Paper Info
Title
Escaping the Streetlight Effect: Semantic Hypermedia Search Enhances Autonomous Behavior in the Web of Things
Abstract
The integration of systems of autonomous agents in Web of Things (WoT) environments is a promising approach to provide and distribute intelligence in world-wide pervasive systems. A central problem then is to enable autonomous agents to discover heterogeneous resources in large-scale, dynamic WoT environments. This is true in particular if an environment relies on open-standards and evolves rapidly requiring agents to adapt their behavior to achieve their goals. To this end, we developed a search engine for the WoT that allows autonomous agents to perform approximate search queries in order to find relevant resources in their environment in (weak) real time. The search engine crawls dynamic WoT environments to discover and index device metadata described with the W3C WoT Thing Description, and exposes a SPARQL endpoint that agents can use for approximate search. To demonstrate the feasibility of our approach, we implemented a prototype application for the maintenance of industrial robots in world-wide manufacturing systems. The prototype demonstrates that our semantic hypermedia search engine enhances the flexibility and agility of autonomous agents in the WoT.
Year
DOI
Venue
2019
10.1145/3365871.3365901
Proceedings of the 9th International Conference on the Internet of Things
Keywords
DocType
ISBN
Autonomous Agents, Hypermedia, Search, Semantic Web, Web of Things
Conference
978-1-4503-7207-7
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Simon Bienz100.34
Andrei Ciortea224.44
Mayer, Simon325129.78
Fabien Gandon41023113.17
Olivier Corby560387.71