Climate change is the biggest threat to humans in the 21st century, and with global warming already occurring, we must prepare to live in a warmer climate that will experience more frequent, intense and longer extreme heat events (Patz et al., 2005)(Costello et al., 2009). The Intergovernmental Panel on Climate Change (IPCC) states that climate change will cause severe impacts on health due to increased frequency and intensity of extreme weather events increasing occurrence of heat-related illnesses, such as heat stroke and acute cardiovascular disease (Bustinza et al., 2013)(Li et al., 2015). Despite the increasing frequency of these extreme weather events, current surveillance ecosystems are not equipped to monitor the indoor temperature in houses and apartments to provide early warnings for high-risk individuals (e.g., older adults and infants) (Davoudi et al., 2012). With IoT technology however, indoor temperature monitoring enables better projections about climate conditions, presenting an opportunity for improvement and innovation (Hughes, 2015). The UbiLab has a research partnership with ecobee, a Canadian smart thermostat company, and access to over 110,000 household temperature records from across North America. The use of this unobtrusive, commercially available monitoring system in Canadian homes would overcome barriers such as cost, and enable long periods of data collection that could save lives.
The use of ecobee devices enables the onboarding of consenting participants into a surveillance network capable of monitoring indoor temperature variations, extremely high temperatures, extremely low temperatures, and multi-day exposure in residences. Coupled with demographic information about the residents and partnering with homecare agencies and emergency services, this platform has the potential to provide mitigation services to seniors at risk and prevent deaths during heatwaves. For my thesis, I will be exploring the use of smart thermostats to monitor indoor temperatures and collect data to understand better how people perceive heat risk and cope with extreme heat. We will be deploying sensors in low-income settings as these populations are unlikely to have smart thermostats. Working with partners such as Health Canada and public health units, the goal is to improve our heat health warning systems to save lives. By leveraging everyday innovations, we can improve society and reduce health disparities, and enable real-time data-driven decision making, and informed policy development.
The research questions I will be answering are below:
- What are some of the limitations of smart-home technologies for the monitoring of indoor physical activity and sleep quality,
- How intrusive and annoying are the sensors that were used in the study,
- Can we develop a machine learning algorithm that can leverage the data from multiple smart-home sensors to accurately quantify sleep quality and indoor physical activity.
Project members:
Arlene Oetomo, PhD
Last updated: April 06, 2021