
Developed Smart Parking and Loitering Detection features for the open-edge-platform/edge-ai-suites repository, focusing on automated parking occupancy and vehicle analytics at the edge. Designed and implemented Node-RED flows to orchestrate data from object detection models, integrating outputs into parking and vehicle data pipelines. Authored a Bash-based installation script that automates Python virtual environment setup, model downloading, and configuration for both use cases, ensuring reproducible deployments. Leveraged skills in Python, Bash scripting, and system integration to deliver an end-to-end solution without reported bugs. The work enabled streamlined deployment of AI-powered analytics for smart parking and loitering detection in edge environments.
March 2025: Delivered Smart Parking and Loitering Detection capabilities in edge-ai-suites. Implemented Node-RED flows and an installation script, including Python virtual environment setup, model downloading, and configuration for both use cases. No major bugs reported this month. Business value: automated parking occupancy and vehicle analytics via an installable, reproducible deployment. Demonstrated skills in Node-RED orchestration, Python automation, and end-to-end integration.
March 2025: Delivered Smart Parking and Loitering Detection capabilities in edge-ai-suites. Implemented Node-RED flows and an installation script, including Python virtual environment setup, model downloading, and configuration for both use cases. No major bugs reported this month. Business value: automated parking occupancy and vehicle analytics via an installable, reproducible deployment. Demonstrated skills in Node-RED orchestration, Python automation, and end-to-end integration.

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