ITx Rutherford 2019 Speakers

Keynotes and Speakers for ITx Rutherford

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Istvan Lengyel

Eastern Institute of Technology

Istvan is a Senior Lecturer in the School of Computing, having come from a Senior IS Management role for a global biotech firm in the UK. Prior to his work in the UK, Istvan worked for a number of mulit-national global companies and the government sector within New Zealand and in the USA banking and lending sector. Istvan has successfully operated an IT security and consulting business and has been certified as a Prince2 Practitioner, ITIL, Cisco Certified Network Administrator (CCNA), Microsoft Certified Systems Engineer (MCSE) and Compaq/HP ASE. Istvan has over 20 years of solid business IT experience and is passionate about innovation and knowledge sharing.

A Traffic Management Prototype based on Computer Vision for Vehicle Detection and Tracking

Thursday 12:00pm - 12:30pm, CITRENZ (https://itp.nz/citrenz3)

Computer vision holds the capabilities of effectively performing tasks such as object classification and object recognition that the human visual system intuitively accomplishes. For this reason, computer vision is being increasingly employed as a tool to support and advance the management of traffic. Traffic management remains an issue in many regions of the world, due to numerous problems such as street obstacles, inefficient road signals, vehicles speeding, and underdevelopment of freeways.
Computer vision-driven systems have been developed to combat such problems, demonstrated by their role in e.g., travel assistance and navigation, parking management and enforcement, vehicle detection, real-Time traffic control, automated vehicle identification and license plate recognition. To help address present traffic concerns in New Zealand, this research project explores how computer vision can be applied to support traffic management systems by exploring the affordances and applicability of object recognition and object tracking for vehicles. Subsequently, this research project follows a design-based approach and is comprised of two sections. The first section posits the development of an effective computer vision-based framework and how a modern traffic management system can be developed. The next section concerns itself with implementation and testing of a computer vision-driven traffic management prototype in real-time. Finally, the implications for advanced computing education are discussed. Throughout the presentation, the authors will also cover the actual tools and devices used during the project.