Webster, Alexander John (2017) Using electricity smart meter data to calculate location and improve GIS data integrity. [USQ Project]
Abstract
In the digital age, data is pervasive, and its value comes from the insights that can be derived and not merely capturing and storing it. This value, or insight, comes from the correlation between two or more datasets. The problem this dissertation explores is how to gain insights from smart meter data to align location information of enterprise information systems.
The study aimed to determine if it is possible to calculate the location of a smart meter from signal strength and if this location is accurate enough to improve enterprise information systems data quality and integrity.
The study focused on ten properties in the town of Mildura, Victoria, Australia. Data was acquired for these properties and analysed. Five data analysis methods were applied to the research. Data visualisation and Exploratory Spatial Data Analysis were used to explore the data and identify underlying patterns and trends. Spatial statistics, interpolation, and multi-lateration techniques were applied to determine the location of smart meters at the properties studied.
The results show that while data visualisation was useful, exploratory spatial data analysis tools were effective at identifying outliers in the datasets. Location determining techniques of mean centre and multi-lateration, using path loss exponent equation, with lease squares method both resolve meter location. Results at studied properties show mean centre average accuracy of 29.7m (standard deviation 19.7m) and multi-lateration average accuracy was 35.5m (standard deviation 24.6m).
This research concludes that it is possible to determine the location of a smart meter with the physical characteristics of the communication network.
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| Item Type: | USQ Project |
|---|---|
| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Armando Apan |
| Qualification: | Master of Spatial Science Technology (Geographical Information Systems) |
| Date Deposited: | 31 Oct 2024 06:08 |
| Last Modified: | 07 May 2025 02:53 |
| URI: | https://sear.unisq.edu.au/id/eprint/52086 |
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