Cognitively stimulating experiences are fundamental to supporting the welfare of zoo-housed animals. Puzzle-feeders are often initially engaging, but require frequent human intervention and often lack adaptability to support animals’ sustained cognitive engagement. We developed a modular adaptive puzzle-feeder designed to support user agency, independence, and multisensory feedback. The system was deployed over four weeks with an Arctic fox (Vulpes lagopus) across progressive difficulty levels and piloted with two coatis (Nasua narica). Combining HCI and animal science methodologies, we assessed (1) multisensory engagement, (2) changes in behavioral diversity and habitat utilization, (3) adaptation to puzzle complexity, and (4) impact on human stakeholders. Results show strong sustained engagement (46.5% time-budget), increased behavioral diversity, habitat exploration, strategic problem-solving, and positive keeper and visitor reactions. This work highlights how technology can support animal welfare and visitor experience, and how mixed HCI and ethological methods enable holistic evaluation of enrichment and animal usership.

The demand for passenger transportation, especially by road, has been increasing due to globalisation, resulting in further delays and traffic congestion. This paper addresses issues to minimise delays and traffic congestion using source and destination information in an urban environment. A journey is defined as the traversal of several road links and junctions. The delays on the links are analysed using M/M/K Markov technique. The delays at a junction are examined using the Zero-Server Markov Chain technique. In order to study multiple junctions, this technique is combined with the Jackson Network model. This combined approach is then used to evaluate the delays at multiple junctions using the Middlesex University VANET Testbed (a real-time vehicular network in London, UK). Initial results indicate that there is more congestion at traffic junctions and hence the Markov Chain analysis will allow better traffic algorithms to reduce congestion at traffic junctions, resulting in reduced journey times as well as less congestion.