Detailed occupancy prediction, occupancy-sensing control and advanced behavioural modelling within whole-building energy simulation

Cette étude a pour but de combler l'écart entre l'état actuel de la simulation énergétique dans le domaine du bâtiment (i.e. hypothèses et modèles) et la connaissance empirique sur le comportement des usagers en matière de contrôle environnemental. L'application principale issue de cette thèse est un module de simulation autonome qui vise la modélisation à haute résolution et à haute fréquence des interactions personne-milieu: de l'occupation des locaux (i.e. l'affectation individuelle d'un environnement modélisé), du contrôle basé uniquement sur la présence ou l'absence des occupants (e.g. détecteurs de mouvement), jusqu'aux modèles comportementaux plus avancés (e.g. commutation manuelle des appareils d'éclairage, l'utilisation des fenêtres ouvrantes). L'intégration du module au sein du logiciel libre ESP-r, un programme qui permet de simuler l'ensemble des interactions bâtiment-systèmes-environnement, permet d'étudier à quel point les modèles d'interactions personne-milieu, issus des études en milieu réel, peuvent influencer les besoins énergétiques d'un bâtiment donné. Certains traits comportementaux, couramment associés aux modèles de contrôle manuel des systèmes d'éclairage, caractérisent également le comportement individuel au niveau des fenêtres ouvrantes; une conclusion issue d'une étude pilote en milieu réel sur le campus de l'Université Laval (Québec). Cette constatation suggère certains traits communs pouvant décrire le comportement des usagers en matière de contrôle environnemental. Le module développé permet également d'étudier le potentiel écoénergétique de stratégies innovatrices: l'application de stratégies de contrôle reposant sur l'adaptation thermique dans un contexte de climatisation hybride, et basées sur l'opération de fenêtres ouvrantes en tant que commutateurs entre climat naturel et climat artificiel. Les résultats préliminaires suggèrent que pour les climats nordiques ou méridionaux, ces approches permettent effectivement de réduire les besoins en climatisation, mais qu'en contre partie les besoins en chauffage augmentent considérablement en raison de l'utilisation des fenêtres en périodes plus tempérées. L'intérêt de la méthode est ici mis en évidence dans sa capacité à simuler globalement l'ensemble des conséquences énergétiques de l'interaction sociale avec l'environnement bâti.This study sets out to bridge the gap between building energy simulation and empirical evidence on occupant behaviour. The major output is a self-contained simulation module that aims to control all occupant-related phenomena which can affect energy use in buildings. It provides high resolution and high frequency occupancy prediction (i.e. when occupants as individual agents occupy a modelled environment), occupant-sensing control (i.e. as driven by the mere presence of one or more occupants, such as occupancy-sensing lighting controls), as well as advanced behavioural models (i.e. active personal control, such as manual switching of lights, manual adjustments to window blinds, operable windows, personalized air-conditioning units). The module is integrated within the ESP-r free software, a whole-building energy simulation program. Simulation results clearly show that occupants-based phenomena exert a strong influence on simulated energy use, revealing a number of limitations in key assumptions in current energy simulation practice. Key behavioural traits, commonly associated to lighting behavioural patterns, also appear to be associated to personal control of operable windows, as demonstrated in a pilot field study in a Université Laval pavilion in Québec. This may suggest an abstract quality to certain behavioural concepts regarding different environmental controls. The study then focuses on the use of the developed work to investigate the energy saving potential of novel yet untried strategies: adaptive comfort control algorithms in hybrid environments, based on the use of operable windows as switching mechanisms between natural and artificial modes of environmental control. Results suggest that for both heating- and cooling-dominant climates, adaptive comfort control effectively reduces cooling requirements, yet operable window use during cooler conditions appear to increase heating requirements. The usefulness of the original method is here illustrated by providing a more complete view on energy use attributed to occupant behaviour

Integrating Smart Ceiling Fans and Communicating Thermostats to Provide Energy-Efficient Comfort

