Date: Wednesday 29 March 2017
Time: 17:00 - 18:30
Location / Room: 5A
Organisers:
Nikil Dutt, UC Irvine, US
Axel Jantsch, TU Wien, AT
Chair:
Nikil Dutt, UC Irvine, US
Co-Chair:
Amir Rahmani, TU Wien, AT
This special hot topic session addresses concepts and applications of self-awareness for engineered systems. Interest in self-awareness continues to grow with applications in diverse domains such as automotive, space, military, consumer electronics, industrial control, health care, etc. The first talk outlines the concepts of self-awareness in psychology, and its applicability in computing, as well as in the engineering of adaptive systems. The second talk reviews the role of self-awareness in autonomous driving systems and explains how system self-awareness has become an important foundation for reliable and flexible platform management of autonomous cars. The third talk presents a remote health monitoring and diagnostic system for holistic perception of a patient's situation, and demonstrates how self-awareness is leveraged through the use of wearable sensors, contextual knowledge of the patient's health situation, and automated reasoning of the patient's health situation.
| Time | Label | Presentation Title Authors |
|---|---|---|
| 17:00 | 8.6.1 | SELF-AWARE COMPUTING SYSTEMS: FROM PSYCHOLOGY TO ENGINEERING Speaker and Author: Peter Lewis, Aston University, GB Abstract At the current time, there are several fundamental changes in the way computing systems are being developed, deployed and used. They are becoming increasingly large, heterogeneous, uncertain, dynamic and decentralised. These complexities lead to behaviours during run time that are difficult to understand or predict. One vision for how to rise to this challenge is to endow computing systems with increased self-awareness, in order to enable advanced autonomous adaptive behaviour. A desire for self-awareness has arisen in a variety of areas of computer science and engineering over the last two decades, and more recently a more fundamental understanding of what self-awareness concepts might mean for the design and operation of computing systems has been developed. This draws on self-awareness theories from psychology and other related fields, and has led to a number of contributions in terms of definitions, architectures, algorithms and case studies. This paper introduces some of the main aspects of self-awareness from psychology, that have been used in developing associated notions in computing. It then describes how these concepts have been translated to the computing domain, and provides examples of how their explicit consideration can lead to systems better able to manage trade-offs between conflicting goals at run time in the context of a complex environment, while reducing the need for a priori domain modelling at design or deployment time. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 17:30 | 8.6.2 | SELF-AWARENESS IN AUTONOMOUS SYSTEMS: SELF-DRIVING CARS Speaker: Rolf Ernst, TU Braunschweig, DE Authors: Johannes Schlatow1, Mischa Möstl2, Rolf Ernst2, Marcus Nolte2, Inga Jatzkowski2, Markus Maurer2, Christian Herber3 and Andreas Herkersdorf4 1TU Braunschweig, Institute of Computer and Network Engineering, DE; 2TU Braunschweig, DE; 3Technische Universität München, DE; 4TU München, DE Download Paper (PDF; Only available from the DATE venue WiFi) |
| 18:00 | 8.6.3 | SELF-AWARENESS IN REMOTE HEALTH MONITORING SYSTEMS THROUGH WEARABLE ELECTRONICS Speaker: Axel Jantsch, TU Wien, AT Authors: Arman Anzanour1, Iman Azimi1, Maximilian Götzinger1, Amir M. Rahmani2, Nima Taherinejad3, Pasi Liljeberg1, Axel Jantsch3 and Nikil Dutt4 1University of Turku, FI; 2University of California Irvine & TU Wien, US; 3Vienna University of Technology, AT; 4UC Irvine, US Abstract In healthcare, effective monitoring of patients plays a key role in detecting health deterioration early enough. Many signs of deterioration exist as early as 24 hours prior having a serious impact on the health of a person. As hospitalization times have to be minimized, in-home or remote early warning systems can fill the gap by allowing in-home care while having the potentially problematic conditions and their signs under surveillance and control. This work presents a remote monitoring and diagnostic system that provides a holistic perspective of patients and their health conditions. We discuss how the concept of self-awareness can be used in various parts of the system such as information collection through wearable sensors, confidence assessment of the sensory data, the knowledge base of the patient's health situation, and automation of reasoning about the health situation. Our approach to self-awareness provides (i) situation awareness to consider the impact of variations such as sleeping, walking, running, and resting, (ii) system personalization by reflecting parameters such as age, body mass index, and gender, and (iii) the attention property of self-awareness to improve the energy efficiency and dependability of the system via adjusting the priorities of the sensory data collection. We evaluate the proposed method using a full system demonstration. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 18:30 | End of session | |