113,959 research outputs found

    Integration of Legacy Appliances into Home Energy Management Systems

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    The progressive installation of renewable energy sources requires the coordination of energy consuming devices. At consumer level, this coordination can be done by a home energy management system (HEMS). Interoperability issues need to be solved among smart appliances as well as between smart and non-smart, i.e., legacy devices. We expect current standardization efforts to soon provide technologies to design smart appliances in order to cope with the current interoperability issues. Nevertheless, common electrical devices affect energy consumption significantly and therefore deserve consideration within energy management applications. This paper discusses the integration of smart and legacy devices into a generic system architecture and, subsequently, elaborates the requirements and components which are necessary to realize such an architecture including an application of load detection for the identification of running loads and their integration into existing HEM systems. We assess the feasibility of such an approach with a case study based on a measurement campaign on real households. We show how the information of detected appliances can be extracted in order to create device profiles allowing for their integration and management within a HEMS

    Designing a Blockchain Model for the Paris Agreement’s Carbon Market Mechanism

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    This paper examines the benefits and constraints of applying blockchain technology for the Paris Agreement carbon market mechanism and develops a list of technical requirements and soft factors as selection criteria to test the feasibility of two different blockchain platforms. The carbon market mechanism, as outlined in Article 6.2 of the Paris Agreement, can accelerate climate action by enabling cooperation between national Parties. However, in the past, carbon markets were limited by several constraints. Our research investigates these constraints and translates them into selection criteria to design a blockchain platform to overcome these past limitations. The developed selection criteria and assumptions developed in this paper provide an orientation for blockchain assessments. Using the selection criteria, we examine the feasibility of two distinct blockchains, Ethereum and Hyperledger Fabric, for the specific use case of Article 6.2. These two blockchain systems represent contrary forms of design and governance; Ethereum constitutes a public and permissionless blockchain governance system, while Hyperledger Fabric represents a private and permissioned governance system. Our results show that both blockchain systems can address present carbon market constraints by enhancing market transparency, increasing process automation, and preventing double counting. The final selection and blockchain system implementation will first be possible, when the Article 6 negotiations are concluded, and governance preferences of national Parties are established. Our paper informs about the viability of different blockchain systems, offers insights into governance options, and provides a valuable framework for a concrete blockchain selection in the future.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische UniversitÀt Berli

    Emotions in context: examining pervasive affective sensing systems, applications, and analyses

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    Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

    Case study:exploring children’s password knowledge and practices

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    Children use technology from a very young age, and often have to authenticate themselves. Yet very little attention has been paid to designing authentication specifically for this particular target group. The usual practice is to deploy the ubiquitous password, and this might well be a suboptimal choice. Designing authentication for children requires acknowledgement of child-specific developmental challenges related to literacy, cognitive abilities and differing developmental stages. Understanding the current state of play is essential, to deliver insights that can inform the development of child-centred authentication mechanisms and processes. We carried out a systematic literature review of all research related to children and authentication since 2000. A distinct research gap emerged from the analysis. Thus, we designed and administered a survey to school children in the United States (US), so as to gain insights into their current password usage and behaviors. This paper reports preliminary results from a case study of 189 children (part of a much larger research effort). The findings highlight age-related differences in children’s password understanding and practices. We also discovered that children confuse concepts of safety and security. We conclude by suggesting directions for future research. This paper reports on work in progress.<br/

    Knowing Your Population: Privacy-Sensitive Mining of Massive Data

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    Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is controversial, in particular raising issues of privacy. However, our hypothesis is that privacy-sensitive uses are possible and often beneficial enough to warrant considerable research and development efforts. Our work contends that peoples behavior can yield patterns of both significant commercial, and research, value. For such purposes, methods and algorithms for mining telecommunication data to extract commonly used routes and locations, articulated through time-geographical constructs, are described in a case study within the area of transportation planning and analysis. From the outset, these were designed to balance the privacy of subscribers and the added value of mobility patterns derived from their mobile communication traffic and transactions data. Our work directly contrasts the current, commonly held notion that value can only be added to services by directly monitoring the behavior of individuals, such as in current attempts at location-based services. We position our work within relevant legal frameworks for privacy and data protection, and show that our methods comply with such requirements and also follow best-practice

    ERP implementation methodologies and frameworks: a literature review

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    Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

    Service Level Agreement-based GDPR Compliance and Security assurance in (multi)Cloud-based systems

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    Compliance with the new European General Data Protection Regulation (Regulation (EU) 2016/679) and security assurance are currently two major challenges of Cloud-based systems. GDPR compliance implies both privacy and security mechanisms definition, enforcement and control, including evidence collection. This paper presents a novel DevOps framework aimed at supporting Cloud consumers in designing, deploying and operating (multi)Cloud systems that include the necessary privacy and security controls for ensuring transparency to end-users, third parties in service provision (if any) and law enforcement authorities. The framework relies on the risk-driven specification at design time of privacy and security level objectives in the system Service Level Agreement (SLA) and in their continuous monitoring and enforcement at runtime.The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644429 and No 780351, MUSA project and ENACT project, respectively. We would also like to acknowledge all the members of the MUSA Consortium and ENACT Consortium for their valuable help
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