The project goal was to identify and test the integration of smart ceiling fans and communicating thermostats. These highly efficient ceiling fans use as much power as an LED light bulb and have onboard temperature and occupancy sensors for automatic operationbased on space conditions. The Center for the Environment (CBE) at UC Berkeley led the research team including TRC, Association for Energy Affordability (AEA), and Big Ass Fans (BAF). The research team conducted laboratory tests, installed99 ceiling fans and 12 thermostats in four affordable multifamily housing sites in California’s Central Valley, interviewed stakeholders to develop a case study, developed an online design tool and design guide, outlined codes and standards outreach, and published several papers.The project team raised indoor cooling temperature setpoints and used ceiling fans as the first stage of cooling; this sequencing of ceiling fans and air conditioningreducesenergy consumption, especially during peak periods, while providing thermal comfort.The field demonstration resulted in 39% measured compressor energy savings during the April–October cooling seasoncompared to baseline conditions, normalized for floor area. Weather-normalized energy use varied from a 36% increase to 71% savings, withmedian savings of 15%.This variability reflects the diversity in buildings, mechanical systems, prior operation settings, space types, andoccupants’ schedules,preferences, and motivations. All commercial spaces with regular occupancy schedules (and twoof the irregularly-occupied commercial spaces and one of the homes) showed energy savings on an absolute basis before normalizing for warmer intervention temperatures,and 10 of 13 sites showed energy savings on a weather-normalized basis. The ceiling fans provided cooling for one site for months during hot weather when the coolingequipment failed.Occupants reported high satisfaction with the ceiling fans and improved thermal comfort. This technology can apply to new and retrofit residential and commercial buildings

Human Mobility Monitoring using WiFi: Analysis, Modeling, and Applications

Understanding and modeling humans and device mobility has fundamental importance in mobile computing, with implications ranging from network design and location-aware technologies to urban infrastructure planning. Today\u27s users carry a plethora of devices such as smartphones, laptops, tablets, and smartwatches, with each device offering a different set of services resulting in different usage and mobility leading to the research question of understanding and modeling multiple user device trajectories. Additionally, prior research on mobility focuses on outdoor mobility when it is known that users spend 80% of their time indoors resulting in wide gaps in knowledge in the area of indoor mobility of users and devices. Here, I try to fill the gaps in mobility modeling in the areas of understanding and modeling indoor-outdoor human mobility as well as multi-device mobility. In this thesis, I propose the characterization and modeling of human and device mobility. Further, I design and deploy mobility-aware applications for contact tracing of infectious diseases and energy-aware Heating, Ventilation, and Air Conditioning (HVAC) scheduling. I try and answer a sequence of four primary inter-related questions : (1) how is indoor and outdoor user mobility different, (2) are multiple device trajectories belonging to a single user correlated, (3) how to model indoor mobility of users and (4) how to design effective mobility aware applications that are easily deployable and align with long term goals of sustainability as well relay positive societal impact. The insights gained from each question serves as a base to build up on the next question in the series. I present answers to these questions across three main parts of my thesis. The first part comprises of characterization and analysis of human and device mobility. In this part I design and develop tool to extract device trajectories from WiFi system logs syslog and map devices to users. These extracted trajectories and device to user mapping are used to characterize and empirically analyze the mobility of users at varying spatial granularity (indoor, outdoor) and extract device mobility correlations between multiple devices of users and forms the first part of my thesis. In the second part, based on the insights gained from the multi-granular and multi-device mobility characterization stated above, I argue that mobility is inherently hierarchical in nature and propose novel indoor human mobility modeling approach. Third, I leverage the passively observed mobility to design mobility-aware applications that either look back or look ahead in time. WiFiTrace is a look back or backtracking application that is a network-centric contact tracing tool to aid healthcare workers in manual contact tracing of infectious diseases and iSchedule is a look ahead machine learning based mobility-aware energy-saving application that predicts Heating, Ventilation, and Air Conditioning (HVAC) schedule for higher energy savings while increasing user comfort

