Alexander Ilic

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.

Increasing Supply-Chain Visibility with Rule-Based RFID Data Analysis

RFID technology tracks the flow of physical items and goods in supply chains to help users detect inefficiencies, such as shipment delays, theft, or inventory problems. An inevitable consequence, however, is that it generates huge numbers of events. To exploit these large amounts of data, the supply chain visualizer increases supply-chain visibility by analyzing RFID data, using a mix of automated analysis techniques and human effort. The tools core concepts include rule-based analysis techniques and a map-based representation interface. With these features, it lets users visualize the supply-chain structure, together with performance metrics, and detect problematic hot spots.

The value of RFID for RTI management

Returnable transport items (RTIs) are key elements for enabling a smooth flow of goods throughout supply chains. Despite their importance, RTIs can be prone to high loss and breakage rates. Today’s RTI management processes are rather inefficient and are based on estimates about when, where and how RTIs are utilised. This limited visibility inevitably causes the involved parties to feel less responsible for the proper management of RTIs. As a consequence, inefficiencies created by a single party can result in a significant cost burden for the whole supply chain. The goal of this paper is therefore to explore the impact of increased asset visibility on the RTI management process. We describe a solution based on Radio Frequency Identification (RFID) technology and quantify its financial impact from each individual stakeholder’s perspective. Our findings suggest that RFID can provide a powerful means to counter inefficiencies in the RTI management process and improve the overall effectiveness of the RTI supply chain network.

Understanding the impact of personality traits on mobile app adoption - Insights from a large-scale field study

The sheer amount of available apps allows users to customize smartphones to match their personality and interests. As one of the first large-scale studies, the impact of personality traits on mobile app adoption was examined through an empirical study involving 2043 Android users. A mobile app was developed to assess each smartphone users personality traits based on a state-of-the-art Big Five questionnaire and to collect information about her installed apps. The contributions of this work are two-fold. First, it confirms that personality traits have significant impact on the adoption of different types of mobile apps. Second, a machine-learning model is developed to automatically determine a users personality based on her installed apps. The predictive model is implemented in a prototype app and shows a 65% higher precision than a random guess. Additionally, the model can be deployed in a non-intrusive, low privacy-concern, and highly scalable manner as part of any mobile app. Personality has a significant impact on mobile app adoption.A novel approach is proposed to study mobile app adoption on a large scale.A machine-learning model is developed to predict a smartphone users personality.The predictive model can be integrated into any mobile app.

Understanding data volume problems of RFID‐enabled supply chains

Purpose – The widespread application of radio frequency identification (RFID) tags in supply chains is said to cause enormous data volume problems that could render RFID event‐driven supply chains unmanageable. An unbiased and quantitative understanding of the characteristics and extent of these data volume problems is necessary to identify and remove adoption barriers. This paper aims to address the issues.Design/methodology/approach – The paper presents a simulation study based on a real‐world scenario that reveals quantitative characteristics of the data volumes problem in an RFID‐enabled supply chain and discusses its implications.Findings – The results suggest that data volumes will be much lower than currently assumed by practitioners. Thus, this work can be seen as a first basis for eliminating unjustified adoption concerns regarding data volumes complexity. However, it finds that the data volume problems bear still significant challenges for researchers and developers of RFID infrastructures with ...

The Dual Ownership Model: Using Organizational Relationships for Access Control in Safety Supply Chains

Counterfeits and contaminated drugs are recognized as a threat to consumer safety. To fight counterfeiting and protect consumers, public health institutions such as the US FDA demand organizations to electronically document the pedigrees of prescription drugs. As the documentation process involves joint collaborations of multiple organizations along the supply chain on electronic pedigrees for billions of individual goods, new and scalable access control models are needed. Therefore, this paper presents a novel concept, which leverages existing organizational relationships to manage access control based on physical possession. The concept is evaluated against other existing models and discussed.

Decreasing false-positive RFID tag reads by improved portal antenna setups

The problem of false-positive RFID tag reads i.e., tags that have been read unintentionally by a reader, is crucial for the actual implementation of RFID solutions in the real world. Prior research has shown that the use of the low-level reader data is suitable to approach this problem and it is the scope of this paper to evaluate the use of alternative RFID reader antenna setups to support this idea. We collected a large number of data in a productive RFID enabled distribution center, derived additional knowledge from our findings and used it to train a machine learning algorithm for the detection of such false-positive reads. It will be shown that the proposed solutions significantly improve the previously in the literature presented classification algorithms.

Dual Ownership: Access Management for Shared Item Information in RFID-enabled Supply Chains

RFID tags combined with globally unique numbering schemes such as the electronic product code (EPC) help standardizing the communication along the supply chain. Participants generate and share item information to collectively build digital lifecycle records. Yet, the challenge of efficient access management for item-level information still remains open. This paper introduces a novel concept for data access management, called dual ownership. The model grants access control to parties that can prove the physical possession of an item. RFID technology hereby tracks the transitions of physical possession to translate them to data access permissions. This paper describes the concept of dual ownership and discusses its implications

Mobile app adoption in different life stages: An empirical analysis

Abstract The analysis of individuals’ current life stages is a powerful approach for identifying und understanding patterns of human behavior. Different stages imply different preferences and consumer demands. Thus, life stages play an important role in marketing, economics, and sociology. However, such information is difficult to be obtained especially in the digital world. This work thus contributed to both theory and practice from two aspects. First, we conducted a large-scale empirical study with 1435 participants and showed that a person’s mobile app adoption pattern is strongly influenced by her current life stage. Second, we presented a data-driven, highly-scalable, and real-time approach of predicting an individual’s current life stage based on the apps she has installed on smartphone. Result showed that our predictive models were able to predict life stages with 241.0% higher precision and 148.2% higher recall than a random guess on average.

Distance-sensitive High Frequency RFID Systems

Location information about a high frequency RFID tag is currently limited to the location information associated with the position of the RFID reader. The distance of a tag from the reader remains unknown. However, more precise location information of objects provided at low cost is critical to create smart spaces. In this paper, we present a distance-sensitive RFID system that accurately resolves a tags distance from the reader. In contrast to other distance sensing systems that operate on the emission of electromagnetic waves, high frequency RFID systems make use of magnetic coupling for data transmission. The paper details the system design and implementation with discrete components, presents the distance measurement procedure, and evaluates the accuracy of the measurements.