Life-cycle information management and acquisition for blood products

Ten of thousands patients die every year because of medical errors. Many more patients suffer permanent damage and have to be medicated for the rest of their life. In the context of a blood donation, blood production and blood transfusion process, a lack of consistent and complete trace and tracking of individual blood bags has been identified as a source of medical errors. This research aims to address this challenge to help organisations such as blood banks to track the donation, manufacture, distribution and in-use of blood products, to remove/minimise the potential medical errors. Although the major goal of this research study is to increase patient security, reduction of wastage is also part of the research aims because donated blood is a scarce resource. Nowadays, up to 20% of the blood bags are put to scrap without use and each of the blood bag costs 220 Euro to produce (i.e. from collection, production and storage until it is consumed/discarded). In Austria alone, 5.6 million Euros could be saved each year if the wastage can be removed. Besides the economic issue, donated human blood is a scarce resource and always gives a poor psychological response from the general public when preventable wastage occurs. This research study approaches the challenges through a life-cycle point of view because it sees the goal can only be achieved through ‘real-time’ life-cycle information that governs the quality and life-span of such products. As a result, a new RF based semi-active transponder (13.56 MHz, ISO 15693 compatible HF interface) with integrated data storage and temperature sensor, which is able to sustain high g - forces have been developed to provide the ‘real-time’ temperature data and other related information support. The developed life-cycle information system has been trialled at the University Clinic of Graz not only to test its effectiveness, but also used as a case study for this research study. Due to the resources constraints (e.g. time), the case study does not create sufficient data to establish any statistical significance to quantify the benefits of the proposed systems. However, all the involved persons including both the operational and professional staff at University Clinique of Graz, have agreed the proposed RFID transponders, together with its lifecycle management system provides better decision support to handle individual blood bag at any stage of its lifecycle. They believe the proposed system will improve patients’ safety and reduce the wastage of blood bags. During the trail, it happened that two blood bags ready for transfusion were detected to be below 0°C somehow during their life-cycle. A blood transfusion would have been 100% mortal to the patients. The detection of this fatal mistake did save at least the life of one human being and illustrated the importance of an objective, overarching and complete life-cycle system for blood products. Although this research is focused on blood products for blood banks and medical environments, the benefits of the system approach and methodologies could also apply to other types of sensitive and fragile goods that require life-cycle information support

4th International Symposium on Ambient Intelligence (ISAmI 2013)

Ambient Intelligence (AmI) is a recent paradigm emerging from Artificial Intelligence (AI), where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. Another main concern of AmI originates from the human computer interaction domain and focuses on offering ways to interact with systems in a more natural way by means user friendly interfaces. This field is evolving quickly as can be witnessed by the emerging natural language and gesture based types of interaction. The inclusion of computational power and communication technologies in everyday objects is growing and their embedding into our environments should be as invisible as possible. In order for AmI to be successful, human interaction with computing power and embedded systems in the surroundings should be smooth and happen without people actually noticing it. The only awareness people should have arises from AmI: more safety, comfort and wellbeing, emerging in a natural and inherent way. ISAmI is the International Symposium on Ambient Intelligence and aiming to bring together researchers from various disciplines that constitute the scientific field of Ambient Intelligence to present and discuss the latest results, new ideas, projects and lessons learned, namely in terms of software and applications, and aims to bring together researchers from various disciplines that are interested in all aspects of this area

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Sensor-based management systems based on RFID technology

Παρατηρήσεις έκδοσης: λείπουν οι σελίδες 78, 102 από το φυσικό τεκμήριο.In this diploma thesis, the RFID technology is analyzed (operating principles, readers' and tags hardware, coding, modulation, anticollision procedures, frequencies, standards, applications). Moreover, a protocol to synchronize readers working in a multi-reader multi-tag environment is proposed. The protocol is applied to the store shelf scanning application and further refined to meet the requirements of this specific application

Learning preferences for personalisation in a pervasive environment

With ever increasing accessibility to technological devices, services and applications there is also an increasing burden on the end user to manage and configure such resources. This burden will continue to increase as the vision of pervasive environments, with ubiquitous access to a plethora of resources, continues to become a reality. It is key that appropriate mechanisms to relieve the user of such burdens are developed and provided. These mechanisms include personalisation systems that can adapt resources on behalf of the user in an appropriate way based on the user's current context and goals. The key knowledge base of many personalisation systems is the set of user preferences that indicate what adaptations should be performed under which contextual situations. This thesis investigates the challenges of developing a system that can learn such preferences by monitoring user behaviour within a pervasive environment. Based on the findings of related works and experience from EU project research, several key design requirements for such a system are identified. These requirements are used to drive the design of a system that can learn accurate and up to date preferences for personalisation in a pervasive environment. A standalone prototype of the preference learning system has been developed. In addition the preference learning system has been integrated into a pervasive platform developed through an EU research project. The preference learning system is fully evaluated in terms of its machine learning performance and also its utility in a pervasive environment with real end users

