IoT Based Brain Hypothermia Monitoring and Controlling Management System
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Abstract
In this work, a non-invasive, selective brain cooling device is designed and manufactured. Thermoelectric
cooling elements were used and fitted inside the proposed helmet as cooling means for the head. The thermoelectric was
cooled using water circulation to make the proposed system provide a long operational time and maintain the system's
cooling rate. NTC temperature sensors are used to collect a patient’s temperature at four locations; inside the ears and on
artery temporal. By utilizing four sensors for temperature measurement, any error that can occur will have less impact on
the whole system's intended performance. Arduino microcontroller and Raspberry Pi are used for data processing and
visualization. The Raspberry Pi is used to create a server running Node-Red software, where the data will be published to
the local Wi-Fi network and the internet using MQTT protocol. The proposed ABHS achieved two main points; first, the
developed helmet is flexible and weight about 1.2 Kg, which make it suitable for all ages, second the designed watercooling
system kept the system cooling rate at maximum throughout the time required for the system to operate which is
between 24 to 72 hours.
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