1,721,117 research outputs found
A practical computer based vision system for posture and movement sensing in occupational medicine
No full textBack pain and upper extremities injuries due to overexertion account for over twenty percent of leave days from work in the US. This explains why a vast amount of initiatives have been, to this date, carried out aiming at reducing the occurrence of such type of injuries. However, although such type of lesions are among the most studied in occupational medicine, no automatic detection and prevention technologies are pervasively available, to this date, at workplaces. Such deficiency is ascribable to the absence of any flexible and cost-effective tectaphnology that may play such role. This work aims at filling such gap: the contribution of this paper is the design and implementation of a movement-posture computer-vision based system that, performing as a sensor, can detect overexertion movements, helping avoid the most common injuries that these cause. Such tasks are carried out with the use of a simple webcam, thus not requiring any expensive or specialized (e.g., Microsoft Kinect) hardware device. The proposed technology is, hence, easily affordable by any type of company and production plant throughout the world and easy adaptable to recognize and detect a wide set of movements and postures. The validity of such approach is demonstrated in realistic settings through a wide set of experiment
Effects of the Uncertainty of Interpersonal Communications on Behavioral Responses of the Participants in an Immersive Virtual Reality Experience: A Usability Study
Full text linkTwo common difficulties which people face in their daily lives are managing effective communication with others and dealing with what makes them feel uncertain. Past research highlights that the result of not being able to handle these difficulties influences people’s performance in the task at hand substantially, especially in the context of a social environment such as a workplace. Perceived uncertainty of information is a key influential factor in this regard, with effects on the quality of the information transfer between sender and receiver. Uncertainty of information can be induced into the communication system in three ways: when there is any kind of information deficit that makes the target message unclear for the receiver, when there are some requested changes that could not be predicted by the receiver, and when the content of the message is so interconnected and complex that it limits understanding. Since uncertainty is an inseparable feature of our lives, studying the effects that different levels of it have on individuals and how individuals nevertheless accomplish the tasks of daily living is of high importance. Modern technologies such as immersive virtual reality (VR) have been successful in providing effective platforms to support human behavioral and social well-being studies. In this paper, we suggest the design, development, and evaluation of an immersive VR serious game platform to study behavioral responses to the uncertain features of interpersonal communications. In addition, we report the result of a within-subject user study with 17 participants aged between 20 and 35 and their behavioral responses to two levels of uncertainty with subjective and objective measures. The results convey that the application successfully and meaningfully measured some behavioral responses related to exposure to different levels of uncertainty and overall, the participants were satisfied with the experience
Empowering Digital Twins with eXtended Reality Collaborations
Full text linkThe advancements of Artificial Intelligence, Big Data Analytics, and the Internet of Things paved the path to the emergence and use of Digital Twins (DTs) as technologies to “twin” the life of a physical entity in different fields, ranging from industry to healthcare. At the same time, the advent of eXtended Reality (XR) in industrial and consumer electronics has provided novel paradigms that may be put to good use to visualize and interact with DTs. XR technologies can support human-to-human interactions for training and remote assistance and could transform DTs into collaborative intelligence tools. We here present the Human Collaborative Intelligence empowered Digital Twin framework (HCLINT-DT) integrating human annotations (e.g., textual and vocal) to allow the creation of an all-in-one-place resource to preserve such knowledge. This framework could be adopted in many fields, supporting users to learn how to carry out an unknown process or explore others’ past experiences. The assessment of such a framework has involved implementing a DT supporting human annotations, reflected in both the physical world (Augmented Reality) and the virtual one (Virtual Reality). The outcomes of the interface design assessment confirm the interest in developing HCLINT-DT-based applications. Finally, we evaluated how the proposed framework could be translated into a manufacturing context
Fast-FMS: Fast multimedia across 3G mobile networks
