airport-ai-facility-monitoring/backend_workspace
Jul 2025 – Aug 2025
2 Months active
Languages Used
JavaXMLJSXJavaScriptPythonSQL
Technical Skills
Backend DevelopmentDependency ManagementDomain-Driven DesignJavaMavenSpring Boot
김민욱
PROFILE
김민욱
Over two months, alsdnr9567@naver.com developed and enhanced the airport-ai-facility-monitoring/backend_workspace, focusing on backend systems for real-time airport facility monitoring. They implemented a robust alerting and notification framework, improved object detection event handling, and introduced deduplication logic in the YOLO API to reduce redundant data. Their work included expanding media upload capabilities, refining dashboard and home views for real-time updates, and enforcing stricter onboarding requirements. Using Java, Spring Boot, and React, they applied domain-driven design and event-driven architecture principles, delivering twelve features and resolving five bugs. The work demonstrated depth in backend reliability, data flow optimization, and maintainability.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
27Total
Bugs
5
Commits
27
Features
12
Lines of code
2,601
Activity Months2
Your Network
1010 people
Work History
August 2025
24 Commits • 10 Features
Aug 1, 2025August 2025: Delivered robust alerting and notification capabilities for the airport facility monitoring backend, with real-time UX improvements and stronger data flow. Implemented a core Alerts system and notification logs, reduced duplicate data transmissions through 30-second dedup logic in YOLO API, and enhanced dashboards/home views for real-time visibility. Expanded media handling (video upload, MP4 assets) and strengthened signup flow (email required). Stabilized the notification subsystem and resolved key UI regressions to improve operator efficiency and reliability across the platform.
24 Commits • 10 Features
Aug 1, 2025August 2025: Delivered robust alerting and notification capabilities for the airport facility monitoring backend, with real-time UX improvements and stronger data flow. Implemented a core Alerts system and notification logs, reduced duplicate data transmissions through 30-second dedup logic in YOLO API, and enhanced dashboards/home views for real-time visibility. Expanded media handling (video upload, MP4 assets) and strengthened signup flow (email required). Stabilized the notification subsystem and resolved key UI regressions to improve operator efficiency and reliability across the platform.
August 2025
July 2025
3 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for airport-ai-facility-monitoring/backend_workspace: Delivered key backend improvements including dependency maintenance, feature enrichments for runway detection events, and code quality refactor to simplify control flow. Focused on stability, data quality, and maintainability to support scalable analytics and faster iteration.
July 2025
3 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for airport-ai-facility-monitoring/backend_workspace: Delivered key backend improvements including dependency maintenance, feature enrichments for runway detection events, and code quality refactor to simplify control flow. Focused on stability, data quality, and maintainability to support scalable analytics and faster iteration.
Activity
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Quality Metrics
Correctness83.0%
Maintainability83.8%
Architecture76.2%
Performance78.6%
AI Usage23.0%
Skills & Technologies
Programming Languages
JSXJavaJavaScriptPythonSQLXML
Technical Skills
AI IntegrationAPI DevelopmentAPI Error HandlingAPI IntegrationBackend DevelopmentCORSCloud ConfigurationDatabase ManagementDependency ManagementDomain-Driven DesignError HandlingEvent HandlingEvent-Driven ArchitectureException HandlingFastAPI
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