| Inhalt: |
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| The Spirit of Context Aware Computing: |
Historical Background, Pioneering and Influential Work, Application Cases, Current Research Trends, Outlook |
| Sensors: |
Overview of available sensors especially suited for the use in context recognition Architectures. (e.g., inertial measurement units for wearable activity recognition; Environmental Sensors, Biosignal, Smartphone as a sensing Platform, etc.). Sensor Node Design & Communication (Bluetooth, ZigBee, etc.) |
| Context Aware System Design Principles I: |
Introducing the Activity and Context recognition chain to transform raw sensor data towards semantic information. |
| Context Aware System Design Principles II: |
Detailed walkthrough and methodological explanation of the necessary steps in the Activity and Context recognition chain. |
| Context Aware System Design Principles III: |
Combination of learned methodologies towards a realtime, activity and context recognition architecture. Identification of specific shortcommings of bottom-up vs. top-down architectures and their possible solution. |
| Identification, Presence & Tracking: |
Identifying Human & Things; Technologies for Identification (RFID, NFC), Positioning, Orientation, Smart Dust, Surfacewave Transponder, Visual Codes (QR), Artificial Noses, Selected Application Cases (e.g., Driver Identity-/Activity Recognition) |
| Social Aware Systems & Patterns: |
Social Computing in general, Algorithms based on graph theory for community detection, |
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SmartPhone as a Sensing Platform on multiple scale and for Crowd Context Detection |
| Looking into the future: |
Introduction into Time Series Prediction, Multiplicative Time Series Model, ARMA, ARIMA, Context Prediction based on State Space Models (HMM) |
| Security Matters?: |
Security and Privacy Definitions, Solove’s Privacy Taxanomy, Legal Issues, Fair information principles, UbiComp Implications, Shamir Tags, Critical Examples of RFID and Smart Devices. |
| Wearable Computing: |
Off the shelf technology review and application scenarios discussion (Glasses, SmartWatches, FitnessTrackers). |
| Energy Efficient Design Methodologies: |
Design specifics to ensure low power consumption (in terms of soft- and hardware techniques) resulting in long (and/or optimized ) |
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| Inhaltliche Voraussetzungen (erwartete Kenntnisse): |
keine |
| Empfohlene Voraussetzungen (erwartete Kenntnisse): |
Systementwicklungsprojekt (SEP) oder MES Praktikum, Programmierung in Java oder Programmierung 1 und Programmierung 2, Einführung in die Kontexterkennung |
| Ziel (erwartete Lernergebnisse und erworbene Kompetenzen): |
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| Kenntnisse: |
Students know the basic design principles, representative and importent projects in the area oft the course, and evaluation criteria’s for Context Recognition Architectures. Students know how recognition methodologies are implemented in real time systems by applying state of the art machine learning and pattern classification methodologies. Students know the fundamental theoretic and practical problems when designing context recognition architectures. |
| Fähigkeiten: |
Students can use their theoretical knowledge about the single steps of the so called “Activity Recognition Chain” ( i.e. sensor selection, sensor sampling, segmentation, feature extraction, classification, fusion, and symbolic processing/reasoning) to apply, discuss, and implement it. |
| Kompetenzen: |
Students learn theoretical and practical competencies (i) in the conception, (ii) in the design, (iii) in the implementation and (iv) in the evaluation of Context Recognition Architectures. During the practical tasks, special focus is put on the reusability of the developed software components to make them easily (re-)usable in future application scenarios. |
| Unterrichts-/Lehrsprachen: |
Englisch |
| Lernorganisation: |
Präsentation mit Projektor, Gruppenarbeit, Wiki |
| Abhaltungstermine: |
siehe StudIP |
| Teilnahmekriterien & Anmeldung: |
Bitte beachten Sie die Ankündungen zur Prüfungsanmeldung. Diese werden i.d.R. 4-6 Wochen nach Semesterbeginn veröffentlich. Bei Fragen zu allen Themen um die Prüfungsanmeldung wenden Sie sich bitte ausschließlich an das Studiensekretariat. |
