Description
**Facial Recognition and People Counting**
Leveraging advanced deep learning algorithms, the camera integrates comprehensive smart features for facial recognition. It simultaneously captures individual facial features while conducting people counting, comparing these features against a built-in facial database to eliminate duplicates. This facilitates efficient access control and accurate people counting by reporting face alerts in real-time.
**Personal Protective Equipment (PPE) Compliance Monitoring**
Utilizing embedded deep learning capabilities, the camera detects individuals within specified areas and verifies the presence of required safety gear, such as hard hats. It captures headshots and triggers an alert for non-compliance, enhancing workplace safety.
**Comprehensive Multi-Target Detection**
The camera employs deep learning algorithms to detect and capture both facial and human body features within designated areas. It extracts key demographic attributes such as gender, age, and clothing color. This enables detailed data structuring and analysis for comprehensive information gathering.
**Queue Management Solutions**
Incorporating deep learning algorithms, the camera accurately detects the number of people in queues and assesses their wait times. By effectively recognizing body features, it minimizes errors and enhances the precision of its detections.
**Enhanced Data Utilization with Metadata**
Metadata captures and utilizes discrete application data instances, serving as a valuable resource for third-party application development and integration.
**Optimized Video Streaming**
Smooth streaming technology enhances video quality across varying network conditions. It dynamically adjusts streaming bit rates and resolutions to maintain optimal performance and minimize latency, even in suboptimal network environments. In robust network settings, the camera transmits redundant data to facilitate back-end error correction, thus mitigating issues such as packet loss and maintaining clarity.
