@proceedings {600,
	title = {SMART -- Expanding Array of Low Cost Magnetometers},
	year = {2022},
	month = {03/2022},
	publisher = {HamSCI},
	address = {Huntsville, AL},
	abstract = {<p>The SMART (Surface Magnetic Assessment in Real Time) Network is a collection of 14 UCLA ground magnetometer systems across the US. Our main objective is to investigate outstanding questions in both travel-time and normal-mode magnetoseismologies. These detectors are very effective but expensive to build and maintain.\&nbsp; SMART is a project to spread sensors to schools and perhaps private individuals. Broader impacts include training students in magnetic field measurements and geospace science. This provides outreach activities to schools hosting SMART systems and will provide SMART magnetometer data collected in the contiguous US to the public. 2020/2021 was time to investigate various solid state and coil systems to find detectors robust, simple, quiet and precise enough to give us reasonable measurements. Solid state and coil systems were built and compared. Finally, two systems met our requirements: RM3100 and FLC-100 coil sensors. Buried in the ground (away from temperature changes and movement) the two sensor systems compare favorably to the Falcon Search Coil system used here for the past 11 years. We will show comparative data in quiet and active times.\&nbsp; We also discuss the various sensitivities of these sensors to electronic and temperature\&nbsp; changes. We present a simple Raspberry Pi system that samples each of these detectors and uploads the data to google and adafuit.com clouds. We present details on construction and wiring of the system. Especially important is how to insulate and bury sensors to they see real magnet changes. Also presented will be estimated costs and availability of components. Our goal is to provide a simple and low-cost system for local measurement of the geomagnetic field.\&nbsp; Additionally, the SMART team has restored many of the original UCLA sensors to operation and begun collection of data. As others build similar systems, we hope to bring many sensors into our array.</p>
},
	author = {Noel Petit and Peter Chi}
}
