The Industrial Temperature Measurement System Based on the Uncooled IRFPA Detector
Issue:
Volume 7, Issue 1, June 2019
Pages:
1-7
Received:
14 November 2018
Accepted:
13 December 2018
Published:
19 January 2019
Abstract: Most of the non-contact temperature measuring devices in the market are mainly based on dot infrared thermometers. The single machine operated instruments can only meet the requirements of temperature measurement for local temperature points, and can not feedback the temperature information and temperature direction of the whole temperature field in real time. Under the condition of low temperature, for the Commonly non-contact temperature measurement system, the reaction is not sensitive, can not keep up with the temperature change, Continuous calibration and debugging are needed in the case of changing ambient temperature, resulting in a great waste of personnel and time. In the aspect of infrared detector, the operating wavelength of the traditional infrared CCD is 0.4-1.1μm, affected by the cut-off wavelength, the error of infrared CCD is very large in industrial low temperature measurement. The operating wavelength of uncooled focal plane array infrared camera is generally between 8-14μm, which temperature measurement accuracy can reach 0.01°C under the optimum working environment. The UL01011 is most commonly used as the core photo detector in the uncooled focal plane uncooled micro-bolometer array infrared camera, we used it as the experimental photoelectric detector, Experiments showed that this method could achieve better results in practice.
Abstract: Most of the non-contact temperature measuring devices in the market are mainly based on dot infrared thermometers. The single machine operated instruments can only meet the requirements of temperature measurement for local temperature points, and can not feedback the temperature information and temperature direction of the whole temperature field i...
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Edge Computing: Applications, State-of-the-Art and Challenges
Issue:
Volume 7, Issue 1, June 2019
Pages:
8-15
Received:
10 October 2019
Accepted:
31 October 2019
Published:
15 November 2019
Abstract: The Internet of Things (IoT) is now infiltrating into our daily lives, providing important measurement and collection tools to inform us of every decision. Millions of sensors and devices continue to generate data and exchange important information through complex networks that support machine-to-machine communication and monitor and control critical smart world infrastructure. As a strategy to alleviate resource congestion escalation, edge computing has become a new paradigm for addressing the needs of the Internet of Things and localization computing. Compared to well-known cloud computing, edge computing migrates data calculations or storage to the edge of the network near the end-user. Thus, multiple compute nodes distributed across the network can offload computational pressure from a centralized data center and can significantly reduce latency in message exchanges. Besides, the distributed architecture balances network traffic and avoids spikes in traffic in the IoT network, reduces latency between edge/cloud servers and end-users, and reduces response time for real-time IoT applications compared to traditional cloud services. In this article, we conducted a comprehensive survey to analyze how edge computing can improve the performance of IoT networks. We classify edge calculations into different groups based on the architecture and study their performance by comparing network latency, bandwidth usage, power consumption, and overhead. Through the systematic introduction of the concept of edge computing, typical application scenarios, research status, and key technologies, it is considered that the development of edge computing is still in the initial stage. There are still many problems in practical applications that need to be solved, including optimizing edge computing performance, security, interoperability, and intelligent edge operations management services.
Abstract: The Internet of Things (IoT) is now infiltrating into our daily lives, providing important measurement and collection tools to inform us of every decision. Millions of sensors and devices continue to generate data and exchange important information through complex networks that support machine-to-machine communication and monitor and control critic...
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