Managing non-trivial internet-of-things systems with conversational assistants: A prototype and a feasibility experiment

• Type: Article in International Scientific Journal
• Date: 2021

Authors

André Sousa Lago (Author) Other; João Pedro Dias (Author) FEUP; Hugo Sereno Ferreira (Author) FEUP

Journal

Title: Journal of Computational Science

Vol. 51

Pages: 1-12

ISSN: 1877-7503

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 8 Citations

Other information

Authenticus ID: P-00T-FGZ

DOI: 10.1016/j.jocs.2021.101324

Abstract (EN): Internet-of-Things has reshaped the way people interact with their surroundings and automatize the once manual actions. In a smart home, controlling the Internet-connected lights is as simple as speaking to a nearby conversational assistant. However, specifying interaction rules, such as making the lamp turn on at specific times or when someone enters the space is not a straightforward task. The complexity of doing such increases as the number and variety of devices increases, along with the number of household members. Thus, managing such systems becomes a problem, including finding out why something has happened. This issue lead to the birth of several low-code development solutions that allow users to define rules to their systems, at the cost of discarding the easiness and accessibility of voice interaction. In this paper we extend the previous published work on Jarvis [1], a conversational interface to manage IoT systems that attempts to address these issues by allowing users to specify time-based rules, use contextual awareness for more natural interactions, provide event management and support causality queries. A proof-of-concept is presented, detailing its architecture and natural language processing capabilities. A feasibility experiment was carried with mostly non-technical participants, providing evidence that Jarvis is intuitive enough to be used by common end-users, with participants showcasing an overall preference by conversational assistants over visual low-code solutions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12