Updated July 27, 2026

Morse Micro Wins the 2026 IoT Edge Computing Innovation Award

IoThinkTank recognizes Morse Micro for providing the secure, long-range connectivity foundation required to deploy Edge AI at scale.

Salt Lake City, July 27, 2026, IoThinkTank has named Morse Micro the winner of the 2026 IoT Edge Computing Innovation Award for the MM8108 Wi-Fi HaLow System-on-Chip, a long-range, low-power connectivity platform designed to extend Edge AI and distributed intelligence across large, infrastructure-limited environments.

As AI moves from centralized cloud systems into cameras, sensors, meters, industrial equipment, utilities, buildings, and remote infrastructure, edge performance increasingly depends on more than processing power alone. Devices must also be able to exchange data, coordinate activity, and remain responsive in the real-world environments where information is created.

Morse Micro provides this critical connectivity layer, enabling distributed intelligence to operate beyond the traditional reach of conventional wireless infrastructure.

Morse Micro stood out for addressing this challenge through a standards-based connectivity platform that combines the range, power efficiency, bandwidth, security, and native IP networking required for Edge AI deployment.

Why Morse Micro Won

The MM8108 is built around the IEEE 802.11ah Wi-Fi HaLow standard and supports data rates up to 43.33 Mbps, output power up to 26 dBm, WPA3 security, low-power sleep behavior, and flexible USB, SDIO, and SPI host interfaces.

These capabilities allow connected devices to operate across larger physical environments without depending on dense access-point placement, extensive cabling, or fragmented proprietary networking models. Cameras, industrial sensors, smart meters, access-control devices, energy assets, and other edge systems can remain connected across facilities, campuses, farms, utilities, commercial properties, and remote infrastructure.

The technology also supports high device density, rich telemetry, responsive edge applications, and over-the-air model updates, helping organizations move beyond basic sensing toward systems that can process, prioritize, and act on information closer to the source.

Edge AI depends on more than processing power alone. Intelligent devices must remain connected across the real-world environments where data is created and decisions are made. Morse Micro’s MM8108 stood out for combining range, power efficiency, bandwidth, security, and deployment scale in a standards-based platform that expands where distributed intelligence can operate.

Jordan Hayes
IoThinkTank Awards Coordinator

About the MM8108

The Morse Micro MM8108 is a highly integrated Wi-Fi HaLow SoC designed for long-range, low-power IoT connectivity. Its compact architecture integrates MAC and PHY functions, power amplification, low-noise amplification, power management, and host offload capabilities to reduce system complexity and power consumption.

By operating in the sub-GHz spectrum, the MM8108 provides improved range and penetration compared with conventional Wi-Fi while maintaining familiar IP networking and modern security. This makes it particularly well suited for edge deployments where cloud connectivity may be inconsistent, wired infrastructure is costly, or devices must remain operational across large or difficult-to-reach environments.

Morse Micro’s broader ecosystem of modules, access points, gateways, and connected-device partnerships further strengthens the MM8108’s ability to support production-ready deployments across a range of IoT markets.

Efficient Computer Named Runner-Up

Efficient Computer earned runner-up recognition for the Electron E1 general-purpose processor, an innovative edge-computing architecture designed to reduce the energy consumed by conventional instruction processing.

Built on Efficient Computer’s Fabric architecture, the Electron E1 demonstrated strong whole-application performance and energy-efficiency results while maintaining general-purpose programmability. Its ability to support on-device processing and AI inference in highly power-constrained environments made it an exceptionally strong entrant and a close competitor in this year’s program.

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