No full textFast-FMS is a new network protocol designed to support fast and effective multimedia delivery in 3G networks. In particular, Fast-FMS provides a reliable session between two mobile customers that want to transmit multimedia and data while on a voice conversation. The protocol leverages the multi-RAB feature of 2.5+ cellular networks to provide a new almost-real-time class of services that fill the gap between the costly circuit-switched video-call service and the basic services based on MMS. © 2005 IEEE
Evaluating Human Aesthetic and Emotional Aspects of 3D generated content through eXtended Reality
Full text linkThe Metaverse era is rapidly shaping novel and effective tools particularly useful in the entertainment and creative industry. A fundamental role is played by modern generative deep learning models, that can be used to provide varied and high-quality multimedia content, considerably lowering costs while increasing production efficiency. The goodness of such models is usually evaluated quantitatively with established metrics on data and humans using simple constructs such as the Mean Opinion Score. However, these scales and scores don't take into account the aesthetical and emotional components, which could play a role in positively controlling the automatic generation of multimedia content while at the same time introducing novel forms of human-in-the-loop in generative deep learning. Furthermore, considering data such as 3D models/scenes, and 360° panorama images and videos, conventional display hardware may not be the most effective means for human evaluation. A first solution to such a problem could consist of employing eXtendend Reality paradigms and devices. Considering all such aspects, we here discuss a recent contribution that adopted a well-known scale to evaluate the aesthetic and emotional experience of watching a 360° video of a musical concert in Virtual Reality (VR) compared to a classical 2D webstream, showing that adopting fully immersive VR experience could be a possible path to follow
Models and performance evaluation of event goodput in sensor platforms
No full textDespite the introduction of novel energy harvesting technologies, the lifetime of a sensor platform remains one of its most important performance metrics. Performance, however, may also be assessed in terms of the fraction of events which may successfully/unsuccessfully be detected and reported within a time interval of interest, i.e., mission time. Such a performance metric, here termed event goodput, is key for all random event-driven networks, ranging from surveillance and intrusion detection applications operating in time critical scenarios, to mobile and wearable crowd-sensed ecosystems, where mobile sensors are utilized by a number of different applications. When reporting the appearance of a series of possible, but unknown, phenomena, predicting which event goodput may be obtained during the planned mission time is challenging. In this paper, we address this issue by reducing the network-wide problem to the analysis of the performance of individual nodes, in terms of their capability of handling given fractions of event arrivals under fixed probabilistic guarantees. This is obtained as a function of mission time, event arrival and energy consumption models of different, detection and communication schemes, all realistic
Analyzing and shaping the lifetime and the performance of barrier coverage sensor networks
No full textIn this work we model and provide the means to extend the lifetime of a barrier coverage sensor network deployed fortarget detection. We consider a scenario where sensors are randomly dropped on a bidimensional field in order to detect target traversals which occur in a stochastic way within a critical mission time. Once a target enters a sensor's detection area, the sensor transmits such information to a cluster head, in charge of receiving and retransmitting the messages received from the sensors deployed on the field. The contribution of this work is fourfold. We first identify the sensing nodes whose behavior is key to model the duration of sensing operations, assuming prior arrival and mobility models for target traversals. We then proceed, providing a heuristic estimation of the traffic received by the cluster head to quantify its energy requirements, resorting to specific lifetime definitions. We also evaluate the relationship between our probabilistic and heuristic models and the time until the barrier remains capable of detecting and reporting the traversal of any target to a sink, as obtained by simulation. Finally, we show how the lifetime of such network may be shaped, with the use of a sequential activation mechanism, for example to combat the traversals of adversaries exploiting the lifetime models obtained in this work
La realtà virtuale immersiva in una classe scolastica. Uno studio esplorativo in un istituto di istruzione superiore
No full textIl contributo presenta gli esiti di un quasi-esperimento che intende
avviare l’indagine sull’efficacia e l’efficienza dell’uso della realtà
virtuale immersiva (IVR) durante l’attività didattica. Sono stati
