• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    • Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • Improving Our Understanding of the Behavior of Bees Through Anomaly Detection Techniques

    Author(s)
    Gama, Fernando
    Arruda, Helder M
    Carvalho, Hanna V
    de Souza, Paulo
    Pessin, Gustavo
    Griffith University Author(s)
    De Souza Junior, Paulo A.
    Year published
    2017
    Metadata
    Show full item record
    Abstract
    Bees are one of the most important pollinators since they assist in plant reproduction and ensure seed and fruit production. They are important both for pollination and honey production, which benefits small and large-scale agriculturists. However, in recent years, the bee populations have declined significantly in alarming ways on a global scale. In this scenario, understanding the behavior of bees has become a matter of great concern in an attempt to find the possible causes of this situation. In this study, an anomaly detection algorithm is created for data labeling, as well as to evaluate the classification models of ...
    View more >
    Bees are one of the most important pollinators since they assist in plant reproduction and ensure seed and fruit production. They are important both for pollination and honey production, which benefits small and large-scale agriculturists. However, in recent years, the bee populations have declined significantly in alarming ways on a global scale. In this scenario, understanding the behavior of bees has become a matter of great concern in an attempt to find the possible causes of this situation. In this study, an anomaly detection algorithm is created for data labeling, as well as to evaluate the classification models of anomalous events in a time series obtained from RFID sensors installed in bee hives.
    View less >
    Conference Title
    Lecture Notes in Computer Science
    Volume
    10614
    DOI
    https://doi.org/10.1007/978-3-319-68612-7_59
    Subject
    Artificial Intelligence and Image Processing
    Science & Technology
    Computer Science, Theory & Methods
    Publication URI
    http://hdl.handle.net/10072/401049
    Collection
    • Conference outputs

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander