Academic literature on the topic 'Mobile switching center'

Introduction: Patient centred care fosters a holistic approach of care switching the focus from a disease perspective to a patient's experience perspective. Patient centred care is of particular importance in the context of paediatric emergency medicine. Indeed, parents entering a paediatric emergency department (PED) are usually under stress caused by their children's illness, the unfamiliar setting of the PED and delays of care. All these factors can deteriorate their experience as well as the relationships between healthcare providers, the patients and their parents.

The communication network is one of the major assistances for disaster management purposes. At each disaster phase, the information flow between the disaster management departments and the population is critical, as it destroys the whole communication infrastructure where the base station to Mobile Switching Centre (MSC) connectivity is broken, power generators are exhausted, and the network may suffer from congestion. Even when radio equipment works, police officers, rescue teams, medical teams cannot communicate with each other because of incompatible radios. To analyze the characteristics of the geological environment in the disaster region and to alert the Disaster Management Department, this solution based on LoRa has been proposed. The penultimate goal of this paper is to fasten the rescue operations.

Nature is the basic condition for human survival and development. The nature-deficit disorder is a phenomenon put forward by American writer Richard Louv, that is, the complete separation of modern urban children from nature in the 21st century. Some experts explain that this desire and ignorance of nature is due to a lack of time to go outdoors, especially in the countryside. In real life, the population of "nature-deficit disorder" has expanded from children to adults. In order to let young people go into nature and understand the thousands of plants in nature, our team wants to design an application to popularize plants through a game-based live experience, so that users can learn more plant knowledge in fun. This design adopts the methods of the questionnaire survey, user interview, and literature retrieval to deeply discover the contemporary young people's understanding of plants, the development status of game-based science popularization apps at home and abroad, and the expected functions of users, to determine the information construction, visual image and interactive experience of the APP. Our team uses Rhino, Cinema 4D, Blender, Unity, Unreal and other software, combined with ergonomics to achieve scene modeling and rendering, to create a more realistic AR experience. The APP can guide users to enter the virtual map, take photos and punch cards through AR switching angles, and randomly obtain passes to unlock other maps. At the same time, users can click to view specific plant data, unlock the plant by completing key tasks such as roots, stems, and leaves, and bring it into the backpack for creation; the app can also game the handicraft which uses plants as raw materials, and guide users to create their own unique imprint. After the usability test, the respondents all believed that this APP could produce a better effect of plant science popularization in the game experience.

Current automated and hierarchical structured production processes can only insufficiently deal with the upcoming flexibilization, specifically regarding the requirements within Industry 5.0. The European project FAIRWork fosters the ‘democratization’ of decision-making in production processes, hence the participation of all involved stakeholders, by introducing a decentralized AI system. Hybrid decision-making faces the challenge first to digitally represent the relevant actors – here we propose the use of digital twins – and the interpretation of that digital twin, by a human expert or by a computer algorithm, to achieve better decisions. Research on existing sensors and data technology is required. In particular, the digital representation of human operators requires so called “Intelligent Sensor Boxes”.Method: ‘Intelligent Sensor Boxes’ are firstly determined by a dedicated group of sensors, such as, low-cost sensors, biosensors, wearables, human sensors, or even virtual sensors. Specific attention is dedicated to the development of the ‘Digital Human Sensor’ (DHS) applying AI-enabled Human Factors measurement technology. Each instantiation of a DHS provides a digital vector of Human Factors state estimates, such as, digital biomarkers on physiological strain, affective state, concentration, cognitive workload, situation awareness, fatigue. On the basis of these vectors, we determine cost function parameters associated with typical (inter-)actions in the work environment. We outline an advanced approach to represent cognitive strain by studying workload related to task switching, multitasking and interruption as well as monotony effects. Furthermore, we will investigate cognitive strain in the context of environmental parameters, such as, air quality, and combine IOT with wearable bio-sensor shirts, smartwatches with biosensors, eye tracking glasses, digital events, and spatiotemporal patterns from human-machine interaction. Cost functions for optimization algorithms can be related to well-being of the worker, this allows data processing with the goal to optimize according to several input factors using data that are derived from humans or from machines like lines and robots. Those data are described with corresponding meta data to result in a descriptive data lake. Such meta data correspond to domain specific models like the production process, the working environment model, or resources models. Data processing and optimization algorithms can then be applied on this data lake. This task complements existing data with human based sensor data and provided adapted data mining tools.Results: We present relevant methodologies for human-centered wearable or mobile measurement technologies for psychological and ecological constructs as typical instantiations of the novel framework. Furthermore, the embedding of the schema of ‘Intelligent Sensor Boxes’ into the framework of ‘Democratic AI-based Decision Support’ (DAI-DDS) is sketched and argued. An outlook on future research trajectories, in particular, in the context of the FAIRWork project, is outlined in detail, and Ethical guidelines are discussed. Experimentation Laboratories, such as, the Austrian Human Factors Lab, are not only considered and presented as a co-creation space to develop new ideas, but also as test, training and communication environment for and between all stakeholders of an innovation chain. Conclusion: The framework and development of ‘Intelligent Sensor Boxes’ with data quality control and including decision modules is described in the context of its relevance within production related environments. ‘Digital Human Sensors’ applying AI-enabled digital Human Factors measurement technology will represent key drivers in the novel Industry 5.0 era.