Expanding the Mesh Scope AI Chat capabilities with the Model Context Protocol (MCP), letting clients talk directly to the system to find answers to questions and share information.
Incorporating AI language models into a Meshtastic IoT system, and reviewing the possibilities created for natural language conversations with global device data. Advanced queries become trivial and conversational, providing new insights on data.
A review of Meshtastic MQTT data process, where the stream of IoT data is stored, evaluated, and processed in real-time. Various tools and technologies are discussed for data storage, including relational data, time series data, and archive files. Real-time data streams feed into agentic systems for processing and evaluation.
A discussion of data enrichment goals and techniques to augment incoming data with additional context to aid in data processing and analytics. Reviews using geospatial bucketing to reduce and optimize data lookups, and some considerations when seeking to enrich received data. The end result is to transform data into useful informa
A review of data filtering processes and techniques when receiving Meshtastic data from the public MQTT broker network, and how the Mesh Scope application focused on identifying issues and actively addressing data quality or network flood issues.
A discussion of the considerations and challenges when receiving Meshtastic data via MQTT brokers, including decoding, decrypting, and preparing data for use within applications.