A framework for how logistics service providers should handle returns as a warehouse operation for e-commerce companies

Title: A framework for how logistics service providers should handle returns as a warehouse operation for pure e-commerce companies Authors: Louise Meurling and Matilda Sturesson Supervisor: Joakim Kembro, Division of Engineering Logistics at LTH Problem description: Managing the reverse logistics process in a warehouse is a central part of the activities for companies operating in e-commerce. Companies can outsource the return handling to a Logistics Service Provider (LSP) in order to focus on their core competences. The theory of today is based on the assumption that a physical point of contact is included in the chain. Therefore, there is a need to extend the theory into the context of e-commerce. Purpose: The purpose of this thesis is to create a framework for how LSPs should handle returns in the warehouse, from the point of receiving until put back in storage, for customers in the e-commerce business. Research questions: How should a LSP handle returns in the warehouse for customers of e-commerce? What are the barriers of the return handling in a warehouse and how can LSPs overcome these? How do the different characteristics of products and customers of a LSP change the handling of returns? How can the return handling in a warehouse of a LSP contribute to greater value for the customers acting in the e-commerce business? Methodology: A flexible design methodology has been used in this thesis together with a multiple case study based on two cases at PostNord TPL´s facility in Helsingborg. Interviews, observations, and historical data have been collected and analysed in an intra case analysis and a cross-case analysis in order to answer the research questions and modify the reverse logistics framework to the context of e-commerce. Conclusions: A framework for how LSPs should handle returns in a warehouse is extended based on theory to the context of e-commerce. Several barriers of the return handling for LSPs have been identified. These are: limited sharing of forecasts, limited visibility, customer requirements, heterogenous decision making, and the changing business of e-commerce. It can be concluded that the product and customer characteristics impact the handling of returns to a large extent. To be able to contribute to greater value for the customers, the LSP should offer a fast, efficient, and less costly reverse logistics process than if they would perform it in-house. Keywords: Warehouse activities, inbound logistics, reverse logistics process, returns, return handling, e-commerce, logistics service provide

State Management for Efficient Event Pattern Detection

Event Stream Processing (ESP) Systeme überwachen kontinuierliche Datenströme, um benutzerdefinierte Queries auszuwerten. Die Herausforderung besteht darin, dass die Queryverarbeitung zustandsbehaftet ist und die Anzahl von Teilübereinstimmungen mit der Größe der verarbeiteten Events exponentiell anwächst. Die Dynamik von Streams und die Notwendigkeit, entfernte Daten zu integrieren, erschweren die Zustandsverwaltung. Erstens liefern heterogene Eventquellen Streams mit unvorhersehbaren Eingaberaten und Queryselektivitäten. Während Spitzenzeiten ist eine erschöpfende Verarbeitung unmöglich, und die Systeme müssen auf eine Best-Effort-Verarbeitung zurückgreifen. Zweitens erfordern Queries möglicherweise externe Daten, um ein bestimmtes Event für eine Query auszuwählen. Solche Abhängigkeiten sind problematisch: Das Abrufen der Daten unterbricht die Stream-Verarbeitung. Ohne eine Eventauswahl auf Grundlage externer Daten wird das Wachstum von Teilübereinstimmungen verstärkt. In dieser Dissertation stelle ich Strategien für optimiertes Zustandsmanagement von ESP Systemen vor. Zuerst ermögliche ich eine Best-Effort-Verarbeitung mittels Load Shedding. Dabei werden sowohl Eingabeeevents als auch Teilübereinstimmungen systematisch verworfen, um eine Latenzschwelle mit minimalem Qualitätsverlust zu garantieren. Zweitens integriere ich externe Daten, indem ich das Abrufen dieser von der Verwendung in der Queryverarbeitung entkoppele. Mit einem effizienten Caching-Mechanismus vermeide ich Unterbrechungen durch Übertragungslatenzen. Dazu werden externe Daten basierend auf ihrer erwarteten Verwendung vorab abgerufen und mittels Lazy Evaluation bei der Eventauswahl berücksichtigt. Dabei wird ein Kostenmodell verwendet, um zu bestimmen, wann welche externen Daten abgerufen und wie lange sie im Cache aufbewahrt werden sollen. Ich habe die Effektivität und Effizienz der vorgeschlagenen Strategien anhand von synthetischen und realen Daten ausgewertet und unter Beweis gestellt.Event stream processing systems continuously evaluate queries over event streams to detect user-specified patterns with low latency. However, the challenge is that query processing is stateful and it maintains partial matches that grow exponentially in the size of processed events. State management is complicated by the dynamicity of streams and the need to integrate remote data. First, heterogeneous event sources yield dynamic streams with unpredictable input rates, data distributions, and query selectivities. During peak times, exhaustive processing is unreasonable, and systems shall resort to best-effort processing. Second, queries may require remote data to select a specific event for a pattern. Such dependencies are problematic: Fetching the remote data interrupts the stream processing. Yet, without event selection based on remote data, the growth of partial matches is amplified. In this dissertation, I present strategies for optimised state management in event pattern detection. First, I enable best-effort processing with load shedding that discards both input events and partial matches. I carefully select the shedding elements to satisfy a latency bound while striving for a minimal loss in result quality. Second, to efficiently integrate remote data, I decouple the fetching of remote data from its use in query evaluation by a caching mechanism. To this end, I hide the transmission latency by prefetching remote data based on anticipated use and by lazy evaluation that postpones the event selection based on remote data to avoid interruptions. A cost model is used to determine when to fetch which remote data items and how long to keep them in the cache. I evaluated the above techniques with queries over synthetic and real-world data. I show that the load shedding technique significantly improves the recall of pattern detection over baseline approaches, while the technique for remote data integration significantly reduces the pattern detection latency

