
Dynamic Service Provisioning
Dynamic Service Provisioning enables the instantiation and deployment of cloud services from Smarter AI Dashboard to deployment or group of cameras. Examples of cloud services include Data Retention, Event Recording, Tracking and Tracing, and more.
Benefits
AI Model Lifecycle Management
- Containerize and OTA program AI models
- Continuous learning / continuous delivery:
- Collect event notifications and recordings
- Retrain AI models – minimize false positives and negatives
- Containerize and program AI models OTA
- Train, containerize, and OTA program new AI models to support new use cases
Programmable Classification Thresholds
- OTA program classification thresholds
- Collect event notifications and recordings
- Optimize classification thresholds – minimize false positives and negatives
- Program a single AI Container with multiple classification thresholds
Sensor Fusion
- Provision and OTA program AI models
- Field of view (FoV) from 0.15 to 360 degrees
- Image resolution from HD to 4K to 8K
- Object distance up to 50 miles
- Sensors including accelerometer, GPS, gyroscope, magnetometer, temperature
Inference Workflow Management
- AI models as programmable objects
- Chain inferencing jobs together with logical operators
- Map AI model outputs to AI model inputs
Inference Scheduling
- Inferencing on demand, continuous inferencing
- Run multiple AI models in parallel:
- using the same imager/sensor inputs
- using logical operators to infer decisions
Greenfield and Brownfield Deployments
- Containerize and OTA program AI models to greenfield (i.e. Smarter AI camera) deployments
- Containerize and OTA program AI models to brownfield (i.e. IP camera) deployments with Smarter AI Gateway
- Map local and distributed imager/sensor outputs to AI model inputs