Farrokh Jazizadeh

Virginia Tech (Virginia Polytechnic Institute and State University) | VT · Department of Civil and Environmental Engineering

Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary...

Sustainable buildings are designed to reduce energy use and other environmental impacts and to provide indoor environmental conditions that maximize well-being and satisfaction among building occupants. However, occupants' comfort in and satisfaction with such buildings has been inconsistent. Evidence indicates occupants' expectations of indoor bui...

This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence. The field of HBI builds on several existing efforts in h...

Mixed reality is gradually becoming ubiquitous and significant in education owning to the inherent benefits of active participation and tacit knowledge development in a safe and engaging environment. However, limited studies have explored design features that facilitate its use as a pedagogical tool in construction education, particularly in equipp...

Dynamic models of occupancy patterns have shown to be effective in optimizing building-systems operations. Previous research has relied on CO2 sensors and vision-based techniques to determine occupancy patterns. Vision-based techniques provide highly accurate information; however, they are very intrusive. Therefore, motion or CO2 sensors are more w...

Dynamic models of occupancy patterns have shown to be effective in optimizing building-systems operations. Previous research has relied on CO$_2$ sensors and vision-based techniques to determine occupancy patterns. Vision-based techniques provide highly accurate information; however, they are very intrusive. Therefore, motion or CO$_2$ sensors are...

With the widespread adoption of smart meters in buildings, an unprecedented amount of high-resolution energy data is released, which provides opportunities to understand building consumption patterns. Accordingly, research efforts have employed data analytics and machine learning methods for the segmentation of customers based on their load profile...

With the increased adoption of distributed energy resources (DERs) and renewables, such as solar panels at the building level, consumers turn into prosumers with generation capability to supply their on-site demand. The temporal complementarity between supply and demand at the building level provides opportunities for energy exchange between prosum...

Building stakeholders must invest an increasing amount of resources in the process of delivering energy-efficient buildings as energy efficiency standards become more aggressive, and building systems become more complex. This paper documents the earlier stages of a larger project, which is a joint venture between Virginia Tech and an industry partn...

Analyzing smart meter data to understand energy consumption patterns helps utilities and energy providers perform customized demand response operations. Existing energy consumption segmentation techniques use assumptions that could result in reduced quality of clusters in representing their members. We address this limitation by introducing a two-s...

Human-aware HAVC operations have been shown to be effective in improving energy efficiency, which is constrained by the HVAC system configuration and operational logic. These constraints can result in a lack of operational flexibility, which in turn reduces the adaptation capacity for energy efficiency. Therefore, in this study, we investigated the...

As demonstrated for extreme events, the resilience concept is used to evaluate the ability of a transportation system to resist and recover from disturbances. Motivated by the high cumulative impact of recurrent perturbations on transportation systems, we have investigated resilience quantification as a performance assessment method for high-probab...

Load shapes obtained from smart meter data are commonly utilized to understand daily energy use patterns for adaptive operations in applications such as Demand Response (DR). However, they do not provide information on the underlying causes of specific energy use patterns – i.e., inference on appliances’ time-of-use (ToU) as actionable information....

Research studies provided evidence on the energy efficiency of integrating personal thermal comfort profiles into the control loop of Heating, Ventilation, and Air-Conditioning (HVAC) systems (i.e., comfort-driven control). However, some conflicting cases with increased energy consumption were also reported. Addressing the limited and focused natur...

Regular monitoring of railway systems is imperative for improving safety and ride quality. To this end, data collection is carried out regularly in the rail industry to document performance and maintenance. The use of machine learning methods in the past recent years has provided opportunities for improved data processing and defect detection and m...

Demand response (DR) is considered an effective approach in mitigating the ever-growing concerns for supplying the electricity peak demand. Recent attempts have shown that the contribution from the aggregate impact of flexible individual residential loads can add flexibility to the power grid as ancillary services. However, current DR schemes do no...

In this study, moving towards enabling the development of a platform for dynamic performance assessment of roadway networks, we have proposed to leverage coarse GPS data from probe vehicles such as taxis to quantify the resilience of road network using a multi-dimensional approach. The method is applied to a dataset of taxi trips in the Washington...

