| Indoor Localization: A Cost-Effectiveness vs. Accuracy StudyRecognizing the occupants' movement and locations within a home is a basic functionality, underlying a variety of smart-home services, including energy management, ambient-environment control, and assistive-living services for seniors and people with disabilities. The outdoor-localization variant of the problem is effectively addressed with the use of GPS; however, GPS does not work well inside buildings, which makes the indoor-positioning problem a very active research topic. In this paper, we report on a study of the indoor-localization problem, relying on easy-to-deploy, inexpensive, BLE-enabled stickers and beacons and WiFi access points.6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2017-06-15 | |
| Ambient and wearable sensors for indoor activity recognition (Poster presentation)Diaz, D., Mohebbi, P., Yee, N., Daum, C., Liu, L., Nikoalidis, I., & Stroulia, E. (2017). Ambient and wearable sensors for indoor activity recognition. Poster presented at AGE-WELL’s 3rd Annual Conference, October 17-19, 2017, Winnipeg, MB6.2 COG-ASSESS University of Waterloo, University of Alberta | Scientific Excellence - Advancing Knowledge | 2017-10-18 | |
| fAARS: a platform for location-aware trans-reality games University of Alberta | Scientific Excellence - Advancing Knowledge | 2012-01-01 | |
| On coordination tools in the PicOS tuples system University of Alberta | Scientific Excellence - Advancing Knowledge | 2011-01-01 | |
| The smart condo: integrating sensor networks and virtual worlds University of Alberta | Scientific Excellence - Advancing Knowledge | 2011-01-01 | |
| PicOS tuples: easing event based programming in tiny pervasive systems University of Alberta | Scientific Excellence - Advancing Knowledge | 2010-01-01 | |
| Software engineering for health education and care delivery systems: The Smart Condo project University of Alberta | Scientific Excellence - Advancing Knowledge | 2009-01-01 | |
| Smart homes and home health monitoring technologies for older adults: a systematic literature review6.1 MEN-ASSESS, 6.2 COG-ASSESS University of Alberta | Scientific Excellence - Leadership | 2015-10-23 | |
| Smart homes and home health monitoring technologies for older adults: A systematic reviewBACKGROUND: Around the world, populations are aging and there is a growing concern about ways that older adults can maintain their health and well-being while living in their homes. OBJECTIVES: The aim of this paper was to conduct a systematic literature review to determine: (1) the levels of technology readiness among older adults and, (2) evidence for smart homes and home-based health-monitoring technologies that support aging in place for older adults who have complex needs. RESULTS: We identified and analyzed 48 of 1863 relevant papers. Our analyses found that: (1) technology-readiness level for smart homes and home health monitoring technologies is low; (2) the highest level of evidence is 1b (i.e., one randomized controlled trial with a PEDro score >/=6); smart homes and home health monitoring technologies are used to monitor activities of daily living, cognitive decline and mental health, and heart conditions in older adults with complex needs; (3) there is no evidence that smart homes and home health monitoring technologies help address disability prediction and health-related quality of life, or fall prevention; and (4) there is conflicting evidence that smart homes and home health monitoring technologies help address chronic obstructive pulmonary disease. CONCLUSIONS: The level of technology readiness for smart homes and home health monitoring technologies is still low. The highest level of evidence found was in a study that supported home health technologies for use in monitoring activities of daily living, cognitive decline, mental health, and heart conditions in older adults with complex needs.6.1 MEN-ASSESS, 6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2016-01-13 | |
| SmartCondo: A Smart Assisted Living Lab6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2015-10-23 | |
| Sensor placement for indoor multi-occupant tracking6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2015-07-08 | |
| Multi-Occupant Movement Tracking in Smart Home Environments6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2015-01-01 | |
| SmartCondo Viewer (Technology demonstration)Technology demonstration at the 2017 AGE-WELL conference in Winnipeg, Manitoba.6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2017-10-17 | |
| Meeting with international collaborators in Hong KongStroulia, Liu, and Nikolaidis are meeting with their collaborators on a project funded by the Worldwide Universities Network in Hong Kong December 18 - 20, 2017. Collaborators include Gangmin Ning (Zheijiang University), Raymond Tong (The Chinese University of Hong Kong), and Arthur Mak (The Chinese University of Hong Kong). Activities will include: site visits to labs, research centres, and centres that serve older adults; seminars with faculty and graduate students; research presentations. 6.1 MEN-ASSESS, 6.2 COG-ASSESS University of Alberta, Zhejiang University | Networking and Partnerships | 2017-12-18 | |
| Sensor Design, Placement, and Data Fusion in the SmartCondoWe discuss the design and implementation of the SmartCondo sensor sub-system. We review the accumulated experience of integrating a system of heterogeneous sensors and protocols to provide essential services to an indoor localization and activity recognition system. Early design constraints included the need for passive non-intrusive monitoring. This led to a coverage-oriented deployment methodology and corresponding optimization problems. We will comment on the challenges that real deployments brought, beyond what was anticipated during the design phase. We discuss how the subsequent integration of multiple sensing modalities and the "black box" interaction with off-the-shelf systems, such as Estimotes, led to a particular sensor fusion methodology. It also demonstrated that the synchronization across heterogeneous sensor systems is a crucial factor to accuracy. Finally, we will comment on the potential of integrating sensors in the building construction process, rather than installing them as retrofits, and what kinds of opportunities for energy harvesting exist that could satisfy the energy needs of the sensors. 6.2 COG-ASSESS University of Alberta | Scientific Excellence - Leadership | 2017-12-18 | |
| Simulation-Based Deployment Configuration of Smart Indoor SpacesEvaluating Wireless Sensor Network (WSN) deployment scenarios for sensor-driven applications is a tedious and labour-intensive task. To mitigate the cost involved with comparatively evaluating alternative deployments, we present an integrated methodology that enables the modeling, simulation, and evaluation of alternative candidate WSN deployments, as well as, the fine-tuning of the corresponding sensor--driven applications. Based on our previous experience on indoor occupant localization and activity recognition, we illustrate our methodology by applying it to the task of deploying an ambient-intelligence application. We explain how our methodology models the real-world environment and the candidate WSN deployment, simulates the occupants' activities and the WSN run-time behavior, and evaluates, through a variety of metrics, the effectiveness of the application under different deployment configurations. We demonstrate our methodology on two real-world localization application scenarios corresponding to two, drastically different, spaces.6.2 COG-ASSESS University of Alberta | Scientific Excellence - Advancing Knowledge | 2019-04-01 | |
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