Capstone Project
| Group | 2024-26 | Status | inprogress |
| Title | Smart First-aid Kit | ||
| Supervisor | B. Goodarzi | ||
| Description | The critical problem is that many Canadians lack the necessary skills to provide immediate first aid in emergencies, despite its potential to save lives. According to the Canadian Red Cross, around 38% of Canadians are untrained in first aid, leaving them unable to respond effectively until professional help arrives. Traditional first aid kits are designed for trained individuals, offering no guidance for those unfamiliar with first aid, nor do they include devices to assess vital signs such as blood pressure, oxygen levels, or blood glucose. Without these tools, untrained responders may struggle to identify the correct course of action in medical emergencies. Additionally, the crucial interventions made by first aid responders in the first few minutes are often undocumented, leaving gaps in vital information when patients reach the hospital.
The proposed solution is a smart first aid kit equipped with medical devices (ECG, blood pressure monitor, glucometer, and oximeter) and an AI-powered system. This kit would guide users through medical emergencies by displaying vital sign readings on a screen and offering real-time, voice-activated instructions tailored to the situation. The AI system would record vital data and user interactions, providing a printed report to be handed over to medical professionals. This would ensure that critical information from the initial response is documented, improving the patient treatment and diagnosis upon arrival at the hospital. |
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| Student Requirement | Prerequisite Knowledge: o Basic knowledge of medical readings (e.g., how blood pressure and glucose levels are measured and interpreted). o Familiarity with first-aid practices (e.g., CPR techniques). o Understanding of IoT (Internet of Things) concepts for sensor integration and data communication. Software Skills: o Proficiency in Python or C for programming microcontrollers. (ENGR 290, COEN 390) o Experience with AI and voice recognition tools (Python libraries like Speech Recognition) (COMP 472) o Familiarity with GUI development for designing the user interface (SOEN 357) o Experience with hardware integration and real-time data display (ELEC 242, ELEC 342) | ||
| Tools | Test Equipment: o Medical sensors (blood pressure monitor, glucose meter, pulse oximeter). o Voice recognition testing system. o Printing hardware for small-scale report generation. - Software: o AI/ML software for voice recognition and response (e.g., TensorFlow, GPT-based models). o Embedded systems software for sensor data collection (e.g., Arduino or Raspberry Pi). o Medical data analysis software (e.g., Python libraries like Pandas and NumPy for processing health readings). o Software for report generation and printing. o Graphical User Interface (GUI) for displaying measurements and warnings on the kit screen. - Hardware: o Display screen for showing real-time body readings. o Microcontrollers for sensor integration (e.g., Arduino or Raspberry Pi). o Small Printer for generating small physical reports. o Voice input device (microphone) for AI-based interaction. o Power supply and backup battery. o Enclosure/casing for the first aid kit, designed to house all components. | ||
| Number of Students | 6 | ||
| Students | Michel Farah, Jaskirat Kaur, Kareem Chamsi, Beshoi Khair, Marc Jenno, Mina Wahba | ||
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