested technique comprises the training of a supervised classification system of the Haar Cascade type, with image banks of the object to be recognized, subsequently generating a predictive model which is put to the test with real-time detection, as well as the calculation for the prediction error. This seeks to build a powerful vision system, affordable and also developed using free software.

A Knowledge-Based Real-Time Vision System for Monitoring the Inside of a Fluid Bed Heat Exchanger Chamber

2018 ◽  
Vol 28 (09) ◽  
pp. 1249-1265
Author(s):  
HyungJun Kim
Keyword(s):  
Image Processing ◽  
Heat Exchanger ◽  
Real Time ◽  
Vision System ◽  
Thermal Power ◽  
Experimental Results ◽  
Image Analysis System ◽  
Real Time Monitoring ◽  
Knowledge Based ◽  
Fluid Bed

In this paper, we present a vision system with a special camera for knowledge-based real-time monitoring of the inside of a fluid bed heat exchanger (FBHE) chamber in a thermal power plant. With the proposed system, it is possible to monitor the internal flux condition and analyze the inner temperature of a chamber. Due to the fact that the mixture of coal and sand inside a chamber flows by very quickly, there is an immense amount of smoke and dust, which make it difficult to capture images and analyze an existing system. An adaptive average method is proposed here to observe the background internal environment of an FBHE chamber. The experimental results show that real-time monitoring is possible, even under hot and dusty conditions. Preliminary experimental results confirm expectations about the possibility and effectiveness of the developed device for commercialized real-time monitoring systems. They demonstrate that a single camera with embedded image processing software can concurrently analyze the degree of fluidization of a mixture and the temperature of the chamber inside, even in extremely harsh and hazardous conditions. We aim to eventually develop an image analysis system that combines image processing and knowledge engineering techniques.

Real-Time Monitoring Station for Production Systems

2013 ◽  
Vol 837 ◽  
pp. 334-339 ◽  
Author(s):  
Grzegorz Ćwikła
Keyword(s):  
Real Time ◽  
Production System ◽  
Production Management ◽  
Vision System ◽  
Monitoring Station ◽  
Research Station ◽  
Manufacturing Execution System ◽  
Real Time Monitoring ◽  
Line Production ◽  
Production Monitoring

Real-time monitoring of the flow of materials, semi-completed and completed products during production process is necessary practice for every company because of need for optimal production management. Identification of technological operations, parts, products and persons responsible for any production stage is possible using means of processes control devices and automatic identification systems. Paper describes the in-line monitoring station designed for tests of real-time production monitoring methods. Available sources of information are RFiD, bar codes, and vision system. These data sources are integrated into the in-line production monitoring station. Modular production system model or small production system can be placed under the In-line station as an object of monitoring. Advanced PLC integrates control over subsystems and allows communication between hardware and software components of data acquisition system. Data acquired from the in-line research station is stored in a dedicated database, then processed and analysed using MES (Manufacturing Execution System) software.

1618: Real-Time Monitoring of Nitric Oxide and Blood Flow During Ischemia-Reperfusion in the Rat Testis

2006 ◽  
Vol 175 (4S) ◽  
pp. 521-521
Author(s):  
Motoaki Saito ◽  
Tomoharu Kono ◽  
Yukako Kinoshita ◽  
Itaru Satoh ◽  
Keisuke Satoh
Keyword(s):  
Nitric Oxide ◽  
Blood Flow ◽  
Real Time ◽  
Ischemia Reperfusion ◽  
Real Time Monitoring ◽  
Rat Testis
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