2023
Lykourinas, Antonios; Skodras, Athanassios
ENF4GR: Hosting ENF of Mainland Greece Technical Report
2023.
Abstract | Links | BibTeX | Tags: ENF, Web Application Development
@techreport{Lykourinas2023_2,
title = {ENF4GR: Hosting ENF of Mainland Greece},
author = {Antonios Lykourinas and Athanassios Skodras},
url = {http://dsip.ece.upatras.gr/wp-content/uploads/2023/06/DSIP-TR003-30.05.2023.pdf},
year = {2023},
date = {2023-05-30},
abstract = {Electrical Network Frequency (ENF), which refers to the instantaneous frequency of a power distribution network, is adopted for a wide range of applications. Taking into consideration both the lack of reference databases for different power grids all around the world and also the lack of Websites for hosting ENF-related data, we decided to create a website featuring some of the latest web development technologies in order to visually represent ENF-related data obtained from our reference database which is being updated by a Raspberry Pi ENF monitoring system.},
keywords = {ENF, Web Application Development},
pubstate = {published},
tppubtype = {techreport}
}
Electrical Network Frequency (ENF), which refers to the instantaneous frequency of a power distribution network, is adopted for a wide range of applications. Taking into consideration both the lack of reference databases for different power grids all around the world and also the lack of Websites for hosting ENF-related data, we decided to create a website featuring some of the latest web development technologies in order to visually represent ENF-related data obtained from our reference database which is being updated by a Raspberry Pi ENF monitoring system.
Lykourinas, Antonios; Skodras, Athanassios
Real-time ENF monitoring with a Raspberry Pi 3 Model B Technical Report
2023.
Abstract | Links | BibTeX | Tags: ENF, Hilbert, Power Grid Frequency Analysis, Raspberry Pi
@techreport{Lykourinas2023_1,
title = {Real-time ENF monitoring with a Raspberry Pi 3 Model B},
author = {Antonios Lykourinas and Athanassios Skodras},
url = {http://dsip.ece.upatras.gr/wp-content/uploads/2023/06/DSIP-TR002-29.05.2023.pdf},
year = {2023},
date = {2023-05-29},
urldate = {2023-05-29},
abstract = {Electrical Network Frequency (ENF), the instantaneous fluctuation of the power grid’s frequency around its nominal frequency due to the imbalance between energy production and consumption, was initially used in forensics applications and since then it has been adopted into a wide range of applications. In this report, the development of a real-time ENF monitoring system is described. The whole system is based on a Raspberry Pi Model B computer, which performs the filtering of the digital signal, the calculation of the ENF values and finally the storage of the frequency values in real-time. Signal capturing is achieved by means of a sensing circuit that we have also designed and constructed. The performance of the system has been compared to existing solutions, thus validating its measuring accuracy},
keywords = {ENF, Hilbert, Power Grid Frequency Analysis, Raspberry Pi},
pubstate = {published},
tppubtype = {techreport}
}
Electrical Network Frequency (ENF), the instantaneous fluctuation of the power grid’s frequency around its nominal frequency due to the imbalance between energy production and consumption, was initially used in forensics applications and since then it has been adopted into a wide range of applications. In this report, the development of a real-time ENF monitoring system is described. The whole system is based on a Raspberry Pi Model B computer, which performs the filtering of the digital signal, the calculation of the ENF values and finally the storage of the frequency values in real-time. Signal capturing is achieved by means of a sensing circuit that we have also designed and constructed. The performance of the system has been compared to existing solutions, thus validating its measuring accuracy
2021
Frantzolas, Christos
Electrical Network Frequency Recording using a Raspberry Pi 3, Model B Technical Report
Department of Electrical and Computer Engineering University of Patras, no. DSIP/TR001, 2021.
Abstract | Links | BibTeX | Tags: Complex Trace Analysis, ENF, Python, Raspberry Pi
@techreport{Frantzolas2021,
title = {Electrical Network Frequency Recording using a Raspberry Pi 3, Model B},
author = {Christos Frantzolas},
url = {http://dsip.ece.upatras.gr/wp-content/uploads/2021/03/DSIP-TR001-10.03.2021.pdf},
year = {2021},
date = {2021-03-10},
number = {DSIP/TR001},
address = {University of Patras},
institution = {Department of Electrical and Computer Engineering},
abstract = {The Electrical Network Frequency (ENF) Criterion is a forensic technique used to identify the authenticity of a digital recording. When using this method, frequency changes are compared between the background utility hum in the evidence and long-term records of the ENF. Recording this frequency (also called mains frequency or power line frequency) can be performed with the usage of a Raspberry Pi - a small single-board computer. The device’s low cost and portability present a great advantage, but the limited computational power and storage capacity create unique problems on how to compute and store the ENF recordings. In this report, a solution is presented, in which the utility signal is first recorded through the audio port of the device, and the EN instantaneous frequency is computed using the Hilbert transform.},
keywords = {Complex Trace Analysis, ENF, Python, Raspberry Pi},
pubstate = {published},
tppubtype = {techreport}
}
The Electrical Network Frequency (ENF) Criterion is a forensic technique used to identify the authenticity of a digital recording. When using this method, frequency changes are compared between the background utility hum in the evidence and long-term records of the ENF. Recording this frequency (also called mains frequency or power line frequency) can be performed with the usage of a Raspberry Pi - a small single-board computer. The device’s low cost and portability present a great advantage, but the limited computational power and storage capacity create unique problems on how to compute and store the ENF recordings. In this report, a solution is presented, in which the utility signal is first recorded through the audio port of the device, and the EN instantaneous frequency is computed using the Hilbert transform.