IoT-based platform for Intensive Care Unit Remote Monitoring and Controlling
The Health Care system is the most important factor in the development of a country. However, the current pandemic has greatly affected the health sector. Day by day, the number of COVID-19 patients is increasing exponentially. According to the news given by the worldmeter, up to January 31, 2021, m
2025-06-28 16:28:24 - Adil Khan
IoT-based platform for Intensive Care Unit Remote Monitoring and Controlling
Project Area of Specialization Internet of ThingsProject SummaryThe Health Care system is the most important factor in the development of a country. However, the current pandemic has greatly affected the health sector. Day by day, the number of COVID-19 patients is increasing exponentially. According to the news given by the worldmeter, up to January 31, 2021, more than 103,132,381 people were infected and more than 2,229,405 have died worldwide. COVID patients need proper ventilation due to severe issues of the respiratory system. To facilitate the patients the maximum number of ventilators are occupied by them and countries are facing the problem of ventilators shortage. Ventilators are costly and so not available in huge amounts in any country. Other patients are also suffering due to lack of ventilators and also their visits to hospitals are not safe in this situation. Doctors and all related staff are on the front line and their health is at great risk so it draws our attention to design a ventilator having two characteristics. Firstly it should be cost-effective so that it would be readily available. Secondly, it should be remotely monitored which will help in controlling the ventilator through the internet anytime and anywhere and the availability of doctors at the patient’s location is not necessary. Patients will be monitored continuously through the internet and guardians will be informed about the patient’s health condition. Patients will be treated in effective environments and the risk of spread of the virus will also be reduced.
The implementation of the project consists of the following: (1) Raspberry-pi based platform for interfacing various sensors and actuators required for ventilation. (2) Breathing (O2) control using the proper level of various constituents of Air while maintaining the required pressure level. (3) Controlling of inhaling and exhale valves based on sensor data. (4) Proper flow control of air mixture. (5) Mathematical modeling and design of airbag and motor control mechanism for required breathing rate of the patient. (6) Machine learning-based decision making. (7) IoT and Web-based platform for remote monitoring of the ventilator Patient. (8) History record of the patient health.
The proposed system will help the physicians and patient guardians to monitor the patient's health condition and get alert messages at any time and anywhere.
Project Objectives- Sensors and Actuators Interfacing: Acquiring data of patient’s health parameters such aspulse rate, oxygen saturation in blood, temperature, blood pressure and all others required using health sensors to make decision for providing proper level of oxygen ventilation.
- Breathing Control Unit: Maintaining air mixture quality and its steady flow towards patient by timely controlling of valves according to patient’s lungs and health condition.
- Health Data Management: Data storage in data base with proper patient attribution and applying machine learning algorithms for decision making based on which actuation is performed.
- Web-IoT based Client Application for Remote control and monitoring: Display real time data of sensors and actuators using IoT and Web based platform. Remote monitoring of ventilator patient while maintaining patient’s health record and sending alert messages to patient’s guardian in critical situations.
Figure 1: Overview of the proposed IoT-enabled Ventilation System for Remote ICU Monitoring
Raspberry Pi is used as the main controller and IoT device. Pulse Oximeter and Pressure sensors are in interfaced with the Raspberry Pi to read the Oxygen saturation and pressure during inhalation and expiration. The actuators attached to the Raspberry Pi are stepper Motor and 2 analogue proportional valves for oxygen level control and pressure control.
There are two modes of operations, Automatic Mode and Manual Mode of ventilator. In Automatic mode the actuators are controlled by the trained machine learning model for optimal parameters for the patients. The model is decision depends upon the patients’ health parameter being monitored by sensors. In Manual mode of operation user inputs the value of Breath Per Minute (BPM), Tidal Volume (TV), Positive end-expiratory pressure (PEEP), Inhale Pressure and FiO2 level. In this mode of operation, the ventilator provides the set parameter by the user. All the entries of the patient health parameters are being saved in the database of Raspberry Pi to be used to display over IoT, help train Artificial Intelligence model and as a record of patient medical history.
