Abstract: Wireless Sensor Network has grown rapidly, e.g. using the Zigbee RF module and combined with the Raspberry Pi 3, a reason at this research is building a Wireless Sensor Network (WSN). this research discusses how sensor nodes work well and how Quality of Service (QoS) from the Sensor node being analyzed and the role of Raspberry Pi 3 as an internet gateway will sending a blood pressure data to the database and displayed in real-time on the internet, from this research it is expected that patients can check the blood pressure from home and don’t need to the Hospital even data can be quickly and accurately received by Hospital Officers, doctors, and medical personnel. the purpose of this research is make a prototype to providing a blood pressure (mmHg) real-time data from systolic and diastolic data patient’s that determine patients suffering from symptoms of certain diseases, i.e, anemia, symptoms of hypertension and even more chronic diseases. this research discusses how sensor nodes work well and how Quality of Service (QoS) from the Sensor node being analyzed and the role of Raspberry Pi 3 as an internet gateway will sending a blood pressure data to the database and displayed in real-time on the internet. Furthermore, Zigbee has the task of sending Blood pressure (mmHg) data in real-time to the database and then sent to the internet from Zigbee end-device communication to ZigBee coordinator. Zigbee communication at a distance of 5 meters, RSSI simulations show a value of -29 dBm and the experiment shows a value of -40 dBm, at a distance of 100 m, RSSI shows a value of -55 dBm (simulation) and -86 dBm (experiment).

Puput Dani Prasetyo Adi and Akio Kitagawa, “ZigBee Radio Frequency (RF) Performance on Raspberry Pi 3 for Internet of Things (IoT) based Blood Pressure Sensors Monitoring” International Journal of Advanced Computer Science and Applications(IJACSA), 10(5), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100504

@article{Adi2019,
title = {ZigBee Radio Frequency (RF) Performance on Raspberry Pi 3 for Internet of Things (IoT) based Blood Pressure Sensors Monitoring},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2019.0100504},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100504},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {5},
author = {Puput Dani Prasetyo Adi and Akio Kitagawa},
}