Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Santos, D., Mataloto, B. & Ferreira, J. C. (2019). Data center environment monitoring system. In CCIOT 2019: Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things. (pp. 75-81). Tokyo, Japan: Association for Computing Machinery.
Exportar Referência (IEEE)
D. Santos et al.,  "Data center environment monitoring system", in CCIOT 2019: Proc. of the 2019 4th Int. Conf. on Cloud Computing and Internet of Things, Tokyo, Japan, Association for Computing Machinery, 2019, pp. 75-81
Exportar BibTeX
@inproceedings{santos2019_1775812487334,
	author = "Santos, D. and Mataloto, B. and Ferreira, J. C.",
	title = "Data center environment monitoring system",
	booktitle = "CCIOT 2019: Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things",
	year = "2019",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1145/3361821.3361824",
	pages = "75-81",
	publisher = "Association for Computing Machinery",
	address = "Tokyo, Japan",
	organization = "ACM",
	url = "https://dl.acm.org/doi/proceedings/10.1145/3361821"
}
Exportar RIS
TY  - CPAPER
TI  - Data center environment monitoring system
T2  - CCIOT 2019: Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things
AU  - Santos, D.
AU  - Mataloto, B.
AU  - Ferreira, J. C.
PY  - 2019
SP  - 75-81
DO  - 10.1145/3361821.3361824
CY  - Tokyo, Japan
UR  - https://dl.acm.org/doi/proceedings/10.1145/3361821
AB  - The Internet of things (IoT) is applied to many cases in the smart cities topic. We apply an IoT-developed platform using LoRa communication to a Data Center to understand temperature behavior within a concentration of servers and the working behavior of these server machines. We describe our work as an IoT platform to measure temperature, humidity, and energy consumption in these data centers. In the end, the gradient temperature was found in the rack, and the increasing temperature is correlated with energy consumption and the backup routines in the night. Our developed approach can be used to understand CPU usage and related temperature and the energy consumption.
ER  -