HUMAN-BUILDING INTERACTION FOR ENERGY EFFICIENCY
EAGER: Developing a Mathematical Framework to Enable Bi-Directional Interactions of Humans with Smart Engineered Systems Using Relational Elements
The modeling framework for user-virtual human agent interactions is the key contribution to smart engineered systems modeling and design and occurs at the intersection of engineering, the behavioral sciences and computational modeling. If successful, the mathematical framework will be used to design smart buildings that have two-way interactions with people. The research objectives contribute to the ultimate goal of enabling cyber-physical systems to interact and collaborate with humans. This project integrates experimental data into the mathematical models, testing the inclusion of relational elements embedded in the personification of a building. The models will predict which response is the most suitable for a building-user interaction. This model will also be informed and constrained by existing theoretical work on persuasion. The model will account for various contextual, temporal and personal factors as well as the changes in user response due to continuous interactions with the building. The multiple-step modeling methodology incorporates a combination of machine learning techniques, mathematical projections for the classification problem, and statistical models such as Markov model, and autoregressive moving average models. In particular, the contributions are twofold: (1) modeling user-building interactions using virtual human agents personifying buildings; and (2) performing fundamental research on how theories of human interpersonal trust and influence can inform the design of automation. The research will contribute to the fundamental understanding of human-machine teamwork, including elucidating theories of why and how people build connections with automated systems and advance our general understanding of how automation exhibiting relational features can facilitate behavior change in the population served by those systems.
Sponsor: National Science Foundation (Award number: 1548517)
PI: Prof. Burcin Becerik-Gerber
Co-PI: Prof. Jonathan Gratch
Acknowledgment and Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No.1548517. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
A Human-Building Interaction Framework for Responsive and Adaptive Built Environments
The purpose of this project is to advance our knowledge about the impact of human-building interactions on energy use, and to explore intelligent, collaborative, and personalized approaches increase energy efficiency and awareness. Taxonomies of types, features, and patterns of human-building interactions will be developed, based on high-resolution building and human related data. The impact of human-building interactions on energy use and comfort will be quantitatively described using a simulation environment that incorporates multiple simulations and modeling technologies. The research will build on the concept of heterogeneous teamwork between building members and their users, through the use of computer agents that represent and interact with these building systems and their users. A model, capable of learning user preferences for automation, will be employed, tested and validated. A diverse set of communication strategies and styles will be evaluated through human subject experiments for influencing energy and comfort.
Sponsor: National Science Foundation (Award number: 1351701)
PI: Prof. Burcin Becerik-Gerber
Acknowledgment and Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No. 1351701. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Creating an Energy Literate Society of Humans, Buildings and Agents for Sustainable Energy Management
The multi-disciplinary team of investigators will develop an energy-aware, cyber-physical multi agent framework of buildings, humans, and intelligent software agents for sustainable energy management, taking a collective, energy literacy approach to influencing building users, operators, designers, and engineers. The investigators will first assess behavior of building occupants, evaluate building design/system specifications, and identify building operational policies. They will then build a multi-agent model to integrate these different systems. Based on this integrated model, feedback about occupant energy use to building designers will be provided to shape early-stage design decisions that have the longest lasting impact on building's lifecycle footprint. The central focus is designing a multi-component model of energy consumption in office buildings in order to identify and test the optimal points of change in energy systems. Specifically, the research predicts that energy use could be optimized and occupant comfort could be maximized in an integrated way by changing occupant behavior, design/system specifications, and building operators' policies via an agent-based system. The system will be tested both in professional and student designer studios to validate the impact of the model in energy aware design decisions. The research contributes to the arena of design and engineering by providing human behavior input in early design stages, the arena of building operations by dynamically controlling buildings based on human behavior and preferences, as well as behavioral science and design intersection by understanding how/if different design features impact sustainability behavior of occupants.