With the widespread adoption of smart metering infrastructures, household energy consumption segmentation is receiving increasing attention. The objective is to transform the large volume of household daily load shapes into representative patterns through clustering methods, with the aim of program targeting and customer engagement. In the literatu...

Power utilities leverage Demand Response (DR) events to effectively reduce the peak load at critical times with excessive power demand. DR programs are generally categorized as manual or automated from the automation perspective. The opportunities for automated DR in the residential sector have emerged with the integration of smart and connected lo...

In recent years, physiological features have gained more attention in developing models of personal thermal comfort for improved and accurate adaptive operation of Human-In-The-Loop (HITL) Heating, Ventilation, and Air-Conditioning (HVAC) systems. Pursuing the identification of effective physiological sensing systems for enhancing flexibility of hu...

Congestion impacts urban mobility, fuel consumption, and air pollution, so it is a critical societal issue. In this study, we have explored the relationship of transportation diversity—the availability of transportation modes (richness) and their distribution in a community (evenness)—on the traffic jam characteristics represented by congestion dur...

The adoption of smart meters in residential households provides electricity consumption data with high temporal resolution. Considering the wealth of the generated information, data analytics methods can be employed to segment the households based on the timing and magnitude of consumption. Specifically, the resultant load shapes reveal the lifesty...

This study seeks to evaluate the applicability of heat flux sensors, as a proxy for contextual thermal comfort representation in an environment, for the human-in-the-loop (HITL) heating, ventilation, and air conditioning (HVAC) operations. In accounting for personalized thermal comfort inference, the predicted mean vote (PMV) model is not often app...

The emergent context-aware applications in ubiquitous computing demands for obtaining accurate location information of humans or objects in real-time. Indoor location-based services can be delivered through implementing different types of technology, among which is a recent approach that utilizes LED lighting as a medium for Visible Light Communica...

Problem: The curricular shift toward scientific theory along with a proliferation of distance education and practical constraints have contributed to diminishing laboratory development, in turn affecting design skills and technical competencies of students in many programs. Objective: The objective of the current study is to help guide the improvem...

Condition monitoring of rail infrastructure is an important task to ensure the safety and ride quality. The increasing travel demands of the rail network due to higher miles traveled requires regular monitoring of the infrastructure and efficient processing of the data for timely decision-making. Despite the regular data collection on different par...

Heating, ventilation, and air-conditioning (HVAC) systems account for almost half of the energy consumption in buildings. By benefiting from advancements in information and communication technology, human-in-the-loop HVAC operations have drawn considerable attention in the last decade with the aim of curtailing unnecessary energy use and providing...

Research efforts have demonstrated the potentials of improving the performance of Heating, Ventilation, and Air-Conditioning (HVAC) systems by leveraging personalized thermal comfort preferences and profiles. However, there are remaining challenges for effective control in collective conditioning in multi-occupancy scenarios. In this study, we have...

Monitoring the temporal changes in the operational states of appliances is a key step in inferring the dynamics of operations in smart homes. This information could be leveraged in a variety of energy management applications including energy breakdown of individual loads, inferring the occupancy patterns, and associating the energy use to occupants...

Spectral clustering algorithms typically require a priori selection of input parameters such as the number of clusters, a scaling parameter for the affinity measure, or ranges of these values for parameter tuning. Despite efforts for automating the process of spectral clustering, the task of grouping data in multi-scale and higher dimensional space...

Spectral clustering algorithms typically require a priori selection of input parameters such as the number of clusters, a scaling parameter for the affinity measure, or ranges of these values for parameter tuning. Despite efforts for automating the process of spectral clustering, the task of grouping data in multi-scale and higher dimensional space...

Power utilities rely on Demand Response (DR) programs in order to shave the peak load at critical times, when there is an excessive demand. In the context of automation, DR programs are categorized as manual or automated. With the emergence of home energy management (HEM) systems that monitor and operate the household appliances, the opportunities...

Despite their impact on work performance, cognitive responses to thermal variations in buildings have not been accurately quantified. Practical limitations in individual laboratory experiments with limited participants often cause low statistical power and restrict generalizability. Thus, inconsistencies in individual studies motivate summary revie...

Electricity disaggregation, the task of inferring appliances' energy consumption in a building from a few sensing points, has received attention in the energy community. In this paper, we introduce EMBED, a publically available dataset for Energy Monitoring through Building Electricity Disaggregation. EMBED is the most comprehensive fully labeled d...

