The authors concept is based on the idea that mental health therapies which are already performed in the virtual reality, can be enhanced using wearable devices measuring body reactions, adding a completely new set of data for the therapeutic software. Those data, like heart rate or galvanic skin response, will be used in the feedback loop, for modifying VR projection or in therapy results assessment. Another goal is to use such additional feedback in psychological training in healthy patients, trying to improve their own behaviors and reactions, for example in stress coping situations. In the paper there is a description of a virtual reality-based anti-stress therapy concept using the wearable device feedback loop. The example is based on horticultural therapy, and was developed using Oculus Rift and Microsoft Band devices as virtual reality headset and physiological data source, respectively.

Tourism’s rapid growth has significant and negative effects on the environment, society, and economy. Sustainable tourism practices are essential in order to mitigate these effects. Virtual reality (VR) technologies offer the possibility of implementing sustainable tourism policies by providing immersive experiences that replace real ones. Moreover, VR can be a useful tool for the protection and promotion of cultural and natural heritage. The article discusses the potential directions for sustainable tourism using VR. This technology can reduce the burden on popular tourist sites without losing their value to visitors. Additionally, it can promote less popular destinations in the wider public awareness. A case study of the implementation of a virtual tour at the Pahlavon Mahmud Mausoleum in Khiva (Uzbekistan) is presented. The research method was designed to evaluate the acceptability of VR technology among a convenience sampling of n = 57 Gen Z consumers (university students 20–24 years of age), who completed interviews following their participation in a voluntary virtual walking tour. The research results suggest that VR can be an acceptable and useful tool for implementing sustainable tourism policies in the near future. Another conclusion is that virtual sightseeing should not fully replace onsite tourism.

This paper evaluates the feasibility of deploying locally-run Large Language Models (LLMs) for retrieval-augmented question answering (RAG-QA) over internal knowledge bases in small and medium enterprises (SMEs), with a focus on Polish-language datasets. The study benchmarks eight popular open-source and source-available LLMs, including Google’s Gemma-9B and Speakleash’s Bielik-11B, assessing their performance across closed, open, and detailed question types, with metrics for language quality, factual accuracy, response stability, and processing efficiency. The results highlight that desktop-class LLMs, though limited in factual accuracy (with top scores of 45% and 43% for Gemma and Bielik, respectively), hold promise for early-stage enterprise implementations. Key findings include Bielik's superior performance on open-ended and detailed questions and Gemma's efficiency and reliability in closed-type queries. Distribution analyses revealed variability in model outputs, with Bielik and Gemma showing the most stable response distributions. This research underscores the potential of offline-capable LLMs as cost-effective tools for secure knowledge management in Polish SMEs.

In this paper, the concept of monitoring the state of roads by means of standard mobile devices (smartphones) is discussed. Using motion data from the device’s sensors - accelerometer, gyroscope, compass - and in coordination with the current location from the Global Positioning System devices, it is possible to track and log any abnormal motion which may signal possible road infrastructure problems. The authors describe the software solution created to gather motion data, as well as the results of an experiment with a real-life car and real roads in different conditions. A pilot study carried out allows to test a developed application which provides precise localization of the artefacts occurring on the road.

In this study, we evaluate the influence of different cloud point filtering algorithms on the process of accurately dimensioning objects. This is critical in vision-based measurement systems, particularly for logistics and packaging applications. We assess three smoothing algorithms: bilateral...