The collected data shows a high level of accuracy when predicting serious critical conditions in Glucose levels. AIM ’94) has been used to train the proposed ML model. This model prediction is best practice in this chronic health domain as it has never been implemented to predicted a future forecast of the patient chart. Moreover, a Machine Learning (ML) model is implemented to predict future events where the patient might have serious issues.

The proposed solution will alert the patients’ parents or guardians of their situation when they about to reach critical conditions specially at night by sending alarms and notifications by Short Messages (SMS) along with the patients current location to up to three people. Near-Infrared (NIR) -as an optical method of the non-invasive technique - has been adopted to help diabetic patients in continuously monitoring their blood without pain. In this paper, an optimum solution to this drawback by adopting the Wireless Sensor Network (WSN)-based non-invasive strategies has been proposed. In some cases, tracking the glucose level might be a hard job especially if the patient is a child, senior, or even have several other health issues. Fingertip pricking - as the traditional method for glucose level tracking - leads patients to be distress and it might infect the skin.

To prevent this issues, diabetes patient are always advised to monitor their glucose level at least three times a day. This is due the fact that Glucose level could change drastically and lead to critical conditions reaching to death in some advance cases. This will eventually allow the users to protect their lives and the properties as well from the disaster.ĭiabetes is considered among the major critical health conditions (chronic disease) around the world. Through this system, it can help users to improve their safety standards by having immediate response in preventing accidents. Results from the test are documented and discussed. When the system detects the temperature of 40☌ or more, it will immediately display an alert notification on LCD display and simultaneously sending an SMS alert to the users upon the high raise temperature in the house. An alert message will be sent to the user via short message service (SMS) via GSM module.

An LM35 temperature sensor is used to detect the heat from the fire. The main controller used is certainly the ATmega328 which controls the home fire alert subjected to the temperature sensor. It utilizes Arduino Uno board in conjunction with ATmega328 chip. The project purposely is for house safety where the main point is to avoid the fire accidents occurred to the residents and the properties inside the house as well. This paper describes the design of a home fire alarm with Arduino-based system by means of GSM Module.

Advanced design system 2017