Many cities seek utilities monitoring with centrally managed Internet of Things (IoT) systems. This requires the development of numerous reliable low-cost wireless sensors, such as water temperature and flow meters, that can transmit information from subterranean pipes to surface-mounted receivers. Traditional radio communication systems are either unable to penetrate through multiple feet of earthen and manmade material, or have impractically large energy requirements which necessitate either frequent replacement of batteries, or a complex (and expensive) built-in energy harvesting system. Magnetic signaling systems do not suffer from this drawback: low-frequency electromagnetic waves have been shown to penetrate well through several feet of earth and water. In the past, these signals were too weak for practical use; however, this has changed with the recent proliferation of high-sensitivity magnetometers and compact rare-earth magnets.
A permanent magnet can be either rotated or vibrated to create an oscillating magnetic field. Utilizing this phenomenon, two types of magnetic transmitter are investigated in this study: one which uses a propeller to directly rotate a diametrically magnetized neodymium magnet; and a second in which a permanent magnet is oscillated back-and-forth across a novel soft-magnet Y-stator, which projects a switching magnetic field. In principle, these oscillating magnetic fields can be used for communication from subterranean infrastructure sensors—such as flow meters and leak detection devices—to an aboveground long range (LoRa) radio-networked Arduino receiver equipped with a magnetometer. Simulation software models the oscillating electromagnetic fields produced by the Y-stator configuration. Laboratory performance and field tests establish the capability of two IoT-linked leak-detection sensors that use magnetic telemetry. Remote datalogging demonstrates the viability of integrating many sensors and surface receivers into a single LoRa wireless IoT network.
| Identifer | oai:union.ndltd.org:uvm.edu/oai:scholarworks.uvm.edu:graddis-1842 |
| Date | 01 January 2018 |
| Creators | Orfeo, Daniel Jerome |
| Publisher | ScholarWorks @ UVM |
| Source Sets | University of Vermont |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate College Dissertations and Theses |
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