Video Analytics is an advanced computer vision product that
harnesses the power of AI and ML models to provide real-time analysis and insights
through camera feeds. This case study offers an in-depth look into the capabilities and
impact of this innovative solution in various settings, including old age homes, hospitals,
and packaging factories.
Product Features
Video Analytics offers a range of features designed to enhance security and provide
valuable insights:
Technologies Used
ANGULAR
Used for the frontend
development, creating a
responsive and intuitive user
interface.
AI/ML Models
Trained and fine-tuned by a
dedicated team of AI/ML experts
to enable the various detection
and recognition capabilities.
NODE JS
Employed for server-side
development, handling real-time
data processing and
communication with IoT devices.
R-T Analytics
Real time analytics provides
live graphs and analytics
based on the data collected
from camera feeds.
Deployment Settings
Video Analytics has been deployed as a demo in several key settings, including:
Impact and Benefits
The deployment of Video Analytics has yielded several tangible benefits:
Challenges Overcome
The development and deployment of Video Analytics were not without challenges:
- Model Training: Training AI/ML models for diverse scenarios and maintaining their accuracy required continuous efforts from the AI/ML team.
- Privacy and Ethics: Ensuring privacy compliance and ethical use of facial recognition technology demanded careful considerations and configurations.
- Integration: Integrating the product seamlessly with existing camera systems and networks was a technical challenge.
Future Directions
Video Analytics continues to evolve and has promising future directions: