Smart Mask
For a big organization or university, it is difficult to monitor all its employees or students and there is always a danger that any person with COVID symptoms may enter in the organization. Mostly people use low-cost disposable masks, these masks are not enough sufficient to stop the transmiss
2025-06-28 16:35:35 - Adil Khan
Smart Mask
Project Area of Specialization Internet of ThingsProject SummaryFor a big organization or university, it is difficult to monitor all its employees or students and there is always a danger that any person with COVID symptoms may enter in the organization. Mostly people use low-cost disposable masks, these masks are not enough sufficient to stop the transmission. The smart mask will detect sneezing, cough with the help of machine learning algorithms. It will measure ambient Exhaled Breath Parameters, ambient environmental parameters and active sterilization of the mask. It will assign unique id to each person in the organization premises and display them on in the control room. System will show alert when someone found with COVID symptoms.
Project Objectives- Measurement of ambient Exhaled Breath Parameters.
- Measurement and comparison of ambient environment parameters.
- Transmitting Temp, Humidity and WearerI.D. through iBeacon protocol for contact-tracing over BLE.
- Deploying real-time cough & sneeze detection ML model build through edge-impulse.
- Active sterilization of the mask through 2x2 twill weave Carbon-fiber mesh heating.
- Remote monitoring of all persons
The Arduino Nano 33 BLE Senser contains following features
1) Microphone to capture and analyse sound in real time
2) 9-axis Inertial Measurement Unit
3) Temperature, Humidity & Barometric sensor for getting highly accurate measurements of the environmental conditions
4) Gesture , Proximity, Color and Intensity sensor
The communications chipset on the Nano 33 BLE Sense can be both a BLE and Bluetooth client and host device. Something pretty unique in the world of microcontroller platforms, with an added possibility of running Edge Computing applications (AI) on it using TinyML. We can create your machine learning models using TensorFlow Lite and upload them to your board using the Arduino IDE.
The initial experiment will be done utilizing carbon-fiber tape that generated temperatures above 50 degrees celsius, a 2x2 twill weave CF will be used at varying voltages starting from 3V upto 9V,).
Sensed parameters will be shared to the web server, where results will be generated using Tensor Flow.
Benefits of the Project-
Reusable Self-sanitizing Mask
-
Realtime monitoring
- Protection from COVID
The project will be able to measure vital sign of COVID-19,

| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 79500 | |||
| Raspberry pi 4 | Equipment | 1 | 25000 | 25000 |
| Arduino Nano BLE | Equipment | 2 | 8000 | 16000 |
| Breathing Sensor | Equipment | 1 | 4000 | 4000 |
| Sparkfun Environmental Breakout | Equipment | 1 | 8500 | 8500 |
| Batteries | Equipment | 1 | 1000 | 1000 |
| Wires, vibrating disk, | Miscellaneous | 1 | 10000 | 10000 |
| OMRON MEMS Thermal Sensors D6T-44L-06 | Equipment | 1 | 15000 | 15000 |

