A multi-agent architecture for quantified fruits: Design and experience

Jean Pierre Briot, Nathalia Moraes Do Nascimento, Carlos José Pereira De Lucena

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

    7 Scopus citations

    Abstract

    The concept of Quantified Self is about connected objects self-monitoring their human owner (e.g., a watch measuring heart rate, etc.). A natural transposition is in self-monitoring arbitrary things, therefore named Quantified Things. In this paper, we present the case of self-monitoring agricultural products. We discuss the rationales for the design of a Quantified Fruit multi-agent architecture for self-monitoring and self-prediction of the maturation of fruits. The architecture includes 6 different types of agents, the 2 more specific ones being respectively, the self-controller equipped with various sensors and the self-prediction module. Our current implementation uses an Arduino microcontroller board with 5 sensors (measuring respectively: temperature, light, humidity, hydrogen and methane). The prediction module uses a neural network. We have implemented the architecture and have conducted various experiments, storing bananas in diverse settings: room, refrigerator, in a box, with other fruits, etc. The paper discusses the architecture, its current implementation, experiments and current results. Future issues (scalability, collaborative prediction, etc.) are also addressed.

    Original languageEnglish (US)
    Title of host publicationProceedings - SEKE 2016
    Subtitle of host publication28th International Conference on Software Engineering and Knowledge Engineering
    PublisherKnowledge Systems Institute Graduate School
    Pages369-374
    Number of pages6
    ISBN (Electronic)189170639X, 9781891706394
    DOIs
    StatePublished - 2016
    Event28th International Conference on Software Engineering and Knowledge Engineering, SEKE 2016 - Redwood City, United States
    Duration: Jul 1 2016Jul 3 2016

    Publication series

    NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
    Volume2016-January
    ISSN (Print)2325-9000
    ISSN (Electronic)2325-9086

    Conference

    Conference28th International Conference on Software Engineering and Knowledge Engineering, SEKE 2016
    Country/TerritoryUnited States
    CityRedwood City
    Period7/1/167/3/16

    All Science Journal Classification (ASJC) codes

    • Software

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