Impact of RFID and EPCglobal on Critical Processes of the Pharmaceutical Supply Chain

The need to implement and guarantee effective item-level tracing systems is becoming more and more important for a wide range of business applications, such as manufacturing, logistics, healthcare, and anti-counterfeiting. Among these, the pharmaceutical supply chain, with millions of medicines moving around the world and needing to be traced at item level, represents a very interesting reference scenario. Furthermore, the growing counterfeiting problem raises a significant threat within the supply chain system. Recently, several international institutions (e.g. Food and Drug Administration, European Medicines Agency, European Federation of Pharmaceutical Industries and Associations, GS1) are encouraging the use of innovative solutions in healthcare and in the pharmaceutical supply chain, to improve patient safety and enhance the efficiency of the pharmaceutical supply chain, with better worldwide drug traceability

Behavior modeling for a beacon-based indoor location system

In this work we performed a comparison between two different approaches to track a person in indoor environments using a locating system based on BLE technology with a smartphone and a smartwatch as monitoring devices. To do so, we provide the system architecture we designed and describe how the different elements of the proposed system interact with each other. Moreover, we have evaluated the system’s performance by computing the mean percentage error in the detection of the indoor position. Finally, we present a novel location prediction system based on neural embeddings, and a soft-attention mechanism, which is able to predict user’s next location with 67% accuracy

Location Based Indoor and Outdoor Lightweight Activity Recognition System

In intelligent environments one of the most relevant information that can be gathered about users is their location. Their position can be easily captured without the need for a large infrastructure through devices such as smartphones or smartwatches that we easily carry around in our daily life, providing new opportunities and services in the field of pervasive computing and sensing. Location data can be very useful to infer additional information in some cases such as elderly or sick care, where inferring additional information such as the activities or types of activities they perform can provide daily indicators about their behavior and habits. To do so, we present a system able to infer user activities in indoor and outdoor environments using Global Positioning System (GPS) data together with open data sources such as OpenStreetMaps (OSM) to analyse the user’s daily activities, requiring a minimal infrastructure

Wearable Technologies and AI at the Far Edge for Chronic Heart Failure Prevention and Management: A Systematic Review and Prospects

Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data and facilitating the reliable diagnosis and management of critical and chronic diseases. The combination of edge computing and artificial intelligence has provided real-time, time-critical, and privacy-preserving data analysis solutions. However, based on the envisioned service, evaluating the additive value of edge intelligence to the overall architecture is essential before implementation. This article aims to comprehensively analyze the current state of the art on smart health infrastructures implementing wearable and AI technologies at the far edge to support patients with chronic heart failure (CHF). In particular, we highlight the contribution of edge intelligence in supporting the integration of wearable devices into IoT-aware technology infrastructures that provide services for patient diagnosis and management. We also offer an in-depth analysis of open challenges and provide potential solutions to facilitate the integration of wearable devices with edge AI solutions to provide innovative technological infrastructures and interactive services for patients and doctors

Thrombosis Is Reduced by Inhibition of COX-1, but Unaffected by Inhibition of COX-2, in an Acute Model of Platelet Activation in the Mouse

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Performance Evaluation of end-to-end security protocols in an Internet of Things

Wireless Sensor Networks are destined to play a fundamental role in the next-generation Internet, which will be characterized by the Machine-to-Machine paradigm, according to which, embedded devices will actively exchange information, thus enabling the development of innovative applications. It will contribute to assert the concept of Internet of Things, where end-to-end security represents a key issue. In such context, it is very important to understand which protocols are able to provide the right level of security without burdening the limited resources of constrained networks. This paper presents a performance comparison between two of the most widely used security protocols: IPSec and DTLS. We provide the analysis of their impact on the resources of embedded devices. For this purpose, we have modified existing implementations of both protocols to make them properly run on our hardware platforms, and we have performed an extensive experimental evaluation study. The achieved results are not a consequence of a classical simulation campaign, but they have been obtained in a real scenario that uses software and hardware typical of the current technological developments. Therefore, they can help network designers to identify the most appropriate secure mechanism for end-to-end IP communications involving constrained devices

GIS based Integration and Analysis of multiple source Information for Non-Proliferation Studies

In recent years the volume and variety of information that needs to be analysed in the context of non-proliferation have been increasing continuously Therefore, an integrated, all-source information analysis is paramount for an efficient and effective monitoring of the Non-Proliferation Treaty (NPT). The ¿Treaty Monitoring¿ workpackage of the LIMES research project addressed this issue by developing an integrated platform supporting the non-proliferation image analyst in verifying treaty compliance. The main benefits of the platform are (i) integrating information from multiple sources and time-frames, including satellite imagery, site models, open source information, reports, etc; (ii) improved information management using a GIS-based platform and (iii) enhanced methodologies for satellite image analysis. The platform components facilitate the analysis by highlighting changes and anomalies, which are potentially safeguards-relevant and by providing quantitative measurements which are not readily available from the images. It improves the efficiency and effectiveness of the information assessment by providing all-source integration capabilities, which allow to easily access supporting collateral information (e.g. Open Source information) from an image analysis task, an vice versa. The paper presents the components of the integration platform and the results of the demonstration which monitored the construction of a nuclear reactor in Olkiluoto, Finland.JRC.E.9-Nuclear security (Ispra

An IoT-Aware Smart System Exploiting the Electromagnetic Behavior of UHF-RFID Tags to Improve Worker Safety in Outdoor Environments

Recently, different solutions leveraging Internet of Things (IoT) technologies have been adopted to avoid accidents in agricultural working environments. As an example, heavy vehicles, e.g., tractors or excavators, have been upgraded with remote controls. Nonetheless, the community continues to encourage discussions on safety issues. In this framework, a localization system installed on remote-controlled farm machines (RCFM) can help in preventing fatal accidents and reduce collision risks. This paper presents an innovative system that exploits passive UHF-RFID technology supported by commercial BLE Beacons for monitoring and preventing accidents that may occur when ground-workers in RCFM collaborate in outdoor agricultural working areas. To this aim, a modular architecture is proposed to locate workers, obstacles and machines and guarantees the security of RCFM movements by using specific notifications for ground-workers prompt interventions. Its main characteristics are presented with its main positioning features based on passive UHF-RFID technology. An experimental campaign discusses its performance and determines the best configuration of the UHF-RFID tags installed on workers and obstacles. Finally, system validation demonstrates the reliability of the main components and the usefulness of the proposed architecture for worker safety