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Explainable Artificial Intelligence for the Smart Home: Enabling Relevant Dialogue between Users and Autonomous Systems
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Smart home technologies aim at providing users control over their house, including but not limited to temperature, light, security, energy consumption. Despite offering the possibility of lowering power consumption (and thus the energy bill), smart home systems still struggle to convince a broad public, often being regarded as intrusive or not trustworthy. Gaining sympathy from users would require a solution to provide relevant explanations without relying on distant computing (which would imply sending private data online). We therefore propose an architecture where the autonomic controller system is extended with an intelligent layer aiming at translating autonomic values into concepts and finding causality relations in order to explain the logic behind the decisions and the state of the system to the user.

Abstract [sv]

Smart-home-teknik syftar till att ge användarna bättre kontroll över sina hem till exempel med avseende på temperatur, ljus, säkerhet eller förbrukning av energi. Denna teknik har svårt att övertyga många kunder trots löften om energibesparing och komfort. Tekniken ses som påträngande. En lösning som ökar användarnas välvilja genom att ge relevanta förklaringar men utan att skicka privata data online är önskvärd. I detta examensarbete föreslår vi en arkitektur där ett intelligent lager läggs ovanpå det autonoma systemet. Det intelligenta lagret försöker dels översätta autonoma termer till begrepp som användaren förstår och dels att hitta kausala relationer som förklarar systemets tillstånd och beslut som fattas av systemet.

Place, publisher, year, edition, pages
2019. , p. 39
Series
TRITA-EECS-EX ; 2019:157
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-252705OAI: oai:DiVA.org:kth-252705DiVA, id: diva2:1320183
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2019-06-12 Created: 2019-06-04 Last updated: 2019-06-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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