Occupant-Centric Simulation-Aided Building Design Theory, Application, and Case Studies

This book promotes occupants as a focal point for the design process

Non-Intrusive Occupancy Detection Methods and Models

Occupants in the built environment impact facility energy consumption and indoor air quality. Predicting the presence of occupants within the built environment can therefore be used to manage these factors while providing additional benefits in terms of emergency management and future space utilization. Detecting occupancy requires a combination of sensors and models to accurate assess data collected within facilities to predict occupancy. This thesis investigated occupancy detection through a non-invasive data collection sensors and model. Specifically, this thesis sought to answer two research questions examining the ability of a radial basis function to accurately predict occupancy when generated from data collected from two facilities. Generated models were evaluated on the data from which they were derived, self-estimation, as well as applied to other areas within the same facility, cross-estimation. The motivation, sensors and models, were discussed to establish a framework. The principle implications of this research is to reduce energy consumption by knowing when the built environment is occupied through the use of non-invasive data collection sensors supplying inputs into a model. The resulting accuracy rates of the derived models ranged from 48% - 68% when using three collected parameters: temperature, relative humidity and carbon dioxide

Airborne Contaminant Dispersal in Critical Built Environments

The Indoor Air Quality (IAQ), being one of the most significant exposures to human beings, encompasses the concepts of comfort and safety from unwanted contaminants. Whereas the thermal comfort is controlled through proper conditioning and distribution of ventilated air, controlling the airborne contaminants requires careful investigation of the flow characteristics. IAQ translates to different requirements, depending on the intended use of the indoor environment. In critical indoor spaces such as Operating Rooms and Cleanrooms, the principal focus of IAQ is to remove/contain/divert contaminants flowing with the airstream to maintain the required sterility, as contamination can lead to adverse patient/product outcomes. The airborne contaminants, generally submicron-sized particles, are controlled by directional airflow through differential pressure, depending on whether the space needs to exfiltrate (e.g., Operating Room – positive pressure) or contain (e.g., Isolation Room – negative pressure) the airborne contaminants. The current design paradigm that determines such pressure differential assumes steady-state conditions. Theoretically, during the steady-state, the rate of flow velocity change is zero, resulting in a constant flow field in time, and the distribution of contaminants in the space can be modeled using ordinary differential equations. Therefore, the steady-state assumption must hold to explain the contamination dispersal. However, in practice, transient occupant interventions like a door opening and walking through the steady-state flow fields alter the flow characteristics. In response, this dissertation examines how occupant-introduced transient events affect the steady-state flow. This study aims to quantify and identify patterns of the changes in the flow characteristics for different scenarios of realistic door openings and human walks under a range of ventilation rates through controlled experiments and numerical simulations. Through specifically designed experiments, the impacts of door operation and occupant walking were characterized and quantified based on different levels of supply flow rates from the ventilation system. The results of the experiments suggested that special considerations were required to control for the transient phenomena and the pressure differential. The walking and door opening experiments also found distinguishable changes in the flow characteristics under each separate interaction between the indoor environment and the occupant. It was interesting to note that even though the magnitude of the effects was different for different levels of initial condition and intervention types, the changes in the flow properties exhibited identical patterns that were possible to model and make predictions. Thus, this dissertation considers the sporadic transient interventions from the occupants (e.g., - door opening and walking) as events and discusses an approximation method called ‘Event-Based Modeling’ (EBM) using the collected data through these experiments. Two-dimensional numerical models were developed to obtain additional data on the changes in airflow characteristics and were used to model and test the accuracy of EBM’s prediction capabilities. The results demonstrated that the predictions from EBM were accurate, and the computational efficiency is improved compared to the traditional numerical simulation approach. This method can eliminate parallel modeling of the same phenomena, providing alternatives to simulate complex and computationally intensive transient events repeatedly. As a potential application, the changes in flow velocities from human-environment interactions in a critical indoor environment like an operating room can be predicted using the EBM method. This way, the ventilation systems can be designed as occupant-centric and energy-efficient by considering the impacts of the transient events instead of only considering the steady-state events

