The Kaitiaki Intelligence Platform: conceptual foundations for an indigenous environmental sensing network

Māori agribusiness collectives (MACs) and iwi (tribal entities) in Aotearoa New Zealand (AoNZ) are increasingly focused on enhancing their environmental intelligence capabilities. With advancements in environmental sensing technologies, artificial intelligence (AI), and data warehousing, it has become feasible for MACs and iwi to establish their own environmental sensor networks (ESNs). In response to this interest, the Kaitiaki Intelligence Platform project was launched to design an Indigenous ESN. This paper examines the types of environmental data that MAC and iwi partners aim to capture with an ESN, as well as their preferences for data structure, querying, and communication. The findings indicate that these partners seek to collect a wide range of biophysical data using both remote and in-situ sensing technologies, combined with Place-based intelligence informed by mātauranga (Māori knowledge/knowledge system). They prefer to structure data using Māori environmental ontologies and apply mātauranga to train AI systems that can identify environmental health indicators and model the balance between human and non-human environmental persons. Data communication is favoured through relational kin-centric metaphors, reflecting a culturally sensitive approach to environmental monitoring. Furthermore, the need for layered data security is emphasised to uphold Indigenous data sovereignty principles.

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Publication Details

Journal
Journal of the Royal Society of New Zealand
Published
2025-03-05
DOI
https://doi.org/10.1080/03036758.2025.2470423
Citations
1
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
6.72

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article

The Kaitiaki Intelligence Platform: conceptual foundations for an indigenous environmental sensing network

John D. Reid, Desna Whaanga-Schollum, Matthew Rout, Corey Ruha et al.
1 citations
Journal of the Royal Society of New Zealand
Geographic Information Systems Studies
6.72
article

The Kaitiaki Intelligence Platform: conceptual foundations for an indigenous environmental sensing network

John D. Reid, Desna Whaanga-Schollum, Matthew Rout, Corey Ruha, Jan Hania
article en
1 citations

Abstract

Māori agribusiness collectives (MACs) and iwi (tribal entities) in Aotearoa New Zealand (AoNZ) are increasingly focused on enhancing their environmental intelligence capabilities. With advancements in environmental sensing technologies, artificial intelligence (AI), and data warehousing, it has become feasible for MACs and iwi to establish their own environmental sensor networks (ESNs). In response to this interest, the Kaitiaki Intelligence Platform project was launched to design an Indigenous ESN. This paper examines the types of environmental data that MAC and iwi partners aim to capture with an ESN, as well as their preferences for data structure, querying, and communication. The findings indicate that these partners seek to collect a wide range of biophysical data using both remote and in-situ sensing technologies, combined with Place-based intelligence informed by mātauranga (Māori knowledge/knowledge system). They prefer to structure data using Māori environmental ontologies and apply mātauranga to train AI systems that can identify environmental health indicators and model the balance between human and non-human environmental persons. Data communication is favoured through relational kin-centric metaphors, reflecting a culturally sensitive approach to environmental monitoring. Furthermore, the need for layered data security is emphasised to uphold Indigenous data sovereignty principles.

Journal of the Royal Society of New ZealandVol. 55(6)
University of Canterbury (NZ), Rotorua Hospital (NZ), Tata Trusts (IN), Furukawa Electric (United Kingdom) (GB)
Maa- ja Vesitekniikan Tuki Ry
Life in Land
Openalex Percentile: Top 6%
Geographic Information Systems Studies
6.72
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The Kaitiaki Intelligence Platform: conceptual foundations for an indigenous environmental sensing network — John D. Reid, Desna Whaanga-Schollum, et al. · Journal of the Royal Society of New Zealand (2025) | TGRS Research Map | TGRS