
Over three months, Kheira developed the Flower Data Management System within the SE4CPS/DMS repository, focusing on backend and frontend integration using Python, Flask, and PostgreSQL. She designed a unified data model for flowers, implemented CRUD operations, and automated watering logic with environment simulation to streamline plant care. Her work included building a web application with HTML, CSS, and JavaScript for user interaction, as well as adding features for query performance analysis and database indexing. Kheira emphasized maintainable project structure, thorough documentation, and groundwork for analytics, resulting in a robust, scalable system that supports both operational automation and future reporting needs.

April 2025 was focused on delivering two value-driven features in SE4CPS/DMS and establishing groundwork for data-driven improvements. The work aligns with business goals: enabling operational automation, improving data access patterns, and preparing the system for analytics and scalable growth.
April 2025 was focused on delivering two value-driven features in SE4CPS/DMS and establishing groundwork for data-driven improvements. The work aligns with business goals: enabling operational automation, improving data access patterns, and preparing the system for analytics and scalable growth.
March 2025 monthly summary for SE4CPS/DMS: Delivered two core features with clear business value: a unified data model for flowers enabling consistent data management and an automated watering system with UI and environment simulation to support proactive plant care. The work establishes a maintainable data layer, scalable UI, and automation that reduces manual effort while enabling data-driven decisions.
March 2025 monthly summary for SE4CPS/DMS: Delivered two core features with clear business value: a unified data model for flowers enabling consistent data management and an automated watering system with UI and environment simulation to support proactive plant care. The work establishes a maintainable data layer, scalable UI, and automation that reduces manual effort while enabling data-driven decisions.
February 2025 – SE4CPS/DMS development: Delivered the Flower Data Management System with a PostgreSQL schema and scripts, including tables for flowers, outdoor plants, and indoor plants; added water level tracking, rain indicators, sample data insertion, and basic connection management to support flower-related data operations. Also reorganized the project structure for Team 1 under project/part1, added a Team 1 readme, and removed obsolete historical Python files related to PostgreSQL operations to improve maintainability and onboarding.
February 2025 – SE4CPS/DMS development: Delivered the Flower Data Management System with a PostgreSQL schema and scripts, including tables for flowers, outdoor plants, and indoor plants; added water level tracking, rain indicators, sample data insertion, and basic connection management to support flower-related data operations. Also reorganized the project structure for Team 1 under project/part1, added a Team 1 readme, and removed obsolete historical Python files related to PostgreSQL operations to improve maintainability and onboarding.
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