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Long-Range Wireless Sensor Network Overview

Providing support for reliably and inexpensively collecting data from remote and rugged locations.

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  • Jan Frigo
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terncoms overview

Wireless Sensor Network

The low-power Long-Range Wireless Sensor Network (LRWSN) developed by researchers at Los Alamos National Laboratory and West Virginia University reliably and inexpensively collects data from remote and rugged locations, transmitting that data from node to node farther and across more square miles than any comparable existing network hardware.

The Long-range Wireless Sensor Network is a turnkey system comprised of field-deployable, temperature-resistant nodes that create a self-forming, self-healing network that communicates via low-power radio frequency across a vast area and has scientific computing capability at the sensor nodes. Master nodes can be linked to the server via satellite so that networks can collect and transmit data from any location on earth.

Data is transmitted from a master node to a host server in near real time so that the user is almost instantly made aware of changes in whatever is being monitored. The user can also remotely monitor network health and change network parameters, data collection rates, and node configurations.This LRWSN system is demonstrated in 2018 with the Stormwater Runoff sensors network in the Los Alamos watershed using 125-150 nodes covering a rugged 39 square miles with node-to-node distances of up to 12 miles and continuous operation for periods of years. This technology has achieved a milestone toward an elegant, affordable, and easy to use remote sensing solution.

Long-range Wireless Sensor Network Overview (PDF, Flier)
  • New Mexico Technology Counsel Women in Technology (WIT) Award, March, 2019
  • R & D 100 Winner 2018, Technology Innovation, Long Range Wireless Sensor Network
Recent Articles
  • Janette Frigo, Hudson Ayers, Shawn Hinzey, Sanna Sevanto, Mike Proicou, Xiougang Yang, Alex Saari, Vinod Kulathumani, “Novel WSN Hardware for Long Range Low Power Monitoring,” DCOSS, June, 2017. LA-UR-17-20811
  • Jan Frigo, et. al., “Energy Efficient Sensor Node Implementations,” IEEE ACM FPGA, 2010, Feb, 2010. LA-UR-09-05907
  • Jan Frigo, et. al., “Sensor network based vehicle classification and license plate identification system,” IEEE INSS, 2009, June, 2009. LA-UR-09-00256
  • Jan Frigo, et. al., “Radiation Detection and Situation Management by Distributed Sensor Networks,” SPIE Defense, Security and Sensing, 2009, April, 2009. LA-UR-09-01503
  • Karen A. Miller, Kendra L. Van Buren, Janette R. Frigo, Max Zeyen, Joshua P. Sackos, Paul M. Mendoza, Austin P. Wright, "Disparate Data Integration for advanced Facility Monitoring," IAEA Safeguards Symposium, Vienna, Austria, November, 2018. LA-UR-18-28226


Janette Frigo
Matt Handley
Dean Prichard
Kevin McCabe 


WVU – Vinod Kulathumani
Cornell University – Holger Klinck
The Nature Conservancy
US Fish and Wildlife Service – Palmyra Atoll
Guest Scientist – Don Enemark


Gabriel Holesinger
Jon Doorne