Image recognition and analysis with Artificial Intelligence
from multiple devices in real-time.
Vehicle recognition and license plate extraction to process videos quickly. Detailed reports with exact location and time of violations via georeferencing in metadata.
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AI-eLPS can run on fixed or mobile devices, using Optical Character Recognition (OCR) based on Deep Learning and Machine Learning (AI).
Edge computing mode, running locally for real-time responses.
Cloud computing mode, efficient post-processing of large data volumes.
Fog computing combines local pre-processing and cloud post-processing.
Access Control
Traffic enforcement
Surveillance
Security
Parking
AI-eLPS can adapt to different approaches
Cloud computing
High data volume
Enables rapid and efficient processing of large image volumes via the Internet, without the need for physical infrastructure. Ensures precise and agile detection through instant and scalable access to computing resources.
Fog computing
Latency reduction
Useful for license plate detection by allowing faster and closer processing to image capture points, optimizing speed and accuracy of plate recognition.
Edge computing
Very low latency
Useful for real-time data processing without sending data to the cloud.
Increase revenue
Lower operating costs
Social responsibility
impact
Higher enforcement rate