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.
Authors
- John D. Reid (ORCID: https://orcid.org/0000-0003-2657-593X)
- Desna Whaanga-Schollum (ORCID: https://orcid.org/0000-0002-0772-0081)
- Matthew Rout (ORCID: https://orcid.org/0000-0002-9969-3884)
- Corey Ruha
- Jan Hania
Institutions
- University of Canterbury (NZ)
- Rotorua Hospital (NZ)
- Tata Trusts (IN)
- Furukawa Electric (United Kingdom) (GB)
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
Funders
- Maa- ja Vesitekniikan Tuki Ry