This research will guide policy formation on improved insight into healthcare management based on accurate, relevant, high quality evidence.

The project will develop prediction algorithms for the early indication of Chronic Obstructive Pulmonary Disease (COPD) 'flare ups' using the data collected from inhaler devices. The outcomes will create models for rapid intervention through new patient care systems such as tele-health.

The development of new spatio-temporal models that combine real-time environmental data and patient health data will also be an outcome of this research.

Research Problem

Chronic Obstructive Pulmonary Disease (COPD) is a significant healthcare issue in New Zealand causing the highest hospitalisation rates in the OECD.

This project seeks to demonstrate the cross-sector benefits arising from the inter-linking of seemingly disparate or previously unlinked datasets and demonstrate how the Internet of Things is transforming healthcare.

In this project, data are geospatially tagged environmental measurements and include particulate (PM10), ambient temperature and humidity, patient data relating to time and usage of medication (obtained from inhaler devices treating COPD), and other health information such as emergency medical care access (phone advice, ambulance usage, and hospital admission).

The introduction of smart health technology to objectively measure and monitor health outcomes of COPD patients using citizen science approaches by using location enabled inhalers to determine high risk locations is novel and will form the foundation of the work covered by this project.


This project works with a number of partners and participants. These include: University of Canterbury, LINZ, WA Dept of Health, FPX, Canterbury District Health Board and Sensing City.


Malcolm CampbellDr Malcolm Campbell
Project Leader