Current Projects

 
 
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SheepNN

A cost-effective and revolutionary sheep facial recognition system that allows for reliable re-identification of your flock.

Currently being commercially prototyped, SheepNN uses images captured by a bespoke camera rig being fed into a machine learning model. Future potential applications for the technology include tracking animal locations to prevent rustling, monitoring animal behaviour, estimating weight, diseases, welfare, or other characteristics, or estimating parentage without the need to observe lambing or do DNA parentage testing. Facial recognition for other species, including cattle and goats are also being developed.

SheepNN is featured as a case study in the report  ‘Artificial Intelligence for Agriculture in New Zealand’ from the AI Forum New Zealand.

PastureNN

Effective pasture management is crucial to your business. PastureNN is a smart, innovative monitoring system combining video captured on the farm with deep learning to provide up-to-date, precise pasture quality information to improve grazing management and performance. 

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Soil health optimisation

Healthy soils support agricultural, horticultural and forest productivity. Working with Agriganics, a company providing a range of services to help cropping, dairy, sheep and beef and horticultural clients farm more sustainably, Iris Data Science is developing an AI system to optimise soil health and produce soil treatment recommendations according to budget and target yield, and predict future soil test results.

Yield prediction

For T&G Global, Iris Data Science is developing machine learning models to predict yields and other characteristics such as quality and size for orchards and glasshouse products, using sensors, computer vision and other information along the supply chain.

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Data and AI partners

As industry leaders, Iris Data Science is a data science partner for AsureQuality, working on projects relating to disease detection using computer vision and deep learning.

Iris Data Science is also part of several data science and statistics related supplier panels for both central and local government.

 Who we work with

 
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