Mert, T.U.Asadi, Farzin2024-07-122024-07-1220239.79835E+1210.1109/ELECO60389.2023.104160212-s2.0-85185823456https://doi.org/10.1109/ELECO60389.2023.10416021https://hdl.handle.net/20.500.12415/747114th International Conference on Electrical and Electronics Engineering, ELECO 2023 -- 30 November 2023 through 2 December 2023 -- -- 197135With the development of wearable sensor technologies, traceability of sports and health data has become widespread. Electrocardiography (ECG) is an important data in the detection of heart diseases and is a graphical representation of the electrical events occurring in the human heart. In this study, real-time transfer of ECG data to the cloud environment was performed with MicroPython using the ESP32 family microcontroller. MicroPython allows complex operations such as machine learning to be performed on microcontrollers with low processing power. Despite this, it seems that the number of studies conducted with MicroPython in the literature is still limited. In this study, after the ECG signal was cleared of noise with the designed software filters, the data was directed to the Amazon Web Services (AWS) cloud environment. Message Queuing Telemetry Transfer (MQTT) protocol is used for instant transmission of data to the cloud environment. In addition, ECG data was read from the cloud environment and graphs were drawn with the Python code developed on the computer. Analysis of the ECG signal was performed using available libraries. © 2023 IEEE.eninfo:eu-repo/semantics/closedAccessData TransferMicrocontrollersWearable ComputersWearable SensorsWeb ServicesWebsitesAmazon Web ServicesCloud EnvironmentsGraphical RepresentationsHealth DataHeart DiseaseHuman HeartMonitoring SystemReal-Time TransferSensor TechnologiesSports DataElectrocardiographyConference ObjectN/A