Earth benefits from NASA research and technology. Life sciences applications

This document provides a representative sampling of examples of Earth benefits in life-sciences-related applications, primarily in the area of medicine and health care, but also in agricultural productivity, environmental monitoring and safety, and the environment. This brochure is not intended as an exhaustive listing, but as an overview to acquaint the reader with the breadth of areas in which the space life sciences have, in one way or another, contributed a unique perspective to the solution of problems on Earth. Most of the examples cited were derived directly from space life sciences research and technology. Some examples resulted from other space technologies, but have found important life sciences applications on Earth. And, finally, we have included several areas in which Earth benefits are anticipated from biomedical and biological research conducted in support of future human exploration missions

An improved mosquito electrocuting trap that safely reproduces epidemiologically relevant metrics of mosquito human-feeding behaviours as determined by human landing catch

Background: Reliable quantification of mosquito host—seeking behaviours is required to determine the efficacy of vector control methods. For malaria, the gold standard approach remains the risky human landing catch (HLC). Here compare the performance of an improved prototype of the mosquito electrocuting grid trap (MET) as a safer alternative with HLC for measuring malaria vector behaviour in Dar es Salaam, Tanzania. Methods: Mosquito trapping was conducted at three sites within Dar es Salaam representing a range of urbanicity over a 7-month period (December 2012–July 2013, 168 sampling nights). At each site, sampling was conducted in a block of four houses, with two houses being allocated to HLC and the other to MET on each night of study. Sampling was conducted both indoors and outdoors (from 19:00 to 06:00 each night) at all houses, with trapping method (HLC and MET) being exchanged between pairs of houses at each site using a crossover design. Results: The MET caught significantly more Anopheles gambiae sensu lato than the HLC, both indoors (RR [95 % confidence interval (CI)]) = 1.47 [1.23–1.76], P < 0.0001 and outdoors = 1.38 [1.14–1.67], P < 0.0001). The sensitivity of MET compared with HLC did not detectably change over the course of night for either An. gambiae s.l. (OR [CI]) = 1.01 [0.94–1.02], P = 0.27) or Culex spp. (OR [CI]) = 0.99 [0.99–1.0], P = 0.17) indoors and declined only slightly outdoors: An. gambiae s.l. (OR [CI]) = 0.92 [0.86–0.99], P = 0.04), and Culex spp. (OR [CI]) = 0.99 [0.98–0.99], P = 0.03). MET-based estimates of the proportions of mosquitoes caught indoors (P i ) or during sleeping hours (P fl ), as well as the proportion of human exposure to bites that would otherwise occurs indoors (π i ), were statistically indistinguishable from those based on HLC for An. gambiae s.l. (P = 0.43, 0.07 and 0.48, respectively) and Culex spp. (P = 0.76, 0.24 and 0.55, respectively). Conclusions: This improved MET prototype is highly sensitive tool that accurately quantifies epidemiologically-relevant metrics of mosquito biting densities, behaviours and human exposure distribution

Atmospheric Air Pollution and Monitoring

Indoor air quality (IAQ) is an important aspect in building design due to its effect on human health and wellbeing. Generally, people spend about 90% of their time indoors where they are exposed to chemicals, particulate matters, biological contaminants and possibly carcinogens. In particular, the air quality at hospitals carries with it risks for serious health consequences for medical staff as well as patients and visitors. This book is a study of atmospheric air pollution and presents ways we can reduce its impacts on human health. It discusses tools for measuring IAQ as well as analyzes IAQ in closed buildings. It is an important documentation of air quality and its impact on human health