Wearable IoT and Geo-fencing-based Platform for Monitoring and Isolation of Severe Acute Respiratory Syndrome Patients
The pandemic disease related to Severe Acute Respiratory Syndrome (SARs) has become a more frequently active disease recently. The first and foremost critical issue in SARs disease is to diagnose it timely and cutting off the chain of transmission by isolating the patient. The challenges which are f
2025-06-28 16:36:44 - Adil Khan
Wearable IoT and Geo-fencing-based Platform for Monitoring and Isolation of Severe Acute Respiratory Syndrome Patients
Project Area of Specialization Internet of ThingsProject SummaryThe pandemic disease related to Severe Acute Respiratory Syndrome (SARs) has become a more frequently active disease recently. The first and foremost critical issue in SARs disease is to diagnose it timely and cutting off the chain of transmission by isolating the patient. The challenges which are faced with the increase in population are fewer medical facilities and the availability of medical staff in rural and urban areas for a high number of the patient due to pandemic. Due to the invasive method of treatment, SARs and currently COVID (coronavirus disease) is spreading swiftly. In this research project, we propose a non-invasive intelligent telemedicine system using wearable sensors and artificial intelligence-based technology to isolate, monitor, and Geofence the activities of the patient. The project is equipped with 4IR (fourth Industrial revolution) technologies involving W-IoT, Big Data, and Machine learning Algorithms. The objective is to select suitable and equipped sensors which can extract physiological parameters necessary for determining COVID patient and to enclose COVID patient in isolation. For remote monitoring, essential parameters are transmitted wirelessly to a centralized database for feature extraction and decision making using machine learning algorithms.
The implementation of the project consists of the following module:
1) RSSI level and GPS based Geofencing for isolation of COVID patient within a geographical area to restrict his/her movement to minimize the spread maximization.
2) Raspberry-pi-based intelligent cloud server for diagnosing and remote monitoring of SAR Patient.
3) Transmission of wearable sensors data from patient side to centralized database.
4) Real-time feature extraction from sensors data and machine learning-based model for decision making about patient health.
5) Web server-based application for patient condition and isolation activity monitoring.
6) Web of Things based Application for the real-time patient monitoring and sensor data visualization by doctors and physicians.
Project Objectives1. Interfacing sensors and actuators to extract physiological parameters for SAR patient.
2. Medical-IOT, Web-based intelligent platform for Identification among Normal Person and COVID-19 Patient.
3. Wireless RSSI level and GPS based Geofencing for SAR (COVID-19) Patient localization.
4. Webpage based visualization for remote monitoring, providing timely precautions and opinion by physicians and doctors for COVID-19 Patient.
5. Cloud server-based historical record of the Patient health data.
6. Alerting nearby Ambulance incase of critical condition.
Figure 1: Objective Diagram for Wearable IoT and Geo-fencing-based Platform for Monitoring and Isolation of Severe Acute Respiratory Syndrome Patients
Project Implementation Method Figure 2 and Figure 3 illustrate the overview of the proposed system. The system is equipped with wearable biomedical sensors and sensors for surveillance detection which are placed on left, right and chest position of patient. The physiological biomedical parameters of patient are extracted from the sensors such as ECG, Pulse Oximeter (SpO2), body temperature, respiratory sensor, accelerometer, and gyroscope. GPS sensor is installed to check and monitor the isolation, movement, and Geo-fence of the susceptible and patient. The acquired data is transmitted wirelessly using master slave configuration of Bluetooth modules to gateway i.e. Nodemcu (WiFi) to enable the Web IoT environment. However, using RSSI level of Wi-Fi and GPS, we can actuate alarm for patient to keep inside geographical (Geo-fence) area. The centralized database i.e. Raspberry pi is connected to multiple nodemcu for multiple patients monitoring. The application peripheral interfaces (API) of raspberry pi allows to extract real time wearable sensor’s data. This data is stored corresponding to multiple patients ID, age etc. Using machine learning algorithms, the patient condition is classified which is stored for maintaining historical record of patient’s health. The classified patient condition and real time sensor’s data is then sent to centralized client-based application where doctors and physicians will analyze patient’s health and recommend precautionary measures according to his/her health. These precautionary measures can be accessed by patient and patient’s guardians. In case of critical health, nearby ambulance is alarmed using GSM to secure patient’s health. Figure 4 shows the overall flow chart of the proposed system. 
Figure 2: Process Overview Diagram for Wearable IoT and Geo-fencing-based Platform for Monitoring and Isolation of Severe Acute Respiratory Syndrome Patients
Figure 3: Implemented Architectural Diagram for Wearable IoT and Geo-fencing-based Platform for Monitoring and Isolation of Severe Acute Respiratory Syndrome Patients
Figure 4: Flowchart Diagram for Wearable IoT and Geo-fencing-based Platform for Monitoring and Isolation of Severe Acute Respiratory Syndrome Patients
Benefits of the Project- WIoT and remote monitoring are applied on various applications like real time health monitoring of SARs patient and reduction of invasive methods.
- Isolation of COVID patient will cut-off the chain of disease transformation. e.g. Surveillance detection using GPS and RSSI will leads to isolation under allowed geographical area.
- This project will further utilized for:
- Safe living and free of disease environment.
- Contributing to safe infrastructure,maintenance and management.
- Reducing invasive methods which leads to improvement of safety factor of doctors and patients.
- In case of pandemic staff unavailability, it inhibits more medical facilities in the form of telemedicine technology.
- Technology development for WIoT and isolation platform for COVID patient and on-board platform for wearable sensor data acquisition APIs
- Sampling rate for biomedical sensors: 50Hz.
- GPS and RSSI level data acquisition: 1 Hz for GPS and 50Hz for RSSI.
- Web page refreshing rate of 1 Hz.
- Technology development for establishing gateway/Hardware data link between on-board raspberry Pi and wearable sensors during patient surveillance and classification.
- MQTT server (for wireless data link between patient and centralized data base).
- Master slave configuration among wearable sensors and gateway.
- Software technological developmental algorithm for patient classification and feature extraction.
- KNN, SVM and RF classifiers
- Web server and client based application for real time sensors data and patient classification visualization.
- Technical reports of implemented systems.
- Finalized achieved results in form of tables, graphs, charts and client application.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 78548 | |||
| ESP8266 nodemcu | Equipment | 2 | 500 | 1000 |
| Arduino nano | Equipment | 3 | 450 | 1350 |
| MPU6050 gyroscope accelerometer | Equipment | 1 | 275 | 275 |
| Pulse Oximeter MAX 30100 | Equipment | 1 | 350 | 350 |
| GPS module | Equipment | 1 | 1100 | 1100 |
| Temperature sensor MAX 30205 | Equipment | 1 | 1600 | 1600 |
| ECG sensor AD8232 | Equipment | 1 | 1200 | 1200 |
| Bluetooth Module | Equipment | 2 | 450 | 900 |
| Breathing/Respiration Sensor SA9311M | Equipment | 1 | 47273 | 47273 |
| Power Module for Raspberry Pi | Equipment | 1 | 1000 | 1000 |
| Raspberry Pi 3 module | Equipment | 1 | 9500 | 9500 |
| Wearable sensor jacket | Equipment | 1 | 1500 | 1500 |
| Rechargeable Power Module for wearable controllers | Equipment | 3 | 500 | 1500 |
| Thesis Copies, Papers Printing, and Posters | Miscellaneous | 5 | 2000 | 10000 |