Synapse Wireless and Silicon Laboratories have introduced a jointly developed wireless mesh networking solution that combines the award-winning Synapse SNAP network operating system with Silicon Labs’ Si1000 wireless microcontroller (MCU). The combined software/hardware solution – the Synapse RF Engine module – makes it possible to deploy scalable, low-power wireless mesh networking for a wide range of applications including smart metering, building automation, commercial lighting control, personal medical devices, asset tracking systems and more.
The SNAP network operating system provides a wireless mesh networking protocol that supports Internet-enabled, wireless machine-to-machine communications, and offers an embedded Python interpreter for application development. Providing the intelligence behind the Synapse RF Engine, SNAP runs on Silicon Labs’ Si1000 wireless MCU, which combines a low-power processor core with a sub-GHz RF transceiver.
The SNAP network operating system is an Internet-enabled, IEEE 802.15.4-based, instant-on, multihop, mesh network software solution designed to run efficiently over a range of popular microprocessors and microcontrollers. SNAP has a very small memory footprint of only 45 KB, thereby leaving more space for user applications. SNAP can support up to 16 million nodes in a single network. Since these are peer-to-peer mesh networks, there is no single point of failure: any node can talk directly to any other node that is in range, and any node can talk indirectly to any other node via intermediate nodes; SNAP networks are self-healing.
The Si1000 wireless MCU combines a 25 MHz 8051 core, EZRadioPRO sub-GHz RF transceiver, 64 KB of flash and a 10-bit ADC – all in a compact 5 x 7 mm package. The integrated power and low-noise amplifiers enable an RF link budget of greater than 140 dB without active external elements. The wireless MCUs offer active-mode current consumption of 160 µA per MHz. In sleep mode, they consume only 315 nA using the internal low-frequency RTC. In deep-sleep mode, they can operate on as little as 25 nA with full RAM retention.
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