1,721,037 research outputs found
A Digital Twin Architecture for Minimizing Injuries Risks with Personalized Regimens via IoT and Machine Learning
No full textWithin the sports domain, the athlete needs to prioritize and maximize performance while minimizing injuries and incidents. With this aim, in recent years, the research community has started to investigate how innovative solutions like the Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twins could be utilized to monitor and improve the level of customization in athletes' training. This paper presents a Digital Twin architecture that combines IoT and AI techniques to create a dynamic digital copy of the athlete. By using physiological data captured by the wearable sensors, the proposed system can implement a Machine Learning(ML) layer of classification aiding in the detection of fatigue levels, one of the most important parameters that influence athletes' performances. The collected data can be used to enrich the dynamic digital copies of the athletes in order to create more realistic simulations and help the interested stakeholders in their mission of enabling athletes to reach their best performance without sacrificing their overall health. The system we propose enhances fatigue management research by utilizing non-intrusive digital scenarios
An Innovative Approach for Predictive Maintenance of Home Boilers: ECOSMART Framework
No full textOne of the preeminent topics of the last decades is environmental sustainability which has attracted a huge amount of contributions also thanks to the growing interest in the so-called Green Deal initiative. Its requirements (e.g., optimizing energy consumption in all sectors) have already contributed to the enhancement and renovation of various fields, including the smart home one. In this context, one of the paradigms that is contributing the most is Predictive Maintenance (PdM). It emerges as a key strategy to offer a proactive approach to minimize energy waste and improve the longevity of home appliances. This paper proposes an innovative Adaptive ECOS-MART Boiler Management Framework that utilizes the Internet of Things (loT) and cutting-edge technologies to support the predictive maintenance of boilers in homes. Unlike the traditional boiler maintenance systems that only rely on static maintenance schedules and manual monitoring, our proposed framework introduces a Dynamic Predictive Maintenance (DPM) strategy. The proposed system employs loT sensors from real-time data, edge computing for local data processing, a cloud-based platform for advanced data analytics, and a user interface for maintenance alerts and live-time system monitoring. The paper discusses the effectiveness of the framework in reducing boiler downtime and maintenance costs and also in improving the energy efficiency of smart homes
Il ruolo dello standard KNX nell'impiantistica
No full textLo standard KNX offre la possibilità di migliorare e ottimizzare il consumo energetico e il comfort soprattutto nel building automation di grandi strutture pubbliche e aziendali dove il controllo capillare di dispositivi e impianti tecnologici rappresenta un’attività onerosa
IDA-Cage: a Demonstration of an RFID-based System for Animal Behavior Analysis
No full textWe present IDA-Cage, a smart system based on passive UHF RFID technology for animal behavior analysis. The proposed system represents an effectiveness, user-friendly and low-cost solution supporting researchers in their daily activity, able to overcome the limits of the common tools used in research laboratories. In the proposed demo, the benefits offered by the designed and developed system are shown through a presentation of its main features
An innovative e-health service based on EPCglobal and HL7 standards to support multiple intolerances
Full text linkICT technologies are playing an increasingly important role in the healthcare scenario, enabling the improvement of the patient safety and of the quality of care. Particular attention is focused on patients affected by specific problems such as intolerances or allergies. New item-level tracing systems based on RFID wireless technology and EPCglobal standard offer a solution for these problems, but they do not represent yet a complete solution. The idea to combine tracing systems with hospital information systems, compliant to Health Level Seven (HL7), represents a great solution. In this article, a prototypal ICT system based on the merging of the EPCglobal and HL7 standards is described, highlighting the potential benefits derived from this innovative e-health service for the main actors of the healthcare scenario
A Survey on Indoor Positioning Systems
No full textThis paper aims to provide the reader with a review of the main technologies explored in the literature to solve the indoor localization issue. Furthermore, some systems that use these enabling technologies in real-world scenarios are presented and discussed. This could deliver a better understanding of the state-of-the-art and motivate new research efforts in this promising field. Finally, focusing on one of the major challenges in the indoor localization field, i.e., the indoor animal tracking, existing indoor tracking systems have been reviewed and compared by analyzing advantages and drawbacks
An RFID-based Smart Cage for Animal Behavior Analysis
No full textAn innovative tracking system based on passive RFID technology in Ultra High Frequency band, able to perform behavior analysis of small laboratory animals, is presented in this work. The proposed smart system consists of both hardware and software components and it is able to extract main behavioral parameters exploiting raw animals tracking data captured by an RFID reader system. The proposed solution allows overcoming some limits of typical analysis methods commonly used in research laboratories for the same purposes, such as systems based on video technology and human observations, while providing the same information content. It is cheaper and guarantees better performance even in case of strong similarity among animals and in poor lighting conditions. Different tests were carried out in order to demonstrate the feasibility and effectiveness of the proposed system using laboratory mice. The software component is able to provide, via Web, a user-friendly tool containing main animal behavioral information such as statistical analysis and graphs regarding animal displacements, indication about the locomotor activity and detection of specific conditions including isolation and aggregation phenomena
An IoT-aware AAL System for Elderly People
No full textThe rapid aging of the population occurred in recent years has encouraged the development of several solutions aimed to guarantee a healthy and safe lifestyle to the elderly. In this paper, an Ambient Assisted Living (AAL) system has been designed in order to create better living conditions for older people. In this way, people can live independently longer in their own house with an improved quality of life. The proposed system includes several features. On the one hand, it is able to continuously monitor the health status of the elderly through data coming from heterogeneous sources (i.e., environmental sensors and medical devices). On the other hand, it is able to guarantee outdoor and indoor localization aimed to know the real-time position of the elderly both inside and outside their home. A remote reasoning system processes all collected data with the aim of generating appropriate events and alerts. The architecture was validated from a functional point of view through a proof-of-concept
An IoT-aware AAL System to Capture Behavioral Changes of Elderly People
Full text linkThe ageing of population is a phenomenon that is affecting the majority of developed countries around the world and will soon affect developing economies too. In recent years, both industry and academia are focused on the development of several solutions aimed to guarantee a healthy and safe lifestyle to the elderly. In this context, the behavioral analysis of elderly people can help to prevent the occurrence of Mild Cognitive Impairment (MCI) and frailty problems. The innovative technologies enabling the Internet of Things (IoT) can be used in order to capture personal data for automatically recognizing changes in elderly people behavior in an unobtrusive, low-cost and low-power modality. This work aims to describe the ongoing activities within the City4Age project, funded by the Horizon 2020 Programme of the European Commission, mainly focused on the use of IoT technologies to develop an innovative AAL system able to capture personal data of elderly people in their home and city environments. The proposed architecture has been validated through a proof-of-concept focused mainly on localization issues, collection of ambient parameters, and user-environment interaction aspects
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