How our APIs work

Last updated 1 year ago

Was this helpful?

Before you read this page, please understand how our stream system work here Overview.

Here’s an in-depth explanation of how each method works:

Purpose: This is used to consume real-time event data resulting from AI model inferences.
Functionality: When AI models running within the VisionAIre Stream complete an inference task, such as object detection or facial recognition, the results are sent out as events.
Real-time Usage: Websockets provide a persistent connection between the client and server, allowing for the instant transmission of data as soon as an event occurs. This is crucial for applications that require real-time alerting or monitoring.

Purpose: The API is used for configuring the data processing pipeline and for retrieving resources.
Configuration: Through the API, users can set up and modify the parameters or the sequence of operations that the AI models use to process the data streams.
Resource Retrieval: The API also allows users to request and retrieve specific resources. This could include accessing specific video streams, processed data, metadata, or AI model outputs.

Purpose: Users can directly query the database to retrieve stored data for custom use cases.
Custom Dashboard Creation: By querying the database, users can pull historical data, analytics results, and other relevant data to create custom dashboards. This allows for tailored visualization and analysis that meets specific user needs.
Data Analysis: Access to the database enables users to perform in-depth analysis, generate reports, and derive insights based on the historical data.

In summary, the VisionAIre platform provides a flexible data consumption model:

Real-time event data is handled via Websockets for immediate updates and alerting.
The API facilitates configuration and on-demand access to resources, allowing users to manage and control the data processing pipeline.
The database access enables custom data queries, allowing users to perform custom analysis and create unique dashboards tailored to their requirements.

Last updated 1 year ago

Was this helpful?

Before you read this page, please understand how our stream system work here Overview.

Here’s an in-depth explanation of how each method works:

Purpose: This is used to consume real-time event data resulting from AI model inferences.
Functionality: When AI models running within the VisionAIre Stream complete an inference task, such as object detection or facial recognition, the results are sent out as events.
Real-time Usage: Websockets provide a persistent connection between the client and server, allowing for the instant transmission of data as soon as an event occurs. This is crucial for applications that require real-time alerting or monitoring.

Purpose: The API is used for configuring the data processing pipeline and for retrieving resources.
Configuration: Through the API, users can set up and modify the parameters or the sequence of operations that the AI models use to process the data streams.
Resource Retrieval: The API also allows users to request and retrieve specific resources. This could include accessing specific video streams, processed data, metadata, or AI model outputs.

Purpose: Users can directly query the database to retrieve stored data for custom use cases.
Custom Dashboard Creation: By querying the database, users can pull historical data, analytics results, and other relevant data to create custom dashboards. This allows for tailored visualization and analysis that meets specific user needs.
Data Analysis: Access to the database enables users to perform in-depth analysis, generate reports, and derive insights based on the historical data.

In summary, the VisionAIre platform provides a flexible data consumption model:

Real-time event data is handled via Websockets for immediate updates and alerting.
The API facilitates configuration and on-demand access to resources, allowing users to manage and control the data processing pipeline.
The database access enables custom data queries, allowing users to perform custom analysis and create unique dashboards tailored to their requirements.