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https://github.com/shashaaankkkkk/sih2024-tilchattaas
SIH2024 idea Solutions
https://github.com/shashaaankkkkk/sih2024-tilchattaas
sih2024
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SIH2024 idea Solutions
- Host: GitHub
- URL: https://github.com/shashaaankkkkk/sih2024-tilchattaas
- Owner: shashaaankkkkk
- Created: 2024-09-30T17:09:42.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-10-28T08:03:46.000Z (about 2 months ago)
- Last Synced: 2024-10-28T09:29:48.960Z (about 2 months ago)
- Topics: sih2024
- Homepage:
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# SIH 2024 - Tilchattaas: Eldicare - AI-Enabled Fall Prevention System for Elderly
### Smart India Hackathon 2024
- **Problem Statement ID**: SIH1580
- **Title**: Wearable Sensor with Artificial Intelligence for Fall Prevention in Elderly People
- **Theme**: MedTech / BioTech / HealthTech
- **Category**: Hardware
- **Team ID**: 18731
- **Team Name**: Tilchattaas
## Project Overview
Eldicare is a wearable, AI-powered system designed to prevent falls among the elderly. This device uses advanced sensors, including a gyroscope, accelerometer, SPO2, and heart rate sensors, to provide real-time monitoring and alert caregivers during emergencies.
## Key Features
- **Fall Prediction**: Detects and predicts falls, immediately alerting caregivers.
- **Vital Monitoring**: Tracks heart rate and oxygen saturation (SPO2) in real-time.
- **Emergency Button**: Allows the user to send an alert manually if needed.
- **Smart Home Integration**: Connects with emergency alarms and smart home systems.
## Flowchart of Working
```mermaid
flowchart TD
Start[Wearable Device Startup]:::start
Start --> Init[Initialize Sensors]:::process
Init --> Check{Sensor Status Check}:::decision
Check -- "Normal" --> Monitor[Monitor User's Vital Signs]:::monitor
Check -- "Abnormal" --> Alert[Trigger Alert System]:::alert
Monitor --> Movement{Movement Detected?}:::decision
Movement -- "Yes" --> Analyze[Analyze Movement Pattern]:::process
Movement -- "No" --> Monitor
Analyze -- "Fall Detected" --> Alert
Analyze -- "Normal Movement" --> Monitor
Alert --> SendAlert[Send Alert to Caregiver]:::alert
SendAlert --> Location[Share Real-Time Data]:::output
Alert --> UserResponse{User Response?}:::decision
UserResponse -- "Emergency Button Pressed" --> SendAlert
UserResponse -- "No Response" --> Escalate[Escalate to Emergency Services]:::alert
Escalate --> Notify[Notify Family/Care Facility]:::output
Monitor -- "Healthy" --> Loop[Continue Monitoring]:::monitor
Loop --> Check
%% Color classes suitable for both themes
classDef start fill:#2E86C1,color:#FFFFFF,stroke:#333,stroke-width:2px; %% Dark blue for start
classDef process fill:#58D68D,color:#000000,stroke:#333,stroke-width:1px; %% Green for processes
classDef decision fill:#F4D03F,color:#000000,stroke:#333,stroke-width:1px; %% Yellow for decisions
classDef monitor fill:#AF7AC5,color:#FFFFFF,stroke:#333,stroke-width:1px; %% Purple for monitoring
classDef alert fill:#E74C3C,color:#FFFFFF,stroke:#333,stroke-width:1px; %% Red for alerts
classDef output fill:#5DADE2,color:#000000,stroke:#333,stroke-width:1px; %% Light blue for outputs
```
## Technical Approach
- **Gyroscope & Accelerometer**: Measures body orientation (X, Y, Z axis) and detects rapid movements or instability.
- **Auto-Reboot**: Prevents false readings by resetting the device periodically.
- **GSM Module**: Ensures connectivity and emergency alerts, even without a smartphone.
## Challenges & Solutions
- **Data Reliability**: Custom dataset development for accurate fall detection.
- **False Readings**: Mitigated by periodic auto-reboots.
- **Communication**: GSM integration ensures connectivity without requiring a smartphone.
## Demo of Android App
https://github.com/user-attachments/assets/2b0fa7b2-f813-4a12-aa6c-b92efee35c8e
The Android app complements the wearable device by displaying real-time data, providing alerts to caregivers, and tracking the user's health status. Key app features include:
- **Real-Time Monitoring**: Displays current vital signs and movement data.
- **Alert Notifications**: Caregivers receive instant alerts in case of a fall or emergency.
- **Emergency Contact Integration**: Allows quick access to emergency contacts.
- **History Tracking**: Logs previous alerts and health data for review.
## Benefits and Impact
- **Increased Safety**: Reduces fall risk, increasing confidence in daily activities.
- **Lower Healthcare Costs**: Minimizes fall-related hospital visits.
- **Caregiver Support**: Automated alerts reduce monitoring strain on caregivers.
- **Enhanced Independence**: Enables elderly individuals to live independently.
- **Health Monitoring**: Early detection of potential health issues.
- **Affordable and Scalable**: Suitable for homes and care facilities.
## Research and References
- GitHub Repository: [SIH2024-Tilchattaas](https://github.com/shashaaankkkkk/SIH2024-Tilchattaas)
- Relevant Research:
- [HealthResearch on Fall Risks](https://journals.lww.com/jtrauma/abstract/2006/02000/a_simple_fall_in_the_elderly__not_so_simple.3.aspx)
- [NIH Study on Fall Prevention](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213836/)
- Google Books: _Promoting Health and Wellness in the Geriatric Patient_ by David A Soto