Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57023
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dc.contributor.authorOran Chieochanen_US
dc.contributor.authorAnukit Saokaewen_US
dc.contributor.authorEkkarat Boonchiengen_US
dc.date.accessioned2018-09-05T03:34:05Z-
dc.date.available2018-09-05T03:34:05Z-
dc.date.issued2017-12-15en_US
dc.identifier.other2-s2.0-85045952727en_US
dc.identifier.other10.1109/ICCAIS.2017.8217588en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85045952727&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/57023-
dc.description.abstract© 2017 IEEE. This research aims to prototype a small smart off-grid solar cell system. o provide an alternative electrical supply for a smart Lingzhi mushroom farm. This research applied the use of IOT with voltage and current sensors to measure and monitor the voltage of solar cell charging, amp (ampere) of current charging from the solar panel into a battery and (ampere) of current loading from a battery to the irrigation systems (fog and sprinkler pumps). Voltage and current data processed through Blynk was developed as an IOT cloud service. Data was stored into the Blynk and displayed on mobile devices in real time. The functional status (switching on and off for periods of time, current consumption) pushes notifications through Blynk IOT cloud service on the Blynk application. The equipment and tools used in this research were NodeMCU, voltage and current sensors, relay modules, DC sprinkler, and fog pumps. A small off-grid solar cell was applied. The solar cell system consists of a charger, battery, and solar panels. The IOT cloud used is Blynk. The results of the research shows that using IOT with voltage and current sensors enhances the prototype of a smart farming as an alternative and green electrical resource.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.subjectPhysics and Astronomyen_US
dc.titleInternet of things (IOT) for smart solar energy: A case study of the smart farm at Maejo Universityen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2017 International Conference on Control, Automation and Information Sciences, ICCAIS 2017en_US
article.volume2017-Januaryen_US
article.stream.affiliationsRajabhat Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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