Thorsten Staake

Extending the EPC network: the potential of RFID in anti-counterfeiting

The International Chamber of Commerce estimates that seven percent of the world trade is in counterfeit goods, with the counterfeit market being worth 500 billion USD in 2004. Many companies already use overt anti-counterfeiting measures like holograms to confine counterfeiting and product piracy. However, current techniques are not suited for automated tests of product authenticity as required in warehouses, or do not provide the required level of security. In this context, Radio Frequency Identification (RFID) is a promising approach, providing an extensible, flexible and secure measure against counterfeiting. Unique product identification numbers together with an infrastructure to seamlessly share RFID-related data over the Internet are a basis of efficient Track & Trace applications. An emerging infrastructure is the EPC Network, which can be used to provide pedigree information of products and makes plausibility checks possible. In this paper, we propose a solution for products requiring authentication mechanisms that go beyond track & trace. Therefore, the evolving EPC Network should comprehend the functionality to handle tags which support strong cryptography. We suggest extending the upcoming EPC Network infrastructure with an EPC Product Authentication Service. Moreover, the development of cost-effective, dedicated authentication devices as well as the belonging standardization is motivated.

The Emergence of Counterfeit Trade: A Literature Review

Purpose – Trade in counterfeit goods is perceived as a substantial threat to various industries. No longer is the emergence of imitation products confined to branded luxury goods and final markets. Counterfeit articles are increasingly finding their way into other sectors, including the fast‐moving consumer goods, pharmaceutical, and automotive industries – with, in part, severe negative consequences for consumers, licit manufacturers, and brand owners alike. This paper seeks to shed light on the economic principles of counterfeit trade and the underlying illicit supply chains.Design/methodology/approach – An extensive literature review was conducted that comprised contributions from different strands of management research.Findings – Though governments as well as management have clearly identified the problem, very little is known – both in practice and theory – about the mechanisms and structure of the illicit market, the tactics of counterfeit producers, consumer behavior with respect to imitation prod...

From Identification to Authentication – A Review of RFID Product Authentication Techniques

Authentication has an important role in many RFID applications for providing security and privacy. In this paper we focus on investigating how RFID can be used in product authentication in supply chain applications and a review of existing approaches is provided. The different categories of RFID product authentication approaches are analyzed within the context of anticounterfeiting and fields where future research is needed are identified.

Occupancy Detection from Electricity Consumption Data

Detecting when a household is occupied by its residents is fundamental to enable a number of home automation applications. Current systems for occupancy detection usually require the installation of dedicated sensors, like passive infrared sensors, magnetic reed switches, or cameras. In this paper, we investigate the suitability of digital electricity meters -- which are already available in millions of households worldwide -- to be used as occupancy sensors. To this end, we have collected fine-grained electricity consumption data along with ground-truth occupancy information for 5 households during a period of about 8 months. Our results show that using common classification methods it is possible to achieve occupancy detection accuracies of more than 80%.

Leveraging smart meter data to recognize home appliances

The worldwide adoption of smart meters that measure and communicate residential electricity consumption gives rise to the development of new energy efficiency services. Several particularly promising applications involve the disaggregation of individual appliances within a particular household in terms of their energy demand. In this paper we present an infrastructure and a set of algorithms that make use of smart meters together with smartphones to realize new energy efficiency services (such as itemized electricity bills or targeted energy saving advice). The smartphones, together with a novel filtering approach, much simplify the training process for appliances signature recognition. We also report on the performance of our system that was tested with 8 simultaneous devices, achieving recognition rates of 87%.

Handy feedback: connecting smart meters with mobile phones

Reducing their energy consumption has become an important objective for many people. Consumption transparency and timely feedback are essential to support those who want to adjust their behavior in order to conserve energy. In this work, we propose an interactive system that provides instantaneous feedback concerning the energy usage on household and device level. For that, we used and extended the capabilities of a smart electricity meter, built a web-based API to enable interoperability with other applications, and developed a mobile phone interface that allows users to monitor, control, and measure the consumption of single appliances. Our system illustrates a way how usage barriers can be lowered and how high user involvement can be created. By providing users the electricity feedback needed -- in real-time and on device level -- the system allows for identifying the biggest energy guzzlers and helps users decrease their energy consumption.

Motivating energy-efficient behavior with Green Is: an investigation of goal setting and the role of defaults

This study investigates the role of information systems in stimulating energy-efficient behavior in private households. We present the example of Velix, a web portal designed to motivate customers of a utility company to reduce their electricity consumption. In particular, we consider the effectiveness of goal setting functionality and defaults in influencing energy conservation behavior. For this purpose, we use the web portal as a test of the theoretical propositions underlying its design. Based on data collected from a field experiment with 1,791 electricity consumers, we test hypotheses regarding the structural relations between defaults and goals, the impact of defaults and goals on consumption behavior, and the moderating role of feedback on goal choice. Our results confirm the positive impact of goal setting on energy conservation. We show that default goals lead to statistically significant savings by affecting goal choice. However, if the default goals are set too low or too high with respect to a self-set goal, the defaults will detrimentally affect behavior. We also show that feedback on goal attainment moderates the effect of default goals on goal choice. The results extend the knowledge on goal setting and defaults and have implications for the design of effective energy feedback systems. The studys approach, which combines hypothesis-driven work and design-oriented IS research, could serve as a blueprint for further research endeavors of this kind, particularly with regard to feedback systems based on future smart metering infrastructures.

Using Sensor Information to Reduce the Carbon Footprint of Perishable Goods

Sensors enhance the control of perishable goods. New applications not only help to increase profits but also to reduce greenhouse gas emissions. An abatement cost analysis examines the trade-offs between profit maximization and emission minimization.

The ECO data set and the performance of non-intrusive load monitoring algorithms

Non-intrusive load monitoring (NILM) is a popular approach to estimate appliance-level electricity consumption from aggregate consumption data of households. Assessing the suitability of NILM algorithms to be used in real scenarios is however still cumbersome, mainly because there exists no standardized evaluation procedure for NILM algorithms and the availability of comprehensive electricity consumption data sets on which to run such a procedure is still limited. This paper contributes to the solution of this problem by: (1) outlining the key dimensions of the design space of NILM algorithms; (2) presenting a novel, comprehensive data set to evaluate the performance of NILM algorithms; (3) describing the design and implementation of a framework that significantly eases the evaluation of NILM algorithms using different data sets and parameter configurations; (4) demonstrating the use of the presented framework and data set through an extensive performance evaluation of four selected NILM algorithms. Both the presented data set and the evaluation framework are made publicly available.

The rise of the “next‐generation bar code”: an international RFID adoption study

Purpose – The present study is concerned with the determinants of RFID adoption among a group of early standards adopters. Despite the extensive discussion of the technological characteristics and expected benefits of RFID in the literature, only little is known about the drivers and barriers of RFID implementations in practice. This holds particularly for the later stages of the adoption process after an initial decision in favor of the technology was made. This paper aims to fill this gap by an analysis of a set of factors on the adoption of RFID, which have been shown to be relevant for the adoption of other forms of IT, such as ERP systems and EDI.Design/methodology/approach – Based on a review of prior works, this paper constructs and empirically tests a structural model including factors related to the technology, the organization, and its environment.Findings – The results suggest that top management support, perceived technology costs, and forces within the supply chain exert a significant influen...