This study presents a vision-based approach that employs RGB video images as the sole source for inferring thermoregulation states in the human body in response to thermal condition variations in indoor environments. The primary objective is to contribute to our envisioned thermoregulation-based HVAC control that leverages actual thermal demands fr...

HVAC systems account for more than 40% of energy consumption in buildings to provide satisfactory indoor environments for occupants. The integration of personalized thermal comfort in the operation of HVAC systems has been shown to be highly effective in enhancing energy efficiency of buildings. To this end, research efforts have proposed personali...

Assessment of the transportation infrastructure resilience as the ability of a system to recover after an incident is one of the priorities of engineers and decision-makers. Due to challenges of real-world data collection, performance and resilience assessment are commonly carried out through event simulations, which still call for validating field...

This study evaluates the sensitivity of our novel and non-intrusive approach, powered by Doppler radar sensors to assess thermoregulation states as feedback to heating, ventilation, and air-conditioning (HVAC) systems. Thermoregulation-based HVAC control employs changes in physiological response of the human body for heat dissipation adjustment as...

Considering the contribution of building systems in the energy and electricity consumption globally and in the US, facilities management and operational strategies that help improve energy efficiency have been the subject of several studies. Electricity desegregation through non-intrusive methods is one of these strategies that provide cost-effecti...

Providing users’ location information in indoor environments has great importance for the management of the built environment in energy conservation efforts, facilitating navigation in large and complex places, providing context-aware information, and addressing safety concerns in emergency situations. Various technologies have been proposed to add...

Studies have shown that the human-centered control of heat, ventilation and air conditioning systems could enhance their performance. Respiration is one of the principle mechanisms that human body uses to exchange heat with the ambient environment. This study evaluates the feasibility of using respiration to represent occupants’ thermal comfort usi...

Studies have shown that increasing the granularity of energy consumption information in buildings could facilitate achieving energy saving objectives. Lighting systems in buildings are one of the main consumers of electricity with a share of approximately (direct and indirect) 23 percent of the total electricity in the US. Direct monitoring of ligh...

Urban facilities are major contributors to annual energy consumption and therefore, evaluating their energy efficiency and retrofit planning play a major role in achieving sustainability goals. For urban facilities, such as buildings, energy performance audits could be conducted by detailed evaluation at building level. However, at urban level, det...

The main driving factor in determining control settings of an air conditioning system is indoor thermal condition and its association with occupants' satisfaction. In recent years, the ubiquity of computing devices has led to techniques for learning personalized thermal comfort by using feedback through smartphones or (commonly wearable) sensors to...

Buildings, which account for the majority of electricity consumption in the US, lack efficient electricity monitoring tools for occupants to take action and reduce energy consumption. Non-intrusive load monitoring is a cost effective approach for electricity consumption disaggregation at the appliance level by using one sensing node in a building u...

Non-intrusive load monitoring (NILM) is a low-cost alternative to appliance level sub-metering, that leverages signal processing and machine learning techniques to estimate the power consumption of individual appliances from whole-home measurements. However, the difficulty associated with obtaining training data sets for the commonly used supervise...

We consider the problem of automatically learning the optimal thermal control in a room in order to maximize the expected average satisfaction among occupants providing stochastic feedback on their comfort through a participatory sensing application. Not assuming any prior knowledge or modeling of user comfort, we first apply the classic UCB1 onlin...

Occupant comfort is a dominant influence on the performance of HVAC operations. Most HVAC system operations rely on industry standards to ensure satisfactory environmental conditions during occupancy. Despite the increasing building energy consumption rates, occupants are not usually satisfied with indoor conditions in commercial buildings. To addr...

Centrally controlled heating, ventilation, and air conditioning (HVAC) systems in commercial buildings are operated by building management systems (BMS) based on the predefined operational settings and a set of assumptions. Despite the high rate of energy consumption by HVAC systems in commercial buildings, observations showed that a significant po...

Current building management systems (BMS) operate based on conservatively defined operational hours, maximum occupancy rates, and standardized occupant comfort set points. Despite the increasing building energy consumption rates, occupants are not usually satisfied with the indoor conditions in commercial buildings. This study proposes an intermedi...

