Mohamed Sedky

Associate Professor

School of Digital, Technologies and Arts

After received his BEng(Hons) in Electro-Physics and Communications in Alexandria University, Egypt, in 1996, Mohamed founded SKM communication systems with two partners. Between 1998 and 2003 he joined the department of electronics and communications of the Arab Academy for Science and Technology (AAST), Egypt, as a lecturer assistant. He finished his MSc degree in Communications and Electronics from the AAST in 2002.

Mohamed joined Staffordshire University in 2003 as a member of the research staff and a P/T lecturer; between 2005 and 2009 he was working as a computer vision consultant. In 2009, he gained a PhD from Staffordshire University, researching the application of physics-based image formation models to change detection in the context of Workplace Video Surveillance. He is the MSc Computer Science deputy award leader and he is the award leader of the proposed BSc Internet of Things award.

Since 2012, as Technical Director of a research spin-off, Adaptive Video Analytic (AVA) Technologies Ltd, Mohamed has been leading the research, development of real-time video processing algorithms and the deployment of new physics-based computer vision algorithms (e.g. moving object segmentation, skin detection and HDR). He has successfully released the first version of AVA, which includes four solutions, Detect, Protect, Count and Summarise. Mohamed has filed a UK patent, a PCT patent and a US patent in the use of Spectral-360® for object detection, targeting security, safety and business intelligence applications. His change detection technique was rated as the best in the world by an independent website www.changedetection.net. Mohamed was recently engaged successfully by a UK Police Authority, using AVA’s software to assist reducing the burden on police investigators.

Academic qualifications

  • PhD in computer vision
  • PGC in Research Supervision
  • PGC in Higher and Professional Education
  • MSc in Electrical and Electronic Engineering
  • BSc (Hons) in Electro-Physics and Communications

Expertise

  • Video Analytics
  • Computer vision
  • Computer Networks
  • IP Telephony & VOIP
  • Network security

Research interests

Current research interests include object recognition, Object tracking, object segmentation, and face detection.

Main Research Projects

  • A physics-based video analytics system for asset protection
  • A passenger counting system to capture escalator usage patterns: a technical feasibility project
  • Evaluation of video-based people counting technologies

Publications

  • “Object Segmentation Using Full-Spectrum Matching of Aledo Derived from Colour Images”
    US patent no. 2374109 12.10.2011 US 2012
  • “Image Processing”
    PCT patent application international application no. PCT/GB2009/002829 2010
    UK patent application no. 0822953.6 16.12.2008 GB 2 2008
  • “Classification of Smart Video Surveillance Systems for Commercial Applications,” in Proceedings of IEEE International Conference on Advanced Video and Signal Based Surveillance, Como, Italy, 2005
  • “Smart Video Surveillance for Workplace Applications: Implications, Technologies and Requirements,” in Proceedings of The 5th IASTED International Conference on Visualization, and Image Processing, Spain, 2005
  • “Adaptive Smart Clinical Pacemaker,” MWSCAS. The 46th IEEE Midwest Circuits and Systems Symposium, 2003.
  • “Control of Chaotic Heart Condition Using Synchronization,” Circuits and Systems, MWSCAS. The 2002 45th IEEE Midwest Symposium, 2002
  • “Control of Heart Fibrillation Using Chaotic Synchronization,” URCI Symposium, 2002

Exhibitions

  • Assisted Living Workshop
    Presenting the application of video analytics in fall detection, in the assisted living workshop sponsored by FCET, May 2011
  • The Eighth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies
    Representing the University by exhibiting and giving an invited talk in the Eighth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies CM2011/MFPT 2011 organised by BINDT (British Institute of Non-Destructive Testing) in Cardiff, sponsored by FCET, June 2011
  • Video Content Analysis Conference
    Representing the University by exhibiting in Video Content analysis Conference in London 2010
  • IFSEC Exhibition 2010
    Representing the University by exhibiting in IFSEC, one of the most prestigious security exhibitions, we have received both high praise and high commercial interest, 80+ enquiries received including some of the market leaders

Events

  • Pitching for Management Events
    Invited talk in pitching for management events in Oxford, Birmingham and Manchester February, March and April 2012
  • North Staffs Chamber of Commerce Business event
    Invited talk to North Staffs Chamber of Commerce members at a Let’s Talk Business event, to 100 businesses at an event in Stoke, sponsored by FCET, September 2011
  • British Computer Society
    Invited lecture to the North Staffs BCS, January 2011

Enterprise and commercial interests

Spin-off from Research

Mohamed is the Lead Researcher and Developer of Adaptive Video Analytic (AVA) Technologies Ltd and is the founder of Spectral-360®.

Spectral-360®

  • Spectral-360® is a complete physics-based object detection technology system that is qualified through test and demonstrations. It has been proven to provide the most accurate analysis available on the market today, across the complete range of lighting and camera conditions. Whilst providing a more reliable and efficient detection tool Spectral-360® allows users to analyse the characteristics of the objects and derive much deeper insights
    Adaptive Video Analytic (AVA) Technology Ltd.

  • AVA uses the physics of spectral analysis coupled with more traditional statistical techniques, to very accurately identify and alarm only those events that are of interest. It has created its unique portfolio, Spectral-360® to address the needs of industry and emerging markets and eradicate the most common issues faced in CCTV monitoring. The portfolio consists of four solutions, Detect, Protect, Count and Summarise

    • DETECT analyses CCTV footage and automatically generates a summarized video/report that logs the key events.
    • PROTECT Protects key assets by proactively identifying illegal removal.
    • Count enables counting of people for health and safety at events and for queue management as well as vehicle counting for traffic flow or car park management.
    • SUMMARISE allows investigators to view the footage, navigate and quickly jump to activity times and record a specific event. It allows investigators to quickly generate evidence that includes only key events suitable for court presentation.

Consultancy

Serco (Innovation Voucher)

  • Design and implement a video-based people counting solution

Centralweighing and Exactrak

  • Design and implement a video-based truck classification solution for weighing bridges

West Midland Technology Network (WMTN)

  • Design and implement a multi-sensor based communication server, which acquires and processes different sensor readings, a computer narrator module that alerts the operator and a set of alarms are sent to a wireless remote terminal, to an email and to a mobile device in form of SMS.

Advanced West Midland (AWM) (INDEX Voucher)

  • Carry out a feasibility study of the location and identification of buried utilities using electromagnetic radiation and cable avoidance tools (CAT)
  • Design a video-based industrial inspection prototype

Smart Light Devices (SLD), Aberdeen, Scotland

  • Deploy MVAS (Machine Vision Automated Server), a video-based meter tracking solution, where the abstract data is sent wirelessly (through GPRS or WLAN) to a mobile device, and computer graphics visualisation displays the meter movement on a remote terminal

Teaching

Module Leader

  • CESCOM10072-4: Fundamentals of Computer Networks (UG)
  • CE02004-5: LAN Switching and WAN Networks (Blended Learning)
  • CE00063-6: Router Security Technologies (Blended Learning)
  • CE00727-7: Networking Concepts (PG)


Teaching

  • CESCOM10149-6: Converged Networks (UG)


Top 250 Young University

Times Higher Education Young University Rankings 2020

Top 15 for Teaching Quality

The Times and The Sunday Times Good University Guide 2021

Top 15 for Social Inclusion

The Times and The Sunday Times Good University Guide 2021

Midlands University of the Year

Midlands Business Awards 2020