Increasing the Intelligence of low-power Sensors with Autonomous Agents
Type
conference paper
Date Issued
2022
Author(s)
William, Jannik
;
Muller dos Santos, Matuzalém
;
de Brito, Maiquel
;
Hübner, Jomi Fred
;
;
Abstract (De)
Low-power sensors are becoming ever more powerful, increasing both their energy efficiency as well as their processing capabilities. Much work in recent years has focused on optimizing machine learning models to low-power systems, typically to locally process sensor data. Significantly less attention has been paid to other artificial intelligence fields such as knowledge representation and automated reasoning, which may contribute to building autonomous devices. In this work, we present a low-power sensor node with an autonomous belief-desire-intention agent. This kind of agent simplifies the implementation of both proactive and reactive behaviors, promoting autonomy in our target applications. It does so by locally perceiving and reasoning, and then wirelessly broadcasting an intention, which can be forwarded to an actuator. The capabilities of the autonomous agent are demonstrated with a light-control application. Experiments demonstrate the feasibility of running intelligent agents in low-power platforms with little overhead.
Language
English
HSG Classification
contribution to scientific community
Event Title
Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things (AIChallengeIoT)
Event Location
Boston, United States
Event Date
6 November 2022
Subject(s)
Division(s)
Eprints ID
268007
File(s)![Thumbnail Image]()
open.access
Name
Increasing-the-Intelligence-of-low-power-Sensors-with-Autonomous-Agents-AIChallengeIoT-2022.pdf
Size
2.06 MB
Format
Adobe PDF
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