SENSITIVE HOMES: REMOTE SENSING AND MONITORING INTEGRAL TO HOMES A Pilot Study on First Nation Homes on an Urban Reserve Motivation Aboriginal families are significantly more likely to live in poor housing conditions than the general population. In Canada, most of these houses are often located in colder regions, which challenge the construction, the indoor air quality and the energy consumption Poor housing is related to poor child health outcomes Causes: Deficient Construction, Lack of Maintenance, Cold Climate, Overcrowding, Lifestyle Problem: No Performance Data is available in literature Research Questions How do construction, mechanical equipment, climate, & occupant related factors combined affect the quality of abo- riginal homes? Answer: A judicious application of Building Science principles & use of technologies. However, unique constraints, construction & service life conditions & uncertainties increase complexity How to identify & measure these unique conditions & uncertainties? How to devise solutions to the aboriginal housing quality problems that incorporate these unique conditions & un- certainties? Research Hypothesis Aboriginal homes need to be made more resilient & responsive to unique constraints, construction & service life con- ditions, & uncertainties There is an urgent need for actual data to understand the factors affecting the performance of these houses Solution should be systems-based. It should consider the construction, the mechanical equipment, climate and the occupants Vision: a remote health monitoring system integral to homes acting as early warning to detect problems before they become more serious and sometimes irreversible Acknowledgements: This research could not have been completed without the continuous guidance of Dr. Rodrigo Mora at British Columbia Institute of Technology The funding for this research project has been provided by British Columbia Institute of Technology and BC Homeowner Protection Office (HPO) This project was conducted in collaboration with SMT Research. Expertise and contribution from Gamal Mustapha and Jason Teetaert is highly appreciated. A special thank you to Buddy Joseph and Ron Nahanee from Squamish Nation Housing and Capital Projects and to the homeowners at Squamish nation community for giving access to their homes A very special thank you to Allan Dobie from CMHC for the guidance at the initial stages of this project Conclusion Important Knowledge gained from the pilot study Sensing System gives valuable feedback However, remote sensing technologies are still evolving Problems faced: cost, reliability, durability, autonomy, communication By Loveleen Atwal, M.A.Sc. Candidate Dr. Rodrigo Mora, Supervisor Building Science Graduate Program Research Methodology Objectives Short Term—Pilot Study - Monitor a group of urban aboriginal homes to obtain preliminary durability, indoor air quality and energy performance data - Use this data to propose a cost-effective solution to optimize the quality & resiliency of these homes Long Term - Study remote communities in the far north and investigate construction systems and Technologies that are resilient and responsive to the unique conditions Hourly Moisture Content on Various Elevations Future Work Study a larger group of houses, more representative of remote, not urban, communities Work with manufacturers to test alternative heating and ventilation technologies Work with researchers to develop intelligent sensing systems & control algorithms Data Acquisition & Sensor Layout Monitoring System Installed SMT Research Monitoring System Data Analysis: Indoor Air Quality 5 10 15 20 25 30 35 40 1/1/13 2/20/13 4/11/13 5/31/13 7/20/13 Moisture Content (%) Date North Bath North kitchen West Kitchen North Bath North Dining Room North Dining Room -50 -30 -10 10 30 50 70 90 10 20 30 40 50 60 70 80 90 100 110 10/11/2012 11/30/2012 1/19/2013 3/10/2013 4/29/2013 6/18/2013 8/7/2013 Temp(◦C) and MC (%) RH (%) Date RH RH_Temp MC Hourly temperature, Relative Humidity and Moisture Content in the Attic Hourly temperature and Relative Humidity in the crawlspace Data Analysis: Durability 0 10 20 30 40 50 60 70 80 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2/28/2013 3/20/2013 4/9/2013 4/29/2013 5/19/2013 6/8/2013 6/28/2013 7/18/2013 8/7/2013 8/27/2013 MC (%) and Temp ( ◦C) CO2 concentration (ppm) Date CO2 (ppm) temp( ͦC) RH (%) Hourly temperature, Relative Humidity and CO2 level in Master bedroom Data Analysis: Energy 0 2 4 6 8 10 12 14 Sep Oct Nov Dec Jan Feb Mar Energy Consumption (GJ) Actual Energy Consumption(GJ) HOT2000 Simulated Energy Consumption(GJ) Comparison of Simulated Vs. actual energy consumption 0 5 10 15 20 25 30 Base Model Continuous Exhaust Continuous Supply HRV 21.9 21.6 23.1 20.6 25 24 29 16 Energy Consumption MWh Energy Consumption MWh Ventilation Losses (%) Comparison of Alternative Ventilation Systems Heating (46%) Cooling (0%) Hot Water (25%) Lights (4%) Other (4%) Appliances (17%) Exterior (5%) Ceiling (4%) Walls (21%) Floors (2%) Windows (21%) Doors (6%) Basement (24%) Ventilation (25%) Components of Annual Energy Consumption Components of Annual Heat Loss Conceptual Architecture: A Health Monitoring System Integral to Homes Main Features: Infer performance knowledge from monitoring data Minimize the need for numerous sensors & data acquisition through monitoring intelligence Statistical algorithms coupled with build- ing science knowledge & principles The algorithms are calibrated by memo- rizing characteristics of time-series gen- erated by sensor data during a learning phase where the building is assumed to behave normally This phase subsequently helps identify anomalous behaviour Lessons Learned From the Pilot Study Envelop Moisture Warning: Some walls particularly north walls are not drying out as expected. Warning: Attics are extremely wet during winter. However, they dried out in summer, but seem to be getting wet again as fall begins Crawlspaces show stable RH/T. Indoor Air Quality Forced air heating system is distributing air to the rooms uniformly when operational. CO2 levels are within limits but occasionally jumps towards higher values (>1400 ppm) due to increased occupancy. RH/T data indicates there is no risk of microbial contamination within the living space. The data analysis combined with calibrated multi-zone CONTAM airflow modeling pointed towards potential indoor air quality problems due to insufficient ventilation rates and possible risks of airborne contamination from the building enclosure Warning: In the long term, mould spores from walls and attic may migrate indoors. To minimize the risk, a balanced ventilation system is desirable Energy Heating and ventilation drive the energy consumption. Warning: Occupants are opening windows in winter and are unaware of the energy penalty Conclusions From the Pilot Study Important knowledge can be gained from a well planned and deployed sensing system integral to homes. This knowledge can be used to provide feedback to occupants on durability, indoor air quality and energy In residential buildings, occupants have more impact on the indoor environment, durability and energy than in commercial buildings Occupant behaviour is critical for the design of any resilient residential indoor environmental system A residential monitoring system has potential to act as an early warning system to detect problems before they become irreversible. Outcomes Short Term Outcomes Recommendations to improve existing homes with simple and affordable solutions Increase air tightness Simulations predicted 8% reduction in energy consumption Recommendations to improve construction, and heating and ventilation systems in future homes based on HOUSE AS A SYSTEM concept Dedicated controlled supply ventilation system (Central Integrated Fan Supply Ventilation system ) Increased insulation in the attic Feedback to homeowners and builders: Energy and IAQ Long Term Outcomes Collaborations with the industry to optimize heating and ventilation systems for improved energy efficiency & IAQ Advanced automated control systems for improved ventilation Permanent real-time home quality monitoring/response platform Partnership with First Nation homes Comparison of energy consumed in existing vs. improved building air-tightness 10 20 30 40 50 60 70 15 20 25 30 16/10/2012 05/12/2012 24/01/2013 15/03/2013 04/05/2013 Temperature ( ◦C) hourly Temp hourly RH Date RH (%)