Stepper Motor is used to provide accurate Breath Per Minute(BPM) by compressing and decompressing the Bag Valve Mask (BVM). SpO2 sensor is read the value of the patient’s oxygen saturation. The valve between the oxygen tank and BVM is used to controlled Fi02 level entering in the patient. Pressure sensor is used to measure the inhale and exhale pressure of the patient. Pressure valve is placed between BVM and the mouth piece of the patient to control the pressure level of the patient. There is safety protocol if the patient expires which will alert the concerning staff for an emergency.
All the entries are saved on the database are transmitted to IoT platform by MQTT protocol. From the webpage the physician is allowed to see and control the ventilator settings. Enabling the ventilator to be monitored and controlled remotely.
Figure 2: Overview of the proposed IoT-enabled Ventilator System for Assisting the COVID Patients
Figure 3: The propsed project implementation process flow block diagram
Figure 4: Flow chart of the proposed IoT-enabled Ventilator System
Figure 5: Web-IoT based client application for remote monitoring of the patient
Benefits of the Project- Automatic control - This project is Remote controlling; Anywhere We can have checked patient data with the help of IOT.
- Easy to used-. It can be supplied around the rural area hospitals for immediate medication with cost efficiency and risk avoidance. Anyone can operate it as no need to study or training of ventilation rules like ICU ventilator
- COVID-19 Pandemic –With help of remote monitoring, less attraction between patient and Doctorless chances to spread corona virus.
- Low Cost- In COVID-19 Pandemic we constructing a low-cost, open-source mechanical ventilator aims to mitigate the effects of this shortage in our regions.
- Reduced Errors – IoT allows for the accurate collection of data, automated workflows and minimized waste, but most importantly it reduces the risk of error.
- Better patient experience – A connected healthcare system creates an environment that meets each patient’s needs. Dedicated procedures, enhanced treatment options and improved diagnosis accuracy make for a better patient experience.
- Improved disease management – With real-time data healthcare providers can continuously monitor patients. This means that they can spot any disease before it spreads and becomes serious.
- This project can be further for
- Saving lives
- Efficient and Saves Time
- Saves Money
- Better Quality of Life
• Breathing Control Ventilation System for Respiratory Issue (COVID-19) Patients
- Respiratory Rate (RR) (breaths per minute): between 6 – 40. Note that the low RRs of 6 – 9 are only applicable to Assist Control.
- Tidal Volume (TV) (air volume pushed into lung): between 200 – 800 mL based on patient weight.
- I/E Ratio (inspiratory/expiration time ratio): recommended to start around 1:2; best if adjustable between range of 1:1 – 1:4.
- PEEP of 5–15 cm H2O required; many patients need 10–15 cmH2O.
• IoT Enabled Monitoring and Controlling of COVID-19 Patient
- To save patients health parameters to database.
- To display the parameters to web page over IoT platform.
- To train Artificial Intelligence model for optimal conditions of patient
- To control the parameters automatically using AI platform.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 78000 | |||
| Raspberry Pi Development Kit | Equipment | 1 | 15000 | 15000 |
| BVM bag | Equipment | 2 | 5000 | 10000 |
| Pressure Sensor | Equipment | 1 | 5000 | 5000 |
| SpO2 Sensor | Equipment | 1 | 2000 | 2000 |
| 1/4 | Equipment | 2 | 5000 | 10000 |
| Small gears-G236(48 tooth,3 in. pitch dia., 14.5° pressure angle, 0.25 | Equipment | 1 | 2000 | 2000 |
| Big Gears-G239(30 tooth, 1.875 in. pitch dia., 14.5° pressure angle. 0 | Equipment | 2 | 3500 | 7000 |
| Metal Plates | Equipment | 1 | 1000 | 1000 |
| Clamps | Equipment | 2 | 1500 | 3000 |
| Stepper Motor NEMA34 | Equipment | 2 | 5000 | 10000 |
| Motor Driver | Equipment | 2 | 1000 | 2000 |
| Analog to Digital Converter | Equipment | 1 | 1000 | 1000 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |