The present social and environmental challenges, the impact of climate change andthe pandemic, revealed the urgency and the opportunity to rethink urban designthrough its renewed spaces and temporalities. The pandemic offered a ‘natural exper-iment’ to explore and develop new perspectives, making public spaces more resilient.Contributing towards a rethink of these spaces, the present paper explores adaptivearchitecture with responsive technologies and their capability of shaping public spacesto constitute a conversation piece with the surrounding environment. This approachcombines and reflects different disciplinary fields: architecture, civic interaction and ur-ban design. The exploration works around a speculative design case – produced aspart of broader research at the Amsterdam University of Applied Science in collabora-tion with the Master in Digital Design.
Abstract: Sedentary behaviour in children, four years of age and older, has increased over the last decades. These children become physically less skilled, which demotivates them for regular sports activities. They become susceptible to health risks such as obesity and have a heightened chance to develop depression and a lower self-esteem. Sports professionals acknowledge that these children in time become unable to keep up with the sports education pace, leaving them prone to social exclusion as well.Exergames seem promising in their potential to increase the amount and quality of physical exercise in this group. Moreover, they offer strategies to motivate children to a more active and healthier lifestyle. However, some issues remain unclear regarding their applicability and individual fittingness. For one thing sports professionals have little to no experience using exergames in physical education, let alone understand which games could be appropriate to structurally activate said children. In addition, existing exergames regularly lack a suitable degree of adaptivity regarding what a child is physically capable of, which psychological needs should be addressed, and to what inactive children find appealing in terms of gameplay.The aim of our research project is to build a first prototype of an adaptive platform for exergames to motivate inactive children to structurally engage in physical exercise more, and better. The participative design method we used in our preliminary qualitative research led to a better understanding of the barriers to move and the psychological needs children have when it comes to physical exercise. We made a first global list of requirements for the adaptive platform and an overview of necessary design directions.Future pursuits in this project include a participative design research study amongst both children and sports professionals, and a thorough review of the literature and state of the art knowledge. We will use this knowledge to create a first prototype of an adaptive platform in collaboration with a serious game company and an organisation of sport professionals. After user testing we will use the evaluation findings as a baseline for future measurements regarding the adaptation of suggested exergames and to formalize and disseminate found design guidelines.
Het RAAK-MKB project Aerobic heeft zich gericht op modulaire robotica (grippers, handling en vision systemen) en specifiek binpicking. Binnen dit project is veel kennis opgedaan die heeft geresulteerd in diverse fysieke demonstrators (robotopstellingen t.b.v. binpicking). Deze nieuw opgedane kennis is erg bruikbaar voor zowel de beroepspraktijk als studenten. Daarnaast is deze kennis praktisch gemaakt en laagdrempelig toepasbaar. Dat maakt het relevant voor (her)gebruik middels het nieuwe open-acces e-learning platform van Fontys: Open Learning Labs. Door trainingsmateriaal te ontwikkelen dat betrekking heeft op onder andere het aspect “binpicking” met behulp van robots, worden toekomstige engineers (onze studenten) en zittend personeel bij bedrijven bekend met nieuwe technieken die toepasbaar zijn in diverse sectoren waar met robots gewerkt wordt. Het doel van deze Top-up aanvraag is tweeledig: 1) het vergroten van de zichtbaarheid van de resultaten uit het initiële RAAK-project, zowel richting onderwijs, onderzoek en beroepspraktijk. 2) het realiseren van trainingsmateriaal t.b.v. het praktisch toepassen van kennis die betrekking heeft op de gerealiseerde binpicking-demonstrator binnen het RAAK project. Dit zal bij toekenning stapsgewijs uitgevoerd worden: 1. Definiëren inhoud lesmodule en bijbehorende didactische werkvormen 2. Realisatie PR- & instructievideo's en onderwijsopdrachten 3. Realisatie E-learning lesmodule Dit alles gekoppeld aan het open-acces e-learning platform Open Learning Labs van Fontys.
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
