Open-source projects for edge computing

Keyword(s):  
Author(s):  
Ashish Joglekar ◽  
Gurunath Gurrala ◽  
Puneet Kumar ◽  
Francis C Joseph ◽  
Kiran T S ◽  
...  

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Liqiang Zhao ◽  
Guorong Zhou ◽  
Gan Zheng ◽  
Chih-Lin I ◽  
Xiaohu You ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5310
Author(s):  
Nour A. Attallah ◽  
Jeffery S. Horsburgh ◽  
Arle S. Beckwith ◽  
Robb J. Tracy

We present a new, open source, computationally capable datalogger for collecting and analyzing high temporal resolution residential water use data. Using this device, execution of water end use disaggregation algorithms or other data analytics can be performed directly on existing, analog residential water meters without disrupting their operation, effectively transforming existing water meters into smart, edge computing devices. Computation of water use summaries and classified water end use events directly on the meter minimizes data transmission requirements, reduces requirements for centralized data storage and processing, and reduces latency between data collection and generation of decision-relevant information. The datalogger couples an Arduino microcontroller board for data acquisition with a Raspberry Pi computer that serves as a computational resource. The computational node was developed and calibrated at the Utah Water Research Laboratory (UWRL) and was deployed for testing on the water meter for a single-family residential home in Providence City, UT, USA. Results from field deployments are presented to demonstrate the data collection accuracy, computational functionality, power requirements, communication capabilities, and applicability of the system. The computational node’s hardware design and software are open source, available for potential reuse, and can be adapted to specific research needs.


IEEE Network ◽  
2019 ◽  
Vol 33 (2) ◽  
pp. 166-173 ◽  
Author(s):  
Chao Yao ◽  
Xiaoyang Wang ◽  
Zijie Zheng ◽  
Guangyu Sun ◽  
Lingyang Song
Keyword(s):  

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 419 ◽  
Author(s):  
Camille Yvanoff-Frenchin ◽  
Vitor Ramos ◽  
Tarek Belabed ◽  
Carlos Valderrama

We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up. In this work, we developed a multi-language robot interface helping to evaluate the mental health of seniors by interacting through questions. Through the voice interface, the specialist can propose questions, as well as receive users’ answers, in text form. The robot can automatically interact with the user using the appropriate language. It can process the answers and under the guidance of a specialist, questions and answers can be oriented towards the desired therapy direction. The prototype was implemented on an embedded device meant for edge computing, thus it was able to filter environmental noise and can be placed anywhere at home. The proposed platform allows the integration of well-known open source and commercial data flow processing frameworks. The experience is now available for specialists to create queries and answers through a Web-based interface.


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