No abstract

Providing a task-representative user interface for building operations and control puts the user in charge of their health, safety, and well-being and improves task performance. Enabling users control of building conditions and operations often results in poor overall building performance, such as increased energy usage due to lighting a non-occupied room. As a result, building designers limit the control users have in the spaces they occupy by implementing lighting schedules, for example. However, research has indicated an improved user experience results when users regulate their environment. This conflict produces significant challenges in building interaction design regarding the allocation of control in user-building interactions. An approach is being developed to align user-building interaction design with the building's purpose-to support users' tasks. Rather than multiple operation specific interfaces, providing users a unified taskrepresentative interface links building operations, users, and tasks. The result is a more informative interaction between the user and building operations and a more effective, efficient, and enhanced task experience.

Facilitated-voluntary geographic information (f-VGI) is a promising method to enable systematic collection of data from residents about their physical and social environment. The method capitalizes on ubiquitous mobile smartphones to empower collection of geospatially-referenced data. It is important to evaluate the validity of user-generated content for use in research or program planning. The purpose of this study was to test whether the aggregated environmental ("bikeability") ratings from novice community residents converges with ratings from experts using a robust research-based, paper audit-tool (the established Pedestrian Environment Data Scan (PEDS) tool). Equivalence testing statistically showed overall agreement between the composite ratings of bikeability within the novice group.

The purpose of this research is to establish an in-depth understanding of task-related occupant behaviors to serve as the basis for the design of an occupant-building interaction interface. Building simulations are frequently used to design buildings and predict energy performance. Yet, all of these assumptions are related to occupant behavior and interactions with the building. In an occupant-controlled environment, an understanding of the occupant decision-making process must be represented in the simulation task lists. Current task lists assume general occupant behaviors based on averages, and lack the details required for this understanding. This paper looks to strike a balance between simplicity and complexity in the generation of task lists to establish a process for developing an understanding of occupant behavior at a greater level of detail than current practice. A contextual task analysis questionnaire characterizes occupant behavior to provide the link between the building, occupant, and task. Generation of a sample task list demonstrates how a detailed understanding of task-related occupant behaviors can be effectively used as the basis of an occupant-building control scheme.

This paper presents a novel modeling methodology that integrates the near building environmental conditions (or microclimate), whole-building design, and occupant behavior. Accurate predictions of the future building operating conditions lead to designs that serve the building's purpose-to support occupants' tasks. This study bridges the gap between human factors and architecture to include physical, cognitive, and organizational systems into building information modeling using future typical meteorological year climate data, canyon air temperature microclimate model, and a whole-building energy simulation to investigate the impact of future microclimate conditions on a "typical" single-occupant office. Additionally, to capture the effects of building occupant decision-making and adaptive behaviors, an agent-based model is proposed. Model inputs are task-based which aim to produce a more robust model to investigate a variety of human-building control interactions to ensure high building performance and occupant comfort and satisfaction.