Building Level Energy Management System (BLEMS)
Minimizing energy consumption and maintaining desired indoor climate are two main goals of building energy management. BLEMS is driven byoccupants' and buildings' behaviors. It monitors indoor ambient environment with embedded sensor neworks, and studies patterns of behaviors of building systems and building occupants with data mining techniques. Based on these sensing and learning results, BLEMS proactively and reactively controls building systems to meet occupant preferences on heating, cooling, air flow and lighting levels as well as specific energy conservation goals.
Indoor Localization for Supporting Building Emergency Response Operations
Building emergencies are big threats to the safety of building occupants and first responders. One way to reduce the hazards is to provide first responders with timely access to accurate location information. After assessing the value of location information and related requirements, the research proposes a radio frequency based indoor localization framework. Ad-hoc sensor networks are designed, two localization algorithms are proposed, and building information is integrated. A smartphone-centric prototype is built and evaluated in both simulation a building-size experiment.
An Integrated Mobile Sensor System for Building Energy Management
The objective of the research is to reduce energy consumption of buildings while maintaining occupant comfort with interaction, sensor monitoring and online control. Inputs from a wide range of modalities and platforms in a heterogeneous sensor system are integrated, fused and evaluated with stochastic algorithms in order to measure and track indoor climate, energy usage, as well as occupant location, activities, and preferences. Validation is done with extensive building-scale simulations and experimentation.
Imaged-Based Verification of As-Built Documentation of Operational Buildings
As-built models and drawings are essential documents for a variety of purposes including the management of facility spaces, equipment, and energy systems. In an attempt to streamline the procedures for verifying and updating as-built documents, the research investigates the advantages and limitations of using photogrammetric image processing, as opposed to largly time-consuming field surveys and manual measurements, to document and verify actual as-built conditions, and generating 3D models.
Applications of Building Information Modeling in Facilities Management Practices
Building information modeling (BIM) is becoming widely adopted by the construction industry, holds undeveloped possibilities for providing and supporting facilities management (FM) practices with its functionalities of visualization, analysis, control, and so on. By conducting surveys, interviews and case studies, this research explores how BIM can be a beneficial platform for supplementing FM, and aims to help FM professionals recognize the potential areas and data requirements of BIM utilization.
Real-Time Occupancy Detection for Energy Conservation in The Built Environments
Knowing a building’s occupancy plays a fundamental role in increasing context-awareness in the built environment. This research evaluates occupancy modeling (both binary and multiclass) using twelve ambient sensor variables. Performance of six machine-learning techniques is evaluated, and he possibility of building a global occupancy model is examined. The occupancy model is used to estimate and visualize the accumulative room and thermal zone usages in a test bed office building as a way to reveal potential building energy reductions.