This is a thesis on developing software that detects things using machine learning and computer vision algorithms. Furthermore, the application includes the use of RTDE to operate a robotic arm that can take the fruit and deliver it to a certain location.

Recent years have seen a massive growth in ethical and legal frameworks to govern data science practices. Yet one of the core questions associated with ethical and legal frameworks is the extent to which they are implemented in practice. A particularly interesting case in this context comes to public …

The use of algorithmic tools by journalists for information-gathering has received particular attention in recent years. While it might facilitate the research process, there are also concerns about their impact on journalism. Based on reconstruction interviews with 27 journalists, we first answer the …

The aviation industry needs led to an increase in the number of aircraft in the sky. When the number of flights within an airspace increases, the chance of a mid-air collision increases. Systems such as the Traffic Alert and Collision Avoidance System (TCAS) and Airborne Collision Avoidance System (ACAS) …

Remaining Useful Life (RUL) estimation is directly related with the application of predictive maintenance. When RUL estimation is performed via data-driven methods and Artificial Intelligence algorithms, explainability and interpretability of the model are necessary for trusted predictions. This is especially …

Assigning gates to flights considering physical, operational, and temporal constraints is known as the Gate Assignment Problem. This article proposes the novelty of coupling a commercial stand and gate allocation software with an off-the-grid optimization algorithm. The software provides the assignment …

B4B is a multi-year, multi-stakeholder project focused on developing methods to harness big data from smart meters, building management systems and the Internet of Things devices, to reduce energy consumption, increase comfort, respond flexibly to user behaviour and local energy supply and demand, and …

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 …

This study focuses on forecasting tomato sap flow in relation to various climate and irrigation variables. The proposed study utilizes different machine learning (ML) techniques, including linear regression (LR), least absolute shrinkage and selection operator (LASSO), elastic net regression (ENR), support …

All Gone is a series of experiments with AI that build on existing collections of climate fiction to create much-needed new climate imaginaries. As the climate crisis is also a “crisis of imagination” (Ghosh, 2016), this project turns to the art genre that is best at forecasting and imagining alternative …