Current pavement condition-assessment procedures are extensively time consuming and laborious; in addition, these approaches pose safety threats to the personnel involved in the process. In this study, a RGB-D sensor is used to detect and quantify defects in pavements. This sensor system consists of a RGB color image, and an infrared projector and...

In the U.S., buildings account for 42% of the total energy consumption - half of which is consumed by commercial buildings. Knowledge of electricity use patterns in buildings has several applications in demand side management. In commercial buildings, acquiring energy consumption information with high granularity requires consuming node level sub-m...

Limited availability of energy resources has motivated the need for developing efficient measures of conserving energy. Conserving energy in commercial buildings is an important goal since these buildings consume significant amount of energy, e.g., 46.2% of all building energy and 18.4% of total energy consumption in the US [1]. This demonstration...

Buildings are one of the major consumers of energy in the U.S. Both commercial and residential buildings account for about 42% of the national U.S. energy consumption. The majority of commercial buildings energy consumption is attributed to lighting (25%), space heating and cooling (25%), and ventilation (7%). Several research studies and industria...

In this study, an inexpensive depth sensor is used to identify defects in pavements. This depth sensor consists of an infrared projector and camera. An innovative approach is proposed to interpret the data acquired by this sensor. The proposed system in this study is a breakthrough achievement for autonomous cost-effective condition assessment of r...

Facilities management (FM) encompasses and requires multidisciplinary activities, and thus has extensive information requirements. While some of these needs are addressed by several existing FM information systems, building information modeling (BIM), which is becoming widely adopted by the construction industry, holds undeveloped possibilities for...

There is growing interest in reducing building energy consumption through increased sensor data and increased computational support for building controls. The goal of reduced building energy is often coupled with the desire for improved occupant comfort. Current building systems are inefficient in their energy usage for maintaining occupant comfort...

Today's construction engineering and management (CEM) graduates must have strong communication and teamwork skills; they must have the ability to work efficiently within colocated teams; and finally, they must know how to apply fundamental engineering, management, and computer skills in practice. However, the traditional CEM education does not equi...

This paper describes an innovative multiagent system called SAVES with the goal of conserving energy in commercial build-ings. We specifically focus on an application to be deployed in an existing university building that provides several key novelties: (i) jointly performed with the university facility management team, SAVES is based on actual occ...

3D laser scanning technology is now widely and increasingly used in several construction tasks such as indoor mapping, project control, construction metrology and automation, development of as-built models, and resource management through scanning, data processing, and modeling stages. The accuracy of these stages affects the quality of the end pro...

In laser scanning, the precision of the point clouds (PC) acquisition is influenced by a variety of factors such as environmental conditions, scanning tools and artifacts, dynamic scan environments, and depth discontinuity. In addition, object color, object texture, and scanning geometry are other factors that affect the quality of point clouds. Th...

Ambient factors such as temperature, lighting, and air quality influence occupants' productivity and behavior. Although these factors are regulated by industry standards and monitored by the facilities management groups, occupants' perceptions vary from actual values due to various factors such as building schedules and occupancy, occupant activity...

Recent years have seen a rise of interest in the deployment of mul-tiagent systems in energy domains that inherently have uncertain and dynamic environments with limited resources. In such do-mains, the key challenge is to minimize the energy consumption while satisfying the comfort level of occupants in the buildings un-der uncertainty (regarding...

The primary consumers of building energy are heating, cooling, ventilation, and lighting systems, which maintain occupant comfort, and electronics and appliances that enable occupant functionality. The optimization of building energy is therefore a complex problem highly dependent on unique building and environmental conditions as well as on time d...

Velocity gradient between main channel and flood plains in compound channels leads to the formation of a large shear layer and secondary currents between these two subsections. These phenomena in the interaction region bring about a complex three-dimensional nature of the flow in compound channels. To cope with these flows, many numerical investiga...

Paper presented at The Seventh International Conference on HydroScience and Engineering (ICHE) hosted by the College of Engineering at Drexel Univeristy on September 10-13, 2006 in Philadelphia, Pennsylvania. The conference theme was IT in the Field of HydroSciences. It included several mini-symposia that emphasized IT topics in HydroSciences and t...