coinvolti 34 studenti di una classe prima di un istituto medio
superiore del Nord Italia. I dati sono stati raccolti mediante
questionari, prove di valutazione e videoregistrazioni. I risultati hanno evidenziato che solo in due casi gli studenti hanno subito limitazioni causate dalla posizione dei compagni, ed un numero esiguo di volte è emersa qualche difficoltà di movimento dovuta alla configurazione dell’aula. Un dato rilevante emerso da questo lavoro sono le numerose posture innaturali assunte dagli studenti durante l’utilizzo della IVR all’interno di un contesto classe reale. A fronte di quest’ultimo risultato, i lavori futuri andranno in questa direzione. Infatti, è già in programma un’analisi tematica più approfondita, tramite un software specifico per questo tipo di compiti, sia per le posture degli studenti presenti in questa esperienza sia per quelle emerse in altre esperienze attualmente in svolgimento
Blockchain and Sensor-Based Reputation Enforcement for the Support of the Reshoring of Business Activities
No full textA common ground for many small businesses which are based and operate in Europe, capable today of standing against the waves of the globalization and the online economy, is the added value given by: (a) the quality of their services/products, and, (b) the trust they receive from their customers. Interestingly, such businesses are capable, in many cases, of maintaining the fidelity of a customer base, which is willing to pay more for their services or products when compared to what it would be paying when resorting to other channels. Such competitive advantage may be maintained as long as the quality of such services is high, one of the key factors that may also encourage and sustain the reshoring of many businesses to Europe. However, the quality of the products of many businesses is often hard to detect for a customer. Many exemplar cases may be individuated in organic farming and sustainable fashion and textiles. For instance, an average buyer may experience a very hard time when trying to distinguish at first sight an apple which has been obtained following organic protocols from one that has been produced following industrial procedures (e.g., use of chemical fertilizers). The same can be said for clothes, how may a consumer say whether given ethical rules and quality standards have been employed while weaving, knitting, felting, and braiding textiles? Because of these problems, in order to guarantee customers no malicious exploitations have been perpetrated, many of such companies resort to centralized and private certification programs. Unfortunately such certification programs can be expensive, long to implement, and even dishonestly exploited. In this scenario, we propose an integrated approach, based on two distinct and well-known ICT technologies, the Blockchain principle and sensor platforms, as a practical solution to preserve trust, increase the value of products and/or services and hence to encourage the reshoring of business activities. In particular, the model we here propose well applies to those business sectors whose actors share some type of immaterial asset related to the values that they convey with their products, which also, in many cases, represents their shared vulnerability point. Two exemplar business sectors where the proposed approach may be applied are represented by organic and sustainable productions in addition to all those which benefit from their association with specific geographical areas whose products, for given categories, are highly valued by customers (e.g., Made in Italy for fashion products). Because of the latter, the proposed approach may represent a viable pathway for the reshoring of companies from abroad
Using geosocial search for urban air pollution monitoring
Full text linkWhile Twitter and other Online Social Networks (OSNs) or microblogs are considered as a source of information for breaking news or uproarious and unexpected events, they could also be exploited as a dense worldwide sensors network for physical measurements. The corpus of geotagged posts from OSNs includes people's feedbacks about a wide range of topics, with precise temporal and geographical metadata, that can be used as a support or an improvement to hardware sensors. For instance, if collocated people, independently and at the same time, write posts complaining about high temperatures, it could effectively denote a raise of heat in that place. In this paper, we explore the feasibility to use a geographical search on social networks, that is, a geosocial search, about air pollution related posts, as effective air impureness measurements. We evaluate our assumption in large cities over three continents of the planet, where a minimum increment about the number of air pollution related posts in an area, indeed corresponds to a raise of minimum pollution values in such area. Such a correlation can be exploited to integrate and extend existing air pollution monitoring networks. At the end of the manuscript we propose to further employ the time series of posts returned by the geosocial search to predict next pollution values
- …
