The NLP module formed the bedrock of the project. It took speech/text queries, normalized them, and employed entity extraction to identify electronic components. Additionally, it parsed parameters like voltage and current needs from queries, structuring them into code blocks. The heart of this module was its dialogue generation component, which responded dynamically to user queries, enhancing user interaction.

This module evolved through two phases.

In Phase 1, we tackled data augmentation and trained the system with domain-specific data. Chatito, a new tool, was leveraged to generate examples for diverse electronic components. Data preprocessing and processing techniques, including the application of “RASA,” honed the system’s ability to extract electronic component entities.

In Phase 2, we integrated RASA-Core for dialogue generation. This component utilized NLP results to formulate meaningful responses, enriching user interactions.

The Combination Module seamlessly amalgamated electronic components into stable circuits, optimized voltage, current, and input requirements. Prioritizing needs, we created cost-effective, stable combinations that met critical specifications.

The Placement Module, fueled by AI, employed Learning Classifier System with Reinforcement Learning. It ensured optimal component placement on PCBs, adhering to design constraints for efficient electronic connections.

The Routing Module revolutionized circuit connectivity for IDEEZA. Powered by AI-driven A* algorithms, it swiftly designed optimized paths, and ensured efficient connections between components. This automation minimized interference, enhanced overall performance, and expedited prototype creation.

Addressing spatial constraints, the Bin Packing Module employed advanced algorithms to strategically position multiple PCBs and batteries. This optimization process allowed IDEEZA to design integrated hardware solutions that made the most of available space without compromising functionality.

Navigating the complexities of three-dimensional space, the 3D Routing Module excelled. By leveraging customized A* algorithms, it formulated efficient pathways for component connections. This translated IDEEZA’s hardware designs into functional reality, ensuring components were seamlessly interconnected within the three-dimensional realm.

The Generative Design Module reimagined circuit aesthetics. Manual covers limited to specific instances prompted the need for adaptable designs. This module crafted real-time covers based on user preferences, offered a fresh dimension of creativity. The ongoing research aimed to refine this approach, ultimately delivering covers with precise dimensions and data tailored to individual hardware configurations.

Transitioning from design to reality, the Gerber/Firmware Module was key. It streamlined the optimal placement, routing, and drilling data into Gerber files. These files contained machine commands from Python arrays, serving as manufacturing blueprints. Organized by timestamps in dedicated directories, they ensured efficient production.

The Android App Module transformed user interactions. It automated user-specific APKs, connected hardware and smartphones seamlessly. Whether drones or video doorbells, this module simplified complex functions via interconnected blocks and ensured intuitive control.