Inspiration
The inspiration for Mustang-GT came from the need to build an interactive, real-time system that can help enhance the user experience with advanced automation. My background in electrical and AI systems engineering, combined with my passion for innovation in automotive technology, motivated me to create a system that integrates seamlessly with both software and hardware. I envisioned a user interface that would allow users to interact with the system through simple controls like buttons and displays.
What it does
Mustang-GT is an interactive system designed to manage and control various components within a high-performance automobile. The project includes a user-friendly GUI, where users can control different aspects of the car’s performance through a set of buttons. The system processes user input, updates system settings, and displays relevant information on the interface. The project also integrates various sensors to provide real-time feedback to users. For example, one of the core features is the ability to control the car's LED indicators and monitor system metrics, such as speed and battery levels.
How we built it
We built Mustang-GT using a combination of hardware and software. The software was developed in C++ and integrated into a WASM environment, which exposed various functionalities such as GPIO, sensors, and communication protocols. We leveraged existing hardware like microcontrollers and sensors for real-time data collection. The software components were programmed to interact with these hardware elements, ensuring smooth integration. For the GUI, we used panel controls and interactive buttons, which were set up using the provided functions. The backend was designed to process user input and output dynamic data to the interface, making it responsive and engaging.
Challenges we ran into
One of the major challenges I encountered was dealing with hardware and software integration. Specifically, interfacing the microcontroller with the sensors and LEDs through the available communication protocols (such as I2C, SPI, and GPIO) was tricky. Debugging issues with real-time data transmission and ensuring smooth communication between the components was time-consuming. Additionally, creating a GUI with interactive elements using the existing functions was challenging, as it required a solid understanding of the event-driven programming model. Another challenge was designing a user interface that was intuitive while also delivering real-time data without lag. There were also issues with managing multiple control states and ensuring that the system remained responsive even during data polling.
Accomplishments that we're proud of
I’m particularly proud of the functionality that allows users to interact with the system through simple button presses to control the car's features. Despite the initial challenges, the real-time processing of user input was successfully implemented, and we were able to create a system that is both intuitive and highly interactive. Additionally, the integration of sensors and the ability to visualize performance data in real-time was a significant achievement.
What we learned
Through this project, I gained a deeper understanding of integrating hardware with software, especially in embedded systems. I learned how to efficiently manage data streams, work with communication protocols like I2C and SPI, and build interactive user interfaces within a real-time system. Additionally, I enhanced my problem-solving skills, particularly in troubleshooting hardware issues and optimizing system performance for seamless operation.
What's next for Mustang-GT
The next steps for Mustang-GT will involve refining the existing features and adding new capabilities, such as: Expanding the range of sensors and feedback mechanisms (e.g., adding a collision detection system or enhanced battery monitoring).
Improving the user interface to include more complex visualizations, like real-time speed charts or diagnostics. Integrating autonomous driving features, such as object detection, and adding more complex logic to the control system for self-driving capabilities. Exploring cloud-based systems to sync data remotely and enhance functionality.
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