Evaluation of LoRa Mesh Networks for Disaster Response
dc.contributor.author | Poke, Brenton | |
dc.contributor.advisor | Suleyman Uludag, Ph.D | en |
dc.contributor.advisor | Stephen Turner, Ph.D. | |
dc.date.accessioned | 2023-05-25T18:27:51Z | |
dc.date.available | 2023-05-25T18:27:51Z | |
dc.date.issued | 2023-04-28 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/176695 | en |
dc.description.abstract | Natural and man-made disasters are becoming more prevalent and increasing in danger as climate change continues unabated and resources get scarce. Whether it be flood or terrorism, disasters displace people and it remains difficult to reach those in need when the disaster does strike. For years, mobile phone networks have been integral in responding to emergencies, but they rely on costly infrastructure that is prone to outages or outright attack. We propose a long-range, low-power mesh network infrastructure based on a new, still-developing networking protocol and embedded software implementation that seeks to fill the need of disaster communications telemetry gathering for a fraction of the cost of mobile phone networking infrastructure such as 4G LTE or 5G. While the protocol is simple, it was found to have an inadequate implementation at this stage. Error rates were high and bugs were found in implementation that led to an abnormal amount of time spent processing corrupted data, though power consumption was encouraging in spite of these conditions. We examine the strengths and weaknesses of this new protocol and suggest improvements to harden the implementation. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | LoRa | en_US |
dc.subject | IoT | en_US |
dc.subject | Wireless Networks | en_US |
dc.subject | Emergency Response | en_US |
dc.subject | Mesh Networking | en_US |
dc.title | Evaluation of LoRa Mesh Networks for Disaster Response | en_US |
dc.type | Thesis | en_US |
dc.subject.hlbsecondlevel | Computer Science | |
dc.subject.hlbsecondlevel | Physics | |
dc.subject.hlbtoplevel | Engineering | |
dc.subject.hlbtoplevel | Science | |
dc.contributor.affiliationum | Computer Science, Engineering and Physics, Department of | en_US |
dc.contributor.affiliationumcampus | Flint | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/176695/1/LoRa_Thesis.pdf | |
dc.identifier.doi | https://dx.doi.org/10.7302/7544 | |
dc.description.depositor | SELF | en_US |
dc.working.doi | 10.7302/7544 | en_US |
dc.owningcollname | Innovation and Technology, College of (UM-Flint) |
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