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E-healthcare applications are essential for smart cities, requiring energy-efficient solutions to successfully fulfilling the applications requirements and to meet sustainability goals. Thus, energy-efficient methods were applied in the Medical Internet of Things (MIoT). This work proposes an MIoT system integrating energy harvesting and data compression. It includes nine e-healthcare applications (Glucose, Concentration GC, Blood Flow BF, Electrocardiography ECG, Respiratory Rate RR, Pulse Rate PR, Blood Pressure BP, Blood PH, Body Temperature BT, and video consultation). The MIoT transmits data wirelessly to healthcare centers, but large data, especially video data causes can burden the wireless communication channel as well as increases energy consumption, and delays. To address this issue, hybrid energy harvesting method (TEG + indoor PV cells) with data compression is applied, enhancing system performance and sustainability. After run a suitable MATLAB code, the data is observed to be reduced to only 33% and the transmission unit energy consumption is reduced to 1/3 the original consumption, while the proposed energy harvesting of (4147.1 plus 216) J/day after 3:1 compression can cover 95.62% of each MIoT device’s unit consumption.

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Sustainable Medical Internet of Things Using Data Compression and Hybrid Energy Harvesting Methods

  • 会议论文

  • 发表日期：

    2026年

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  • Amina Gh. Abdullah,
  • Mohammad T. Yaseen,
  • Firas S. Alsharbaty

摘要

E-healthcare applications are essential for smart cities, requiring energy-efficient solutions to successfully fulfilling the applications requirements and to meet sustainability goals. Thus, energy-efficient methods were applied in the Medical Internet of Things (MIoT). This work proposes an MIoT system integrating energy harvesting and data compression. It includes nine e-healthcare applications (Glucose, Concentration GC, Blood Flow BF, Electrocardiography ECG, Respiratory Rate RR, Pulse Rate PR, Blood Pressure BP, Blood PH, Body Temperature BT, and video consultation). The MIoT transmits data wirelessly to healthcare centers, but large data, especially video data causes can burden the wireless communication channel as well as increases energy consumption, and delays. To address this issue, hybrid energy harvesting method (TEG + indoor PV cells) with data compression is applied, enhancing system performance and sustainability. After run a suitable MATLAB code, the data is observed to be reduced to only 33% and the transmission unit energy consumption is reduced to 1/3 the original consumption, while the proposed energy harvesting of (4147.1 plus 216) J/day after 3:1 compression can cover 95.62% of each MIoT device’s unit consumption.