Positioning LoRaWAN as the “digital nervous system” for AI reframes LPWAN from basic transport to an intelligence distribution fabric. Embedding AI at the edge, core and application layers signals a shift from raw telemetry to intent-driven, event-based IoT traffic, which can change how networks are dimensioned, secured and monetized. The examples listed suggest that value will concentrate in verticalized analytics, autonomous operations tools and multi-bearer architectures (e.g., NTN hybrids), rather than in connectivity alone. This move aligns IoT more closely with emerging “physical AI” paradigms where models and actuators are tightly coupled.
AI is reshaping the core tenets of IoT from connectivity and visibility to intelligence and action.
At Mobile World Congress Barcelona 2026, the LoRa Alliance is announcing its vision for how LoRaWAN and AI are uniting to enable transformative capabilities and greater value throughout the IoT stack’s edge, core, and application layers.
LoRaWAN has established itself as the LPWAN connectivity technology with the highest accessibility, within reach of anyone who needs it for their own product development, or to leverage LoRaWAN-enabled devices for their own IoT applications. At the end of 2025, there were more than 125 million LoRaWAN IoT devices worldwide. Now, LoRaWAN is taking on an even bigger role, providing the connectivity foundation for IoT to become the digital nervous system for AI. LoRaWAN enables the collection of raw IoT data for AI analysis. The resulting insights and actions are delivered via LoRaWAN to wherever they can create the greatest value by improving operational efficiency, creating new revenue opportunities, and allowing IoT users to do more with their connected devices and IoT applications.
The LoRa Alliance explained that there are three distinct ways AI and LoRaWAN technologies are working together to add new value to the widest adoption of IoT deployments: AI at the edge, AI in the core, and AI in the application.
AI at the edge:
A growing number of LoRaWAN-connected sensors and other devices are enabling AI processing to happen at the far edge of the IoT network inside the devices themselves, not just at the radio access network. On-device AI processing eliminates the need for large amounts of data to be sent to the cloud, lowering latency between perception, insight, and action. Those devices can then leverage LoRaWAN’s power efficiency, high scalability, and low-cost connectivity to transmit only necessary outcomes, such as notifications, alerts, and recommendations.
For example, LoRaWAN-connected cameras are already deployed in a variety of environments for purposes such as event detection and people counting. Image data processed by on-device AI allows alerts to be created more quickly. Elsewhere, vibration and load sensors connected via LoRaWAN are being used to monitor equipment in large industrial environments. In these scenarios, AI analyzes conditions and generates recommendations for predictive maintenance as wear and tear reaches specific thresholds.
With the most robust ecosystem, many LoRa Alliance member companies are enabling these applications today. For example, members Seeed Studio and Milesight each have camera products featuring on-device AI processing, while fellow members Honeywell, Advantech, Watteco, and TE Connectivity each have vibration sensors integrating LoRaWAN connectivity and AI processing.
AI in the core:
While AI processing provides benefits at the farthest edges of the LoRaWAN IoT networks, it also can be leveraged in the LoRaWAN core network by network operators to interpret network patterns and detect anomalies. This translates to the ability to manage network performance, reliability, and security in a more proactive manner.
For example, LoRa Alliance member Kudzu Technologies’ CanopyNOC product leverages agentic AI to autonomously observe and identify network anomalies and provide network operators with actionable intelligence to resolve any core network issue that arises.
AI in the application:
LoRaWAN technology supports the widest range of IoT applications, covering large distances and geographic areas, such as low-power asset tracking, smart cities, smart agriculture, and wide-area environmental and industrial monitoring. Integrating AI into these IoT application scenarios can help applications run more efficiently and provide more accurate information about the location and status of LoRaWAN-connected assets.
LoRA Alliance members leveraging AI in this manner today include Browan and Combain, each of whom provides AI-enhanced products for indoor location tracking applications. Also, Akenza’s IoT platform features an AI chatbot that fields questions and addresses them with answers that directly reflect available IoT data.
Meanwhile, Creative5, Inc. has deployed a hybrid LoRaWAN + Non-Terrestrial Network (NTN) satellite connectivity solution in Taiwan to enable real-time environmental monitoring in remote mountain forests beyond terrestrial coverage collecting data such as temperature, humidity, water level, etc. This is transmitted via Creative5’s Hestia LoRaWAN gateway integrated with NTN satellite connectivity. AI-driven analytics on the cloud platform enable anomaly detection, early wildfire and flood warning, and predictive environmental insights.
Elsewhere, Emergent Connext in its Rip Platform combines LoRaWAN connectivity and an AI-powered intelligence layer to deliver automated capabilities to agricultural producers. Also, inBiot’s ANNE AI assistant connects directly to its LoRaWAN sensor network to interpret real-time indoor air quality data against standards.
Additionally, MachineQ, a Comcast company and LoRa Alliance member, has developed its own AI application that demonstrates how IoT and AI are converging. The feature uses AI to translate millions of IoT data points into clear, actionable insights for operations and procurement teams, reducing days of analysis to just seconds. By repeatedly synthesizing high-volume data, the application identifies patterns and trends across key areas including asset location, utilization, alerts, general status updates, and sensor readings from monitoring devices, producing concise, easy-to-understand summaries that help teams make informed decisions quickly and streamline workflows.
Alper Yegin, CEO of the LoRa Alliance, said:
“LoRaWAN and AI working together pave the path for AI to move from the purely digital world into the physical world.”
“LoRaWAN’s global footprint includes the largest volume of IoT-connected devices among all LPWAN technologies and the widest variety of application types, allowing it to serve as the best possible interface between AI and physical world devices. LoRaWAN can extend AI’s reach and utility, and AI can increase the performance and value of every LoRaWAN-connected device.”
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