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Overall Architecture
High-level overview of the Deeply system architecture and core components.
Last updated: January 1, 1980
Overall Architecture of Deeply AI System
This diagram provides a high-level overview of the Deeply system, illustrating the relationships between microphones, edge servers, and the central server.
Introduction
The Deeply system architecture is designed to monitor audio events in real time, process them efficiently, and transmit the resulting data reliably. This architecture consists of multiple components working together seamlessly, including microphones, an edge server, a central server, and a dashboard.
Components
Edge Server
The Edge Server is a critical component in the system, responsible for initial processing of audio data received from the microphones. Its main roles include:
- Audio Data Processing: Preprocesses audio data to reduce noise and isolate relevant signals.
- Event Detection: Identifies specific audio events based on predefined thresholds and labels.
- Data Transmission: Communicates processed data to the central server via API calls, ensuring efficient data transfer and reducing network load.
The edge server is strategically connected to the microphones to minimize latency and ensure faster sound data processing.
Event
The Event class represents an audio event detected by the system. Each event is identified by a unique label, confidence score, and timestamp, providing detailed insights into the detected sound. The key attributes of an event include:
- ID: A unique identifier for the event.
- Label: Classification of the audio event (e.g., "breathing heavily").
- Confidence: Confidence score indicating the accuracy of the classification.
- Audio File: Path to the recorded audio file associated with the event.
- Device Information: Details of the device that recorded the event, including device ID, name, location, and status.
The event data is stored and processed by the central server, allowing users to view and analyze the events on demand.
Refer to Events API Overview for detailed event data.
By combining real-time data processing with detailed event tracking, Deeply system architecture ensures efficient audio event monitoring and management, supporting both real-time and historical analysis.