This week marked a major milestone for L.A.A.R.K Lite as we successfully transitioned from isolated development modules to a fully connected system. What began as separate frontend, backend, database, and modeling efforts has now evolved into an integrated full-stack prototype.
System Integration: Connecting the Pieces
Our primary focus this week was establishing seamless communication between the frontend, backend, and database layers. Using Supabase as our cloud database solution, we connected our backend APIs to a live database and ensured that the frontend could dynamically fetch and display stored data.
This means that data entered through the user interface is now persistently stored, retrieved in real time, and reflected back in the dashboard — validating our end-to-end system architecture. Seeing live data flow through the application confirmed that our technical stack is functioning cohesively rather than as independent components.
Model Completion and Readiness for Deployment
Alongside system integration, we completed the development of our baseline machine learning model. Using the refined and merged dataset, we finalized feature selection, validated outputs, and ensured the model generates meaningful predictions aligned with our predictive maintenance objectives.
With the model completed and the infrastructure ready, we are now positioned to integrate predictive outputs directly into the dashboard experience.
Reflection: From Architecture to Implementation
This week highlighted the importance of modular design. Because each subsystem — frontend, backend, database, and ML — was developed with clear boundaries, integration was a matter of alignment rather than redesign.
The platform is no longer theoretical. It is operational.


Moving Forward
In the upcoming week, we will focus on:
- Integrating model predictions into the live dashboard
- Refining UI interactions for improved usability
- Enhancing data validation and testing workflows
- Preparing for MVP-level demonstration
With Supabase powering our database, APIs actively serving data, and our predictive model finalized, L.A.A.R.K Lite is steadily advancing toward a fully functional intelligent lighting asset management system.












