In recent years, drones have increasingly supported First Responders (FRs) in monitoring incidents and providing additional information. However, analysing drone footage is time-intensive and cognitively demanding. In this research, we investigate the use of AI models for the detection of humans in drone …

NarcoView aims to improve finding narcotic waste dumpsites by utilizing a methodology that reduces reliance on current reporting methods. The project faces challenges in data- and main question is: How does the NarcoView project ensure secure handling of data used on the platform and customize …

The NDT methods currently used in aviation MRO are predominantly labour-intensive and time-consuming processes performed by human operators throughout the lifespan of an aircraft. These techniques are time-consuming, require perpetual training and are highly dependent on the operator's skills. Thus, …

Oral presentation of AHFE conference paper (accepted/in-press)

Oral presentation of AHFE conference paper (accepted/in-press)

Machine learning models have proven their use in the medical field, assisting physicians in early diagnosis of serious diseases. Diabetic retinopathy is one of such diseases that could benefit from early detection, but the amount of data available to train accurate models is limited. This challenge could …

ABSTRACT Purpose: This short paper describes the dashboard design process for online hate speech monitoring for multiple languages and platforms. Methodology/approach: A case study approach was adopted in which the authors followed a research & development project for a multilingual and multiplatform …

Exploring virtual assurance of a Partially Automated Driving System during car following conditionsTraditionally, driving simulators are used to investigate driver responses to manipulations in the driver-vehicle-environment triangle, such as adding distractors or introducing low visibility driving conditions. …

The goal of this study was to develop an automated monitoring system for the detection of pigs’ bodies, heads and tails. The aim in the first part of the study was to recognize individual pigs (in lying and standing positions) in groups and their body parts (head/ears, and tail) by using machine learning …