This repository contains the implementation of a Voting Machine, showcasing both a Behavioral Model and a Structural Model. The design emphasizes clarity and modularity for a better understanding of the system's working and scalability.
The Behavioral Model is designed using a Finite State Machine (FSM), providing a clear overview of the voting process.
- Finite State Machine: Clearly represents the different states of the Voting Machine.
- Transparent Workflow: Easy-to-understand logic and flow for users.
- Define States: Enumerate system states (e.g., initialization, candidate selection, vote casting).
- State Transitions: Specify transitions between states based on user interactions.
- Input Handling: Detail how user inputs trigger state transitions.
The Structural Model is implemented with an asynchronous reset up counter as its primary component. Scalability is achieved by adding counters based on the number of candidates.
- Asynchronous Reset Up Counter: Core component for the structural design.
- Scalability: Adaptable to the number of candidates for voting.
- Counter Integration: Integrate the asynchronous reset up counter as a structural component.
- Modular Design: Ensure a modular structure for easy scalability.
- Wiring and Connectivity: Establish proper connections between components.
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Behavioral Model:
- Utilize simulation tools compatible with Finite State Machines (e.g., ModelSim).
- Simulate the behavioral model to observe the voting process and states.
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Structural Model:
- Utilize HDL synthesis tools (e.g., Xilinx Vivado) to synthesize the structural model.
- Configure FPGA or other hardware for deployment.
- Ensure necessary simulation and synthesis tools are installed.
- Refer to specific documentation for synthesis tools for hardware deployment.
Feel free to explore and modify the models based on election requirements or hardware constraints. The provided models offer a foundation for a functional and scalable electronic voting machine.
Happy Voting!