Energy Consumption Improvement of a Healthcare Monitoring System: Application to LoRaWAN

• Published in: IEEE sensors journal Vol. 22; no. 7; pp. 7288 - 7299
• Main Authors: Taleb, Houssein, Nasser, Abbass, Andrieux, Guillaume, Charara, Nour, Cruz, Eduardo Motta
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Biomedical monitoring; Blood pressure; Body area networks; Early warning systems; Electronics; Energy consumption; Engineering Sciences; EWS; Fuzzy control; fuzzy expert system; Fuzzy logic; Health care; Heart rate; IoT; Logic gates; LoRa; LoRaWAN; LPWAN; medical applications; Medical personnel; Medical services; Monitoring; Optimization; Other; Oxygen content; Physicians; Power consumption; Reference systems; Remote monitoring; Sensors; Telemedicine; WBAN; Wireless communication; Wireless communications; Wireless networks; Wireless sensor networks; wireless technologies; EWS; wireless technologies; LoRaWAN; Medical services; IoT; Wireless communication; WBAN; Wireless sensor networks; medical applications; LPWAN; fuzzy expert system; LoRa; Logic gates; Sensors; Biomedical monitoring; Monitoring
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2022.3150716

Recent advances in wireless communication technologies are having a great impact on people's life, especially in the field of healthcare industry that provides a remote monitoring enabling medical staff to follow up the patient and diagnose his disease. LoRa wireless technology is becoming one of the most energetic effective solutions for Wireless Body Area Networks (WBANs) communications. In this work, we propose a LoRa-based low power healthcare WBAN platform called HeaLoRa for an adaptive patient monitoring process. Physicians can remotely monitor patient's temperature, oxygen saturation level, blood pressure and heart rate to prevent any abnormality. Moreover, data acquisition and transmission are controlled based on a power consumption optimization strategy aiming to reduce redundant data. Based on the Early Warning Score (EWS), the system configuration is dynamically adapted, using a Fuzzy logic controller that makes the decision about the system sleep mode duration and the sent data rate. Furthermore, an analytical model of the energy consumption for acknowledged LoRa transmission is presented in this paper. The graphical abstract of the paper illustrates a medical application of a wireless body area network system where LoRa technology is used to transmit the data to a gateway then the data is transmitted to the doctor using IP based technology. By comparing with a reference system, the simulation results indicate that our system consumes 3 to 10 times less of energy depending on the studied scenario.