Vom Internet der Computer zum Internet der Dinge

Zusammenfassung: Der Beitrag diskutiert die Vision, die informationstechnischen Grundlagen und Herausforderungen sowie die Anwendungsmöglichkeiten eines ,,Internet der Dinge". Ferner wird auf informatikbezogene Aspekte wie RFID und die Realisierung von IP-Stacks und Webservern für smarte Alltagsgegenstände eingegangen. In einem Ausblick werden auch einige gesellschaftliche und politische Fragen angesprochen, die mit einem Internet der Dinge auf uns zukomme

Fine-Grained Product Class Recognition for Assisted Shopping

Assistive solutions for a better shopping experience can improve the quality of life of people, in particular also of visually impaired shoppers. We present a system that visually recognizes the fine-grained product classes of items on a shopping list, in shelves images taken with a smartphone in a grocery store. Our system consists of three components: (a) We automatically recognize useful text on product packaging, e.g., product name and brand, and build a mapping of words to product classes based on the large-scale GroceryProducts dataset. When the user populates the shopping list, we automatically infer the product class of each entered word. (b) We perform fine-grained product class recognition when the user is facing a shelf. We discover discriminative patches on product packaging to differentiate between visually similar product classes and to increase the robustness against continuous changes in product design. (c) We continuously improve the recognition accuracy through active learning. Our experiments show the robustness of the proposed method against cross-domain challenges, and the scalability to an increasing number of products with minimal re-training.Comment: Accepted at ICCV Workshop on Assistive Computer Vision and Robotics (ICCV-ACVR) 201

PowerPedia: changing energy usage with the help of a community-based smartphone application

When it comes to conserving electricity, it is crucial for users to know how much energy is consumed by individual appliances. However, the technical feedback provided by existing energy consumption feedback systems in the form of dry numbers and intangible units is not appropriate for most users. To address this shortcoming, we developed PowerPedia, a system that provides behavior-influencing feedback over and above pure consumption values. By integrating a community platform—a Wikipedia for electrical appliances—PowerPedia enables users to identify and compare the consumption of their domestic appliances with that of others. It thus helps users to better understand their electricity consumption and take effective action to save electricit

Configuration of smart environments made simple combining visual modeling with semantic metadata and reasoning

We present an approach that combines semantic metadata and reasoning with a visual modeling tool to enable the goal-driven configuration of smart environments for end users. In contrast to process-driven systems where service mashups are statically defined, this approach makes use of embedded semantic API descriptions to dynamically create mashups that fulfill the user's goal. The main advantage of the presented system is its high degree of flexibility, as service mashups can adapt to dynamic environments and are fault-tolerant with respect to individual services becoming unavailable. To support end users in expressing their goals, we integrated a visual programming tool with our system. This tool enables users to model the desired state of their smart environment graphically and thus hides the technicalities of the underlying semantics and the reasoning. Possible applications of the presented system include the configuration of smart homes to increase individual well-being, and reconfigurations of smart environments, for instance in the industrial automation or healthcare domains

A Formal Account of the Open Provenance Model

On the Web, where resources such as documents and data are published, shared, transformed, and republished, provenance is a crucial piece of metadata that would allow users to place their trust in the resources they access. The Open Provenance Model (OPM) is a community data model for provenance that is designed to facilitate the meaningful interchange of provenance information between systems. Underpinning OPM is a notion of directed graph, where nodes represent data products and processes involved in past computations, and edges represent dependencies between them; it is complemented by graphical inference rules allowing new dependencies to be derived. Until now, however, the OPM model was a purely syntactical endeavor. The present paper extends OPM graphs with an explicit distinction between precise and imprecise edges. Then a formal semantics for the thus enriched OPM graphs is proposed, by viewing OPM graphs as temporal theories on the temporal events represented in the graph. The original OPM inference rules are scrutinized in view of the semantics and found to be sound but incomplete. An extended set of graphical rules is provided and proved to be complete for inference. The paper concludes with applications of the formal semantics to inferencing in OPM graphs, operators on OPM graphs, and a formal notion of refinement among OPM graphs

SmartTrack: Efficient Predictive Race Detection

Widely used data race detectors, including the state-of-the-art FastTrack algorithm, incur performance costs that are acceptable for regular in-house testing, but miss races detectable from the analyzed execution. Predictive analyses detect more data races in an analyzed execution than FastTrack detects, but at significantly higher performance cost. This paper presents SmartTrack, an algorithm that optimizes predictive race detection analyses, including two analyses from prior work and a new analysis introduced in this paper. SmartTrack's algorithm incorporates two main optimizations: (1) epoch and ownership optimizations from prior work, applied to predictive analysis for the first time; and (2) novel conflicting critical section optimizations introduced by this paper. Our evaluation shows that SmartTrack achieves performance competitive with FastTrack-a qualitative improvement in the state of the art for data race detection.Comment: Extended arXiv version of PLDI 2020 paper (adds Appendices A-E) #228 SmartTrack: Efficient Predictive Race Detectio

A Transition Model from Web of Things to Speech of Intelligent Things in a Smart Education System

Several terms have been used to describe Internet of Things; Web of Things (WoT) is a term which can be used interchangeability and it is referred to as the capability of devices to interconnect to the World Wide Web and sharing the information and data to one another. WoT has been mentioned in the literature to improve interconnection between devices at all times. In WoT, two different modes of communication which are generally mentioned in previous studies include person-to-thing (or thing-to-person) and thing-to-thing. This paper presents an architecture for transiting from WoT to speech-enabled WoT known as Speech of Intelligent Things (SoIT). The system employs a combination of technologies such as system design, server-side scripting, speech-based system tools, and data management in developing the SoIT prototype system as a third mode of communication. This paper illustrates a scenario whereby remote monitoring and controlling of WoT devices within the university campus might be difficult to manage by only using the modes discussed in the literature. An evolution of WoT to SoIT was realized using speech technology to provide a prototype system. Technical implications involve using a telephone by connecting an object telephone number (OTN) and dial WoT objects and establish a control mechanism. The research limitation is mainly the cost of dialing an OTN number. The contribution of this paper is to favor and encourage the use of speech technology to enhance the convenience of communication between WoT devices within the school campus