Hi HN! I've been working on this IoT platform that aims to simplify deploying remote sensor networks by combining pre-configured LTE hardware with a cloud platform for remote programming and AI-based analysis.
The main challenges I'm trying to solve are:
1. Eliminating infrastructure setup headaches for IoT deployments
2. Making remote programming and debugging practical for devices that might be difficult to access physically
3. Using natural language for analyzing sensor data, and possibly taking actions based on the analysis
I'd really appreciate feedback on:
1. Is this approach to IoT development interesting to you?
2. What use cases would you want to explore with this kind of platform?
3. What concerns would you have about adopting something like this?
4. Could anyone recommend workflows or tools for making the AI agent more reliable? Currently using LLMs to generate isolated SQL queries to extract data, but ensuring consistent responses has been challenging.
Thanks for any thoughts, and feel free to ask any questions about how the hardware or platform works. Happy to dive into the details!
If the code needs to change, that is much safer to do in a controlled, low risk, nonproduction environment, where you will very likely have development hardware that has been optimized for ease of development/debugging. Once changes are tested and otherwise validated, an over the air update process would be used to send that new firmware image to the device. This way, your devices all can be on a single version of the firmware, meaning you can scale the deployment of that update to 10, then 100, then 1000 devices, etc.