Expanding Connectivity with Meshtastic
Bridging Networks and Processing Real-Time IoT Data
Continuing our series on Meshtastic, we want to dive further into the interconnected nature of the Meshtastic system. One of its most compelling features is the ability to bridge a local radio-based Meshtastic network across the internet via MQTT servers, effectively creating an interconnected network of mesh networks. This becomes incredibly powerful for ensuring seamless communication across a wide area without compromising security or data integrity.
What is MQTT?
Lets start with a bit of background on what MQTT is, and the connectivity it provides. MQTT, which stands for Message Queuing Telemetry Transport, is a lightweight messaging protocol designed for efficient communication between devices in the Internet of Things (IoT) world. Imagine it as a system where devices can talk to each other through a central messenger, called a broker. Instead of devices directly contacting each other, they send messages to specific topics, like “msh/US/abc“ and the broker makes sure these messages reach all the devices interested in those topics. This approach is particularly useful for devices with limited power or in areas with unreliable internet connections, as it uses minimal resources to send and receive information. MQTT's simplicity and efficiency make it ideal for connecting various smart devices in your home, sensors in industrial settings, or even applications on your smartphone, allowing them to share information and work together seamlessly.
In this context, MQTT is beneficial in providing a fabric to cross-connect Meshtastic nodes via an efficient and well coordinated model. Using a standards-based mechanism such as MQTT ensures that Meshtastic can build an ecosystem and integrate devices and solutions, rather than create specialized unique standards that would limit adoption.
Bridged Networks with MQTT
A meshtastic node, by default, is not sending or consuming information from any MQTT services. It is the decision of a user to connect the local radio network to MQTT, and to determine where it will publish, what topics it will use, and what servers it will integrate with.
When using MQTT publishing, a Meshtastic client has full control over whether information is sent to an MQTT server, which server to use, and, most importantly, which encryption keys to implement. Unlike many centralized systems, Meshtastic puts control in the hands of the user, allowing them to decide where to publish information and who may access it.
An important caveat, any other node receiving a client’s radio-based broadcast in a local area may choose to send it out over the public MQTT networks as well. In other words, a client may not be aware of it’s device being picked up and sent out, as any receiver in the local area may choose to publish to the global MQTT services. For devices with privacy concerns, this may be mitigated through only using private encrypted channels and to avoid the general public radio channels.
With the ability to publish to public channels or establish ad-hoc private communication networks, nodes can securely exchange information even across shared public internet infrastructure. This flexibility makes Meshtastic a powerful tool for individuals and organizations requiring resilient, decentralized communication solutions.
Real-Time Global Data and IoT Insights
Although Meshtastic nodes operating on public channels can anonymize certain details, such as node identifiers and geolocation precision, a wealth of real-time data is still being published globally. Meshtastic nodes, which function without a central registry or mandatory naming convention, can transmit diverse sensor and geospatial data, including:
With hundreds of thousands of messages published daily over Meshtastic’s global MQTT services, this dataset provides valuable insights into decentralized communication patterns and real-world IoT applications.
Lemuridae Labs and IoT Data Processing
At Lemuridae Labs, we specialize in processing and analyzing real-time IoT data, and Meshtastic’s MQTT-based data stream presents an exciting opportunity to apply our expertise. By transforming & normalizing, filtering, enriching, and processing this data, we gain a deeper understanding of the movement characteristics of semi-anonymous nodes across the world.
Lemuridae Labs proceses IoT data from Meshtastic in a reasonably normal manner, seeking to enrich information and contextualize data prior to processing. In this case, augmenting the MQTT-based Meshtastic data with additional context, such as message rate, geospatial characteristics, and other factors. A general high level flow can be seen below.
A map-based visualization is shown below, highlighting types of nodes, recency of transmission, and other communications characteristics. On this display, selecting nodes provides additional information including self-identified node name and description, recent movements, region configuration, and other characteristics.
A different visualization is an interesting comparison, as it is showing node-density as a heat map, although other factors such as a transmit rates could be used as the primary metric for the heat map visualization.
Map-based Mesh Time Series Data
One way we visualize this data is through a map-based Mesh Activity Visualization, highlighting nodes based on type, activity, and data recency. However, beyond mapping, Meshtastic data is rich in time-series information, offering significant opportunities for analysis.
Time-series data refers to measurements collected at different time intervals—for instance, temperature fluctuations at a location, engine load on a vehicle, or air quality monitored by environmental sensors. As Meshtastic nodes transmit data over time, this information can be aggregated and analyzed to support local or global communities.
For example, air quality data from nodes can be regionally aggregated to provide real-time environmental insights, even in areas with intermittent connectivity. This capability becomes particularly valuable in disaster response scenarios, where sensor data is critical for tracking and maintaining public health and safety, even if traditional communication networks or power infrastructure are compromised.The ad-hoc nature of Meshtastic communications, backed by MQTT-based interconnects, builds a resilient and powerful foundation for communications in all scenarios.
Next Steps
As this series continues, we will detail our data analysis process with the Meshtastic network, including how we receive, transform, and evaluate information in various ways. These efforts align closely with other services provided by the team at Lemuridae Labs, and we are always interested in collaborating with partners on unique and innovative opportunities.
Stay tuned for further insights into the evolving Meshtastic ecosystem and its growing role in decentralized communication and IoT data analysis!