Artificial Intelligence Monitor and Indicate To 108 Ambulance from Remote Area Using Deep Learning and ESP8266 Of the Patient Health -Heart Rate and ECG Signal

The contactless BPM and ECG signal measurement using web cameras gives greater potential for the medical team using the remote photoplethysmography technology. In research areas this contactless rPPG technology plays a major role in medical as well as industrial purpose. Many new methods were updated by using the deep learning algorithm for the remote Heart measurement of the patients. This paper shows a detailed analysis of the hybrid deep learning algorithm for capturing the remote heart measurement and ECG signal of the patient in the remote area. The computer vison technology supports detecting the face from the live video and the hybrid deep learning algorithm supports to capture the fluctuating signal as per the patient expression through their faces. Once the heart rate captured through Artificial intelligence technology the abnormal and normal BPM was converted as analog signal through the Arduino Uno. In this work the IoT plays a major part for the wireless communication between the remote area patient and the hospital (108 AMBULANCE). The Light signal was detected by a light sensor and an ESP8266 Wi-Fi module combines with the BLYNK cloud to give the alert emergency message to the nearer hospital from the remote area about the patient health. The alert message was given to the hospital through E-mail as well as through the mobile phone message with the help of Wi-Fi device ESP8266. This work gives accurate measurement of the heart rate and ECG signal and monitor as well as indicate to nearer hospital from the remote area.