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IoT Beehives and Open Data to Gauge Urban Biodiversity

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Advances in Information and Communication (FICC 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1363))

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Abstract

Environmental sustainability is a key element of modern society. It has received global attention in recent years, both at scientific and administrative levels. Despite the scrupulous studies addressing this theme, many issues remain largely unresolved. A (big) data and AI approach is a promising alternative for tackling societal or environmental problems that are hard to grasp. We apply this approach to assess urban biodiversity. More specifically, the concept of intelligent beehives is introduced. This concept encapsulates and leverages biotic elements, such as harnessing bees as biomonitoring agents, with technologies like IoT instrumentation and AI. Together they comprise the data-driven services that shape the backbone of a real-time environmental dashboard. In this vision paper, our solution architecture and prototypization for such service-enabled beehives are sketched and discussed. We focus on the role of the IoT beehive network and open data for predictive modelling of biodiversity and argue how MLOps practices support a transformative process for creating awareness and maintaining or even increasing urban biodiversity.

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Notes

  1. 1.

    https://ipbes.net/global-assessment-report-biodiversity-ecosystem-services.

  2. 2.

    https://www.un.org/sustainabledevelopment/news/communications-material.

  3. 3.

    Note that pollinators directly affect 35% of the world’s food crop production [13].

  4. 4.

    This is an extended version of an earlier concept presented at SummerSoC 2020 [22].

  5. 5.

    http://melixa.eu/en/.

  6. 6.

    https://beep.nl/home-english.

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Acknowledgment

The authors thank Michiel Groenemeijer for his valuable and creative beehive design contributions and his dedicated beekeeping activities for this project.

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Authors and Affiliations

  1. Fontys University of Applied Sciences, Eindhoven, The Netherlands

    Gerard Schouten

  2. Tilburg University - JADS, Tilburg, The Netherlands

    Gerard Schouten, Mirella Sangiovanni & Willem-Jan van den Heuvel

Authors
  1. Gerard Schouten
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  2. Mirella Sangiovanni
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  3. Willem-Jan van den Heuvel
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Corresponding author

Correspondence to Gerard Schouten .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Schouten, G., Sangiovanni, M., van den Heuvel, WJ. (2021). IoT Beehives and Open Data to Gauge Urban Biodiversity. In: Arai, K. (eds) Advances in Information and Communication. FICC 2021. Advances in Intelligent Systems and Computing, vol 1363. Springer, Cham. https://doi.org/10.1007/978-3-030-73100-7_17

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