The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system’s performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.
MULTIFILE
In this study, we investigated the effects of wearing a police uniform and gear on officers’ performance during the Physical Competence Test (PCT) of the Dutch National Police. In a counterbalanced within-subjects design, twenty-seven police officers performed the PCT twice, once wearing sportswear and once wearing a police uniform. The results showed clear indications that wearing a police uniform influenced the performance on the PCT. Participants were on average 14 seconds slower in a police uniform than in sportswear. Furthermore, performing the test in uniform was accompanied by higher RPE-scores and total physiological load. It seems that wearing a police uniform during the test diminishes the discrepancy between physical fitness needed to pass the simulated police tasks in the PCT and the job-specific physical fitness that is required during daily police work. This suggests that wearing a police uniform during the test will increase the representativeness of the testing environment for the work field.
The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system’s performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.
MULTIFILE
A unique testing ground where the creative sector and education work together to better understand the possibilities around volumetric video capturing. Within a volumetric studio, dozens of cameras capture all the movements of a living subject simultaneously. These recordings are converted into a fully moving and digital image, which results in an image that is barely distinguishable from reality. Chronosphere gives content creators and scientists the unique opportunity to experiment with volumetric capturing, using the newest volumetric studio within De Effenaar. There is room for a total of twenty projects, and proposals can be submitted.Partners:De Effenaar 4DR Studios Wildvreemd Natlab 360 verbeelding Dutch Rose Media Hyperspace Institute Fontys Hogescholen TU/e Center for Humans & Technology
The DALI project is carried out under the flag of Logistics Community Brabant. DALI is a testing ground aimed at lifting datafication in the logistics sector of the south of the Netherlands to a higher level, consequently future-proofing the sector.DALI focuses on developing knowledge-intensive logistics (smart logistics): devising, developing, demonstrating and applying new logistics working methods. The project’s aim is to create higher added value, increase the efficiency of goods flow handling, and maintain our international market position.Within DALI, 18 companies are carrying out cases in the area of datafication. The findings from the business cases are translated into generic applications for the logistics and supply chain sector and education. In addition, they are developing a community of data and logistics specialists.Partners:LCB, Gemeenten Breda en Tilburg, REWIN, Midpoint Brabant, Ministerie van Economische Zaken en Klimaat, Rijksoverheid, Provincie Noord-Brabant, Regio West-Brabant, Regio Hart van Brabant.In Dutch:Proeftuin van logistieke innovatie. DALI is een project waarin 18 bedrijven pilots uitvoeren om met datatoepassingen processen in de logistiek en supply chain te verslimmen. Vanuit deze pilots worden generieke toepassingen en tools op het gebied van data ontwikkeld voor MKB-bedrijven en het onderwijs.
Entangled Machines is a project by Mariana Fernández Mora that interrogates the colonial and extractive legacies underpinning artificial intelligence (AI). By introducing slowness and digital kinship as critical frameworks, the project reconceptualises AI as embedded within intricate social and ecological networks, thereby contesting dominant narratives of efficiency and optimisation. Through participatory, practice-based methodologies such as the Material Playground, the project integrates feminist and non-Western epistemologies to articulate alternative models for ethical, sustainable, and equitable AI practices. Over a four-year period, Entangled Machines develops theory, engages diverse communities, and produces artistic outputs to reimagine human-AI interactions. In collaboration with partners including ARIAS Amsterdam, Archival Consciousness, and the Sandberg Institute, the research seeks to foster decolonial and interdisciplinary approaches to AI. Its culmination will be an “Anarchive” – a curated assemblage of artistic, theoretical, and archival outputs – that serves as a resource for rethinking AI’s socio-political and ecological impacts.
