Deployment of embedded technologies is increasingly being examined in industrial supply chains as a means for improving efficiency through greater control over purchase orders, inventory and product related information. Central to this development has been the advent of technologies such as bar codes, Radio Frequency Identification (RFID) systems, and wireless sensors which when attached to a product, form part of the product's embedded systems infrastructure. The increasing integration of these technologies dramatically contributes to the evolving notion of a "smart product", a product which is capable of incorporating itself into both physical and information environments. The future of this revolution in objects equipped with smart embedded technologies is one in which objects can not only identify themselves, but can also sense and store their condition, communicate with other objects and distributed infrastructures, and take decisions related to managing their life cycle. The object can essentially "plug" itself into a compatible systems infrastructure owned by different partners in a supply chain. However, as in any development process that will involve more than one end user, the establishment of a common foundation and understanding is essential for interoperability, efficient communication among involved parties and for developing novel applications. In this paper, we contribute to creating that common ground by providing a characterization to aid the specification and construction of "smart objects" and their underlying technologies. Furthermore, our work provides an extensive set of examples and potential applications of different categories of smart objects.
Despite the popularity of current Radio Frequency Identification (RFID) and Wireless Sensor Networks (WSN), current research fails to propose the global vision that is needed for truly pervasive computing. In this paper we introduce our effort to build a global standard infrastructure for WSN and RFID based on the EPCglobal standard Architecture Framework. By leveraging the EPC Network infrastructure, our proposed EPC Sensor Network will effectively provide standardized WSN/RFID integration framework to support sensor data sharing.
The Internet of Things (IoT) concept is being widely presented as the next revolution toward massively distributed information, where any real-world object can automatically participate in the Internet and thus be globally discovered and queried. Despite the consensus on the great potential of the concept and the significant progress in a number of enabling technologies, there is a general lack of an integrated vision on how to realize it. This paper examines the technologies that will be fundamental for realizing the IoT and proposes an architecture that integrates them into a single platform. The architecture introduces the use of the Smart Object framework to encapsulate radio-frequency identification (RFID), sensor technologies, embedded object logic, object ad-hoc networking, and Internet-based information infrastructure. We evaluate the architecture against a number of energy-based performance measures, and also show that it outperforms existing industry standards in metrics such as network throughput, delivery ratio, or routing distance. Finally, we demonstrate the feasibility and flexibility of the architecture by detailing an implementation using Wireless Sensor Networks and Web Services, and describe a prototype for the real-time monitoring of goods flowing through a supply chain.
Objective:To examine the relationship between experienced mental workload and physiological response by noninvasive monitoring of physiological parameters.Background:Previous studies have examined how individual physiological measures respond to changes in mental demand and subjective reports of workload. This study explores the response of multiple physiological parameters and quantifies their added value when estimating the level of demand.Method:The study presented was conducted in laboratory conditions and required participants to perform a visual-motor task that imposed varying levels of demand. The data collected consisted of physiological measurements (heart interbeat intervals, breathing rate, pupil diameter, facial thermography), subjective ratings of workload (Instantaneous Self-Assessment Workload Scale [ISA] and NASA-Task Load Index), and the performance.Results:Facial thermography and pupil diameter were demonstrated to be good candidates for noninvasive workload measurements: For seven out of 10 participants, pupil diameter showed a strong correlation (R values between .61 and .79 at a significance value of .01) with mean ISA normalized values. Facial thermography measures added on average 47.7% to the amount of variability in task performance explained by a regression model. As with the ISA ratings, the relationship between the physiological measures and performance showed strong interparticipant differences, with some individuals demonstrating a much stronger relationship between workload and performance measures than others.Conclusion:The results presented in this paper demonstrate that physiological and pupil diameter can be used for noninvasive real-time measurement of workload.Application:The methods presented in this article, with current technological capabilities, are better suited for workplaces where the person is seated, offering the possibility of being applied to pilots and air traffic controllers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.