Sponsor: National Science Foundation (Award number: 1231001)
PI: Prof. Burcin Becerik-Gerber
Co-PI: Prof. Milind Tambe, Prof. Wendy Wood, Prof. David Gerber
Acknowledgment and Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No.1231001. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
An Integrated Mobile Sensor System for Occupancy and Behavior Driven Building Energy Management
The research objective of this project is to test the hypothesis that interactive, sensor monitoring and online control can significantly reduce the energy consumption of buildings (by 20 percent or more) while maintaining occupant comfort. Through simulations and experimentation, inputs from a wide range of modalities and platforms in a heterogeneous sensor system (including wired and wireless sensors; mobile and static sensors; automatic and human-input-based sensors) are integrated and fused in order to measure and track indoor climate, energy usage, as well as occupant location, activities, and preferences with much higher accuracy and lower cost compared to homogeneous systems. The research encompasses mathematical and empirical analyses and evaluation of efficient online stochastic algorithms based on multi-armed bandit theory that take the integrated sensor measurements as input to learn over time how to automatically operate building controls, so as to minimize energy consumption while maintaining occupant comfort, and quantify the gains in energy consumption obtained in typical environments.
Sponsor: National Science Foundation (Award number: 1201198)
PI: Prof. Burcin Becerik-Gerber
Co-PI: Prof. Bhaskar Krishnamachari
Acknowledgment and Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No.1201198. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Impact of Design on Energy Behavior: Explorations within Virtual Immersive Environments
The amount and complexity of available data generated in the design and construction phases of buildings and infrastructure systems are rapidly growing. Such data can improve building designs by considering both the architectural and engineering perspectives as well as the end users’ personal needs in energy and comfort. In order to gain efficiency in exploiting and extracting the necessary data and to study human response to different design alternatives, As part of the SEP project (1231001), this research aims to study impact of design on energy behavior within immersive virtual environments. These interactive environments provide the users with an additional dimension, allowing them to comprehend more information about the designed environment. More importantly, interactive immersive environments give the users a sense of “presence" in a virtual setting, which currently is not part of the design process. This purpose of this research is to (1) identify the data requirements for user-data interactions for AEC professionals and practices, (2) understanding the human energy consumption behavior and developing alternative methods to reduce such energy use, (3) creating agent interactions with building users to provide additional information about the design, energy consumption, and the improvements could made to reduce the energy use on daily basis (4) and allowing designers to develop alternative and cost effective designs based on the end user feedback.
USC i-LAB Research Video: Immersive Virtual Environments
GOALI/CPS: Medium: A Framework for Enabling Energy-Aware Smart Facilities
The goal of this research is to identify ways to inexpensively provide specific information about energy consumption in buildings and facilitate conservation. Signal processing, machine learning, and data fusion techniques will be developed to extract actionable information from whole-building power meters and other available sensors. The main objectives are: (a) to create a framework for obtaining disaggregated, appliance-specific feedback about electricity consumption in a building by extracting high-value information from low-cost data sources; and (b) to investigate and develop data mining and machine learning algorithms for making use of appliance-specific electricity data, in order to provide users with recommendations on how to optimize their energy consumption and understand the effects of their energy-related decisions. The main scientific merit of the project is the development of a framework for evaluating energy-use-disaggregation methods according to their value for promoting energy conservation. The resulting data sets will be large enough to produce significant conclusions about the feasibility and effectiveness of the technology, and allow for the development of new models about the trends and patterns of appliance usage in buildings.
Sponsor: National Science Foundation (Award number: 0930868)
PI: Prof. Mario Berges
Co-PI: Prof. Lucio Soibelman (Former PI)
Acknowledgment and Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No. 0930868. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Building Level Energy Management System (BLEMS)
The importance of efficiency in building energy consumption has assumed great urgency due to fast depleting energy resources and increasing environmental pollution. To address this urgent and practical issue, the BLEMS project aims to develop solutions for bringing together ad-hoc legacy Energy Management System (EMS) configurations under a single unified framework that makes them interoperable. Communication networks are implemented to transmit building sensor data to a centralized brain which in response, send and control information to system actuators. In this way, the framework alleviates the apparent limitations of EMS legacy systems, including security, reliability, extensibility, self-management, and self-dispersed optimal energy allocation. By studying the human behavior in regard to energy consumption and understanding the building behavior in regard to device operations, the behavior-driven self-contained BLEMS system serves to maximize user/occupant comfort levels while simultaneously minimizing energy usage and/or energy cost.
Sponsor: Department of Energy (Award number: DE-EE0004019)
PI: Information Sciences Institute
Co-PI: Prof. Burcin Becerik-Gerber
USC i-LAB Research Video: BLEMS
Acknowledgment and Disclaimer: This material is based upon work supported by the Department of Energy under Grant No. DE-EE0004019. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of Energy.