But beyond just tracking temperature or location, I wanted to explore something different:
What if we could combine local sensor data with global trade data to provide context-aware analytics?

That’s where platforms like Tradeint come into play. It provides access to structured import-export data across major markets (USA, China, Japan, Korea, etc.) — including:

• HS code lookups
• Company-level shipment records
• Trends in commodity movement over time

My concept:

• Use M5Stack to collect environmental data in transit (e.g., humidity in a seafood shipment);
• Periodically match that with historical trade data for similar commodities using the Tradeint API (or scraped results);
• Alert the shipper if values deviate from norms or if market demand is shifting.
  
  It’s still an early stage, but combining IoT + trade intelligence feels like a practical step for small exporters who can’t afford full-scale ERP systems.

Anyone here experimenting with supply chain or logistics-focused M5Stack projects? Would love to hear your setups, sensors, or software stacks — especially if you're integrating external data sources!