Modeling the Impact of Automated Materials Locating and Tracking Technology on the Construction Supply Network

Ineffective materials and equipment management continues to be a leading cause of poor performance on construction projects today. Many of the problems arise as a result of the inability to convey information pertaining to the location and status of construction material and equipment in an accurate and efficient manner. The integration of automated materials locating and tracking technologies (AMLTT) within the construction supply network presents a viable solution to this problem. The objective of this thesis is to further the understanding of the broader impact which these technologies could have on construction supply network management and the construction management process in general. This knowledge, however limited, is increasingly important as leaders in other industry sectors are beginning to report tangible benefits as a result of the integration of these technologies within their organizations’ supply networks. Using a modeling and simulation approach, the impact of AMLTT on three segments of the construction supply network, typical to most large scale and industrial construction projects, was investigated. The results indicate the potential for AMLTT to have a positive impact on resource allocation, productivity, risk mitigation, and improving the overall performance of the construction supply network in general

Digital Technologies as Enablers of Component Reuse : Value Chain Perspectives in Construction & Manufacturing

Our planet is experiencing climate emergency due to the overconsumption of natural resources and ever-increasing carbon footprint. The construction and manufacturing industries are by far the biggest contributors to this grim situation. Hence, it is of paramount importance that the current economic model in those industries shifts from conventional linear to circular. Among the different circular economy (CE) approaches, adopting the component reuse practices is more imperative; because, after reduce, reuse is considered to be the least resource and energy intensive CE principle. With regard to transformation of the construction and manufacturing industries towards component reuse, digitalization could play a major enabling role. However, how the digital technologies such as BIM, digital twin, IoT (sensors and RFIDs), and robots could facilitate the component reuse practices is still an underexplored field of study. Additionally, the studies thus far in this direction lack the integrative approach both from multi-technology and multi-stakeholder perspectives. Therefore, the objective of this research is to investigate the perspectives of value chain actors, in construction and manufacturing, on how the digital technologies can advance component reuse practices. To address the research objective, this study employs qualitative research methodology and therein, multiple case study method. For the selection of most relevant cases, purposive sampling strategy was used. As a result, ten cases were selected, out of which, six are from the construction industry and the remaining four belong to manufacturing industry. To garner the primary data from those cases, semi-structured elite interviews were carried out. Subsequently, the data analysis process proceeded from within-case analysis to cross-case analysis. Finally, the findings from construction industry were juxtaposed to the findings from manufacturing industry, in order to examine the similarities and differences in how the digital technologies can advance component reuse practices in each industry. The findings of this study suggest that both the construction and manufacturing industries are becoming more perceptive to the need circular economy transformation. They recognize that the digital technologies are de facto the cornerstones in their efforts to adopt component reuse practices. The results demonstrate that collectively the BIM and IoT in construction, similar to digital twin and IoT in manufacturing, enables several component reuse practices- namely, DfDR, predictive maintenance, logistics & inventory management, quality & lifecycle assessment, and component disassembly planning. In addition, a few digital technology-enabled reuse practices were identified, that are peculiar to each industry. Robots, for instance, were recognized for the potential to partially automate some repetitive processes in construction industry, but that was not the case in manufacturing. Nevertheless, this study indicate that, for the technologies to be optimal in their enabling role, their current technological capabilities need to be developed further in the future. This study enriches the literature stream in circular economy and digitalization both in terms research methodology and findings. By taking a broader and integrative stance and through comparative study of two industries, this study validates several previous findings and also pro-poses novel findings of its own. To the practitioners the findings will provide comprehensive in-sights that may be useful in their efforts to adopt or foster digitalization in component reuse context. Finally, this study identifies a few directions for future research that may result in promising outcomes