I went straight to the software layer and kind of glossed over the actual hardware constraints, which I think hurt me.
Start by clarifying the business goal and constraints, then propose a high-level architecture that balances technical feasibility with privacy and scalability. Walk through the key components, data flow, and trade-offs, emphasizing how the solution improves warehouse safety and efficiency.
Pro tip: Frame the solution as a product that must drive adoption and trust—address privacy concerns proactively and suggest a phased rollout with clear success metrics.
Ask questions to understand scale (number of employees, warehouse size), accuracy needs, budget, privacy regulations, and integration with existing systems. Define success metrics like compliance rate or reduction in incidents.
Propose a system with wearable devices (e.g., badges) that measure temperature and distance via sensors (e.g., IR, UWB). Include a communication layer (e.g., Bluetooth Low Energy, Wi-Fi) and a backend for data aggregation and alerts.
Describe sensor selection, data processing (on-device vs. cloud), privacy measures (anonymization, aggregation), and alerting mechanisms (e.g., supervisor dashboard, real-time notifications).
Compare options: wearable vs. environmental sensors, on-device vs. cloud processing, accuracy vs. cost, and privacy vs. effectiveness. Justify choices based on requirements.
Propose a phased implementation, pilot testing, and metrics to measure success (e.g., adoption rate, reduction in close contacts, temperature screening accuracy).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.