\section*{Abstract}
This project addresses the challenges faced by farmers in implementing and maintaining reliable real-time field monitoring and control. Knowning their system operating with high failure rate, which often attributed to issues such as network connectivity, sensor malfunctions, and vendor dependency, this research focuses on developing autonomous control-based station to overcome some of these challenges. The system is designed to provide farmers with real-time data acquisition and remote control capabilities without reliance on external cloud services or 5G networks, thus retain autonomy of farmers for long term.

With system engineering approach, this thesis will adopt tools such as system analysis, functional decomposition, and physical architecture design, while offer alternatives assessment on multiple technology such as farming drones, AI-integrated image capturing, and control-based stations, using multi-criteria decision-making methods like the Analytical Hierarchy Process (AHP). Farmers can be persuade in some aspect where control-based station solution can be an alternative that is cost-effective, maintainable, and adaptable to new pool of wireless technology. This project also address new growth of utilizing open-source software and popular open-source hardware available to minimize vendor dependency and ensure long-term support.

Operational requirements, economic factors, design constraints, and non-functional requirements are thoroughly analyzed to guide the system's development. The scope of the project will includes defining functional hierarchies, creating N-square diagrams, and developing a function allocation table to ensure traceability and modularity. The project also introduce linear regression models for water need prediction and cloud-native computing principles for system reliability and maintainability.

The goal for this research is a  system design that can balances performance, cost, and maintainability. The end goal of the design is providing farmers with a reliable and autonomous field monitoring and control solution for their crops cares. 