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) 
Perez, R., Correia, S. & Valderi, R. (2021). Lossless compression scheme for efficient GNSS data transmission on IoT devices. In International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021. Cape Town: IEEE.
Exportar Referência (IEEE) 
P. Rafael et al.,  "Lossless compression scheme for efficient GNSS data transmission on IoT devices", in Int. Conf. on Electrical, Computer, and Energy Technologies, ICECET 2021, Cape Town, IEEE, 2021
Exportar BibTeX 
@inproceedings{rafael2021_1730765843083,
	author = "Perez, R. and Correia, S. and Valderi, R.",
	title = "Lossless compression scheme for efficient GNSS data transmission on IoT devices",
	booktitle = "International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021",
	year = "2021",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/icecet52533.2021.9698642",
	publisher = "IEEE",
	address = "Cape Town",
	organization = ""
}
Exportar RIS 
TY  - CPAPER
TI  - Lossless compression scheme for efficient GNSS data transmission on IoT devices
T2  - International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021
AU  - Perez, R.
AU  - Correia, S.
AU  - Valderi, R.
PY  - 2021
DO  - 10.1109/icecet52533.2021.9698642
CY  - Cape Town
AB  - Wireless data transmission is one of the most energy-consuming tasks performed on embedded devices, being a crucial feature of battery-powered Internet of Things (IoT) applications. The present work proposes a new methodology to reduce the energy footprint of GNSS-based sensors by decreasing the amount of transmitted data applying a lossless compression strategy. Online trajectory data is structured through a pre-processing stage without information loss and posteriorly com-pressed through standard lossless algorithms. Simulations are performed considering different trajectory shapes, comparing the proposed schema with traditional compression methods without the proposed pre-processing stage. The results show that the proposed scheme can reach lower compression rates, reducing embedded IoT devices' energy footprint. 
ER  -