Name
Abstract | ||
|---|---|---|
Smart electricity meters typically upload power consumption readings once or few times a day. Utility providers aim to increase the upload frequency in order to access consumption information in near real time, but the currently used data compressors fail to provide sufficient savings in this new scenario on the low-bandwidth, high-cost data connection. We propose a new compression method and data format for DLMS smart meter readings, which is significantly better with frequent uploads and makes it feasible to report every reading in near real time with the same or lower data sizes than the currently available compressors in the DLMS protocol. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ICC45855.2022.9838758 | ICC 2022 - IEEE International Conference on Communications |
Keywords | DocType | ISSN |
data compression,generalized deduplication,smart meter,DLMS,IoT | Conference | 1550-3607 |
ISBN | Citations | PageRank |
978-1-5386-8348-4 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marcell Fehér | 1 | 0 | 0.34 |
| Daniel E. Lucani | 2 | 236 | 42.29 |
| Morten Tranberg Hansen | 3 | 0 | 1.01 |
| Flemming Enevold Vester | 4 | 0 | 1.01 |