A Reference Model for IoT Embodied Agents Controlled by Neural Networks

Nathalia Nascimento, Paulo Alencar, Donald Cowan, Carlos Lucena

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Scopus citations

    Abstract

    Embodied agents is a term used to denote intelligent agents, which are a component of devices belonging to the Internet of Things (IoT) domain. Each agent is provided with sensors and actuators to interact with the environment, and with a 'controller' that usually contains an artificial neural network (ANN). In previous publications, we introduced three software approaches to design, implement and test IoT embodied agents. In this paper, we propose a reference model based on statecharts that offers abstractions tailored to the development of IoT applications. The model represents embodied agents that are controlled by neural networks. Our model includes the ANN training process, represented as a reconfiguration step such as changing agent features or neural net connections. Our contributions include the identification of the main characteristics of IoT embodied agents, a reference model specification based on statecharts, and an illustrative application of the model to support autonomous street lights. The proposal aims to support the design and implementation of IoT applications by providing high-level design abstractions and models, thus enabling the designer to have a uniform approach to conceiving, designing and explaining such applications.

    Original languageEnglish (US)
    Title of host publicationProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
    EditorsXintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3500-3505
    Number of pages6
    ISBN (Electronic)9781728162515
    DOIs
    StatePublished - Dec 10 2020
    Event8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States
    Duration: Dec 10 2020Dec 13 2020

    Publication series

    NameProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

    Conference

    Conference8th IEEE International Conference on Big Data, Big Data 2020
    Country/TerritoryUnited States
    CityVirtual, Atlanta
    Period12/10/2012/13/20

    All Science Journal Classification (ASJC) codes

    • Computer Networks and Communications
    • Information Systems
    • Information Systems and Management
    • Safety, Risk, Reliability and Quality

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