Performance Optimization and MSA-Based Cloud-Native Transformation of an Intelligent Hazard Detection Solution

This project was undertaken to optimize the core AI model performance of Human ICT's Vision-based hazard detection system and to overhaul the infrastructure for maximum scalability and maintenance efficiency.

TOSKY successfully transitioned from the existing Monolithic architecture to MSA (Microservices Architecture), enabling independent operation of each service.
Technically, Kubernetes (k8s) deployment processes were introduced for the Python-based ML components and communication servers, enabling flexible orchestration in cloud environments.
Additionally, a Multi-Tenant architecture was applied to the Java-based management site, allowing a single instance to serve multiple clients, dramatically improving operational efficiency.

Through this project, TOSKY demonstrated advanced AI model optimization capabilities as well as system architecture design expertise leveraging the latest cloud-native technology stack.