Asthma Monitoring using IoT and Edge Technology

Project Title

Asthma Monitoring using IoT and Edge Technology

Project Area of Specialization Artificial IntelligenceProject Summary

To control the escalating cost of treating chronic diseases such as the asthma, it is required that they need to self managed by the patients. The main goal of this project is to detect the severity levels of Asthmatic Patients, and people suffering from seasonal allergies. This can be done by designing filters that detect the respiratory sounds of a patient and then use that data to get further insights into the disease's condition and eventually, predict its severity. Data is acquired from various sources, such as the heart rate sensor, microphone, and a peak flow graph etc. Using some already availabe datasets of the Asthmatic patients, suitable machine learning models can be built to predict the severity and using edge computing, results can be displayed in real-time.

Project Objectives

• To provide a low cost, effective, portable and immediate health monitoring system 

• To help doctors monitor asthma patients.

• To help doctors understand if their treatment is helping reduce the severity of the disease.

• And lastly to have a positive impact on the lives of asthmatic patients.

Project Implementation Method

• It takes in the respiratory sound of the patient as input through a mobile device. Then our algorithm processes and analyzes the signal.

• We then use signal processing techniques to filter out the required sound (wheeze, cough, crackle etc)

• Lung Sound Analysis; Exploit the different features of respiratory sound signal to extract useful information. 

• Feed the extracted features to a machine learning model to classify the severity level as ‘High’, ‘Low’ or ‘Medium’.

Benefits of the Project

• Low cost
• Portable
• Quick

Technical Details of Final Deliverable

• An Android/iOS Mobile app capable of running on all smartphones and iphones, having the capability of interacting with the patient, recording their respiratory sounds, and giving back the results in real time
• An edge device based on a raspberry pi performing the same functionality
• The results include a severity level prediction, a few precautions to take, and a few suggestions to overcome the current condition

Final Deliverable of the Project HW/SW integrated systemCore Industry MedicalOther IndustriesCore Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT)Sustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	25500
Raspberry Pi 4 (4 GB)	Equipment	1	25500	25500