At Nida Ai, we have developed an advanced Fall Detection & Emergency Response System that utilizes AI-driven cameras, radar sensors, and voice-based validation to detect falls in real-time and ensure timely medical intervention. This system is specifically designed to enhance elderly care and independent living, providing automatic alerts to emergency services and caregivers in case of an unresponsive individual. A web-based dashboard enables real-time monitoring, making this an ideal lifesaving solution for senior citizens living alone.
Elderly individuals living alone are at a high risk of falls, which can lead to serious injuries or fatalities if medical help is delayed. Traditional solutions, such as wearable emergency buttons, rely on manual activation, which may not always be possible in case of a severe fall. The absence of automatic detection and rapid response mechanisms puts elderly individuals at great risk.
Current fall detection solutions rely on wearable devices, motion sensors, and camera-based AI, each with limitations. Wearables require manual activation, making them unreliable if the person is unconscious. Motion sensors often trigger false alarms, while camera-based AI struggles with poor lighting and occlusions, leading to delayed emergency response and increased risk.
At Nida Ai, we have developed a multi-modal AI-powered system that accurately detects falls using cameras, radar sensors, and voice-based confirmation to eliminate false alarms and ensure rapid medical assistance.
Our system functions in three critical stages:
Fall Detection –AI cameras and radar sensors analyze human movement and posture in real-time to identify sudden falls with high precision.
Validation – If a fall is detected, the system asks the person for confirmation. If there is no response within a few seconds, it triggers an emergency protocol.
Emergency Response & Dashboard Alerts – If no response is received, automatic alerts are sent to emergency services, family members, and caregivers, while the dashboard logs the event for real-time monitoring and medical action.
This multi-layered validation process ensures accurate fall detection, minimizes false alarms, and accelerates life-saving intervention.
Uses computer vision and radar-based sensing to detect falls in real-time.
Voice-Based Confirmation:Automatically asks the person for confirmation to reduce false alerts.
Emergency Contact Alerting:Notifies emergency services, family members, and caregivers if no response is detected.
Cloud-Connected Dashboard:Tracks fall history, emergency responses, and system diagnostics for better medical insights.
Privacy-Focused AI:Uses non-intrusive monitoring, ensuring elderly individuals' comfort and data security.
Immediate trigger of emergency calls ensures timely medical assistance.
No Manual Activation Needed:Works without requiring the user to press any button or take action.
Low False Alarm Rate:Voice-based validation and multi-sensor fusion reduce false triggers.
Real-Time Monitoring:Families and caregivers can track incidents and health trends remotely.
Ensures Independent Living:Supports elderly individuals living alone, providing a safer environment.