Um Mecanismo de Compressão de Dados Local em Tempo Real Energeticamente Eficiente para Redes WBANs

• Cainã Passos UFPR
• Aldri Santos UFPR

DOI: https://doi.org/10.5753/sbrc_estendido.2021.17172

Abstract

Among the networks for health care monitoring, we highlight wireless body networks (WBANs), which enable continuous and real-time monitoring of physiological signals. However, this monitoring results in the overuse of data transmission, drastically affecting the power consumption of the devices. This dissertation investigated these issues and has proposed the GROWN system, a hybrid approach to local data compression to reduce the redundancy of information in the data transmission and reduce the energy consumption of the devices, through WSN local data compression methods. GROWN was evaluated through experimentation and achieved a decrease in the energy consumption of the devices in face of transmitted signals and an increase in network lifetime.

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