Akvelon’s client is a leading provider of digital transformation solutions for network operators, service providers, and content providers.
The client wanted to enhance their vision-based parking lots management solution with a live video analytics technology in order to process video streams from 5G wireless cameras locally (on the edge).
One of the key success factors to the project was to minimize the effort required to set up parking lot configuration when deploying the system to new sites.
Akvelon worked closely with the client’s teams to analyze integration requirements and come up with the sound technical design. Then, Akvelon developed an integration module that manages the system’s configuration and handles real-time updates on parking lot occupancy data by tracking individual parking spaces. The integration module retrieves occupancy data from the edge devices, processes it, and makes it available via REST or WebSocket APIs.
To address day-zero configuration requirements, Akvelon developed a visual editor that provides a way to specify the layout of parking spaces on a live camera image and configures parameters for individual parking slots. To improve the parking manager’s workload, Akvelon developed a computer vision algorithm which analyzes a camera view and detects and outlines the parking slots automatically.
Akvelon developed a modular integration solution that provides the following benefits:
- Provides real-time analytics about parking spaces occupancy from the edge devices to the centralized analytics system
- Can be deployed either to on-premise edge devices or to the cloud
- Simplifies day-zero configuration by providing functionality to detect parking spaces automatically on a camera view.