Background
The widespread use of multimedia content, especially images and videos, as the main form of communication has led to a significant increase in its creation and distribution across the internet and social media platforms. The information contained in these media files regarding their location of origin is invaluable for law enforcement and national security in their effort to effectively track and fight crime such as those on domestic violence, human trafficking, child exploitation and other illegal acts. Multimedia geolocation involves identifying the real-world location where a multimedia file, such as image or video, was captured. This task is gaining significance in digital forensics as the number of multimedia files involved in criminal investigations continues to grow.
Technology overview
This patented technology relates to a method and system for determining geolocation data derived from a video recording where GPS coordinates and other metadata have been removed to conceal the location where the video was captured.
The method uses an almost undetectable Electric Network Frequency (ENF) location-based signature that is naturally embedded in a video and/or audio that can identify the location of videos captured with a smartphone at intra-grid level. The ENF represents the frequency of the electrical power grid, fluctuating around its standard value of 60 Hz in North America and 50 Hz in Europe, Australia, and many other parts of the world. The intrinsic fluctuation characteristic of the ENF stems from the variations in the load on the power grid and are essentially random. The mains frequency, and hence the ENF, may influence internal components of a recording device such as the sensor readout, clock signals, or frame timing. An ENF signal may therefore be embedded in video and/or audio files generated by devices connected to the mains power or situated in surroundings where electromagnetic interference or acoustic mains hum is detectable.
Benefits
- Improved digital and media forensics to assist criminal investigations
- Identification of the inter- and intra-grid geographic source of the video when traditional methods are not available
Intellectual Property
An Australian provisional patent application No. 2025901222 titled “Method and System for Determining Intra-Grid Location from Video Recordings” was filed on 10 April 2025. Prior art searches have not revealed any documents or patents indicating prior discovery of the methodology. It is intended that patent protection will be sought in the major western markets including the United States of America, Canada, Europe, Japan and Australia.
Applications
- Digital and media forensics
- Criminal investigations concerning domestic violence, human trafficking, child exploitation and other illegal acts
Commercial opportunity
UniSC is seeking a commercialisation partner for the development and deployment of the Technology, in the target applications.
The commercialisation strategy for this technology is to demonstrate efficacy for a range of geographical locations and input video data sourced from multiple devices.
Brief note on scientific founders
Professor Li-minn Ang (Kenneth) – received his BEng (Hons) and PhD degrees from Edith Cowan University in Australia. He is currently the Professor of Electrical and Computer Engineering at the School of Science, Technology and Engineering at the University of the Sunshine Coast (UniSC).
Dr Ang has worked in Australian and UK universities including Monash University, University of Nottingham, Edith Cowan University, Charles Sturt University and Griffith University. Prior to joining UniSC, he was an Associate Professor at Griffith University.
His research interests are in computer, electrical and systems engineering including Internet of Things, intelligent systems and data analytics, machine learning, visual information processing, embedded systems, wireless multimedia sensor systems, reconfigurable computing (FPGA) and the development of innovative technologies for real-world systems including smart cities, engineering, agriculture, environment, health and defence.
Mr Ericmoore Tochukwu Ngharamike – received the bachelor’s degree in computer science from the Federal University of Technology, Owerri, Nigeria, and the master’s degree in network computing from Coventry University, U.K. He is currently pursuing the Ph.D. degree with the University of the Sunshine Coast, Australia.
Before commencing the Ph.D. degree, he was a Lecturer and a Researcher with the Department of Computer Science, Federal University Oye-Ekiti (FUOYE), Nigeria. Ericmoore has also been serving as a sessional academic staff member in the School of Science, Technology and Engineering at the University of the Sunshine Coast, Australia, since July 2022. His research interests include the Internet of Things (IoT), wireless multimedia sensor systems, data analytics, AI and machine learning, and multimedia signal processing.
Contact
For further information concerning the commercial opportunity please contact:
Michael Finney – Commercialisation Advisor