Access Control PatternAC Pattern Dimensions
Possible User(READ, WRITE, ACTUATE)(Energy Meter, Temperature Setpoint, etc)CONDITIONTODOContext-BasedMetadata-Based
VenueYearPaper TitleApplicationSummaryoccupantanybodyenergy providerbuilding managerother appsothersNoteHOWWHATWHOWHENtemporary accessevent typeTime (when)Event
(state changes)
User Locationrsrc-rsrc relationrsrc typersrc-user relationuser-user relationRole
Buildsys2009Challenges in Resource Monitoring for Residential SpacesEnergy Disaggregation
Real-time electricity and water monitoring
Detect the Appliance’s load using NILM techniques.
Problems: Inferred information like behavior, health may be privacy sensitive.
000110monitor real-time electricity and water usage; this pattern assumes that the app/algorithm has access to real-time data and inferences from the data.
Power Meter and Water Flow monitor(1)Individual Users
(2)Building Managers / Sensor Drivers
Read Data continously for Drivers, Passive continuous monitoring0001001001
Buildsys2009Energy Efficient Building Environment Control Strategies Using Real-time Occupancy Measurements
Occupancy-Based Control
Using data from camera sensor network predict user mobility patterns in buildings.
Using the mobility patterns models, predict room usage thereby enabling control to the HVAC systems in an adaptive manner so as to reduce the energy consumed by HVAC systems.
000100Provide occupancy information of a building and usage patterns to the BMs(1) READCamera Sensor Deployment(1) BuildingManagers 3 images every 2 seconds0user location00101001
Buildsys2009Evaluation of Energy-Efficiency in Lighting Systems using Sensor NetworksOccupancy-based controlUses extra lighting sensors to see whether lighting energy is being wasted001100read, writeread occupany sensor
read light controller
building manageralways (or when occupancy status is changed?)0device state0
when the light is on
Buildsys2009iSense: A Wireless Sensor Network Based Conference Room Management SystemOccupancy Detection;Space ManagementMeasure occupancy to detect the schedules of conference rooms are correct or not. Improve the utilization00011occupantsreadread occupancy sensors, calendarundecidedwhen the room is booked.0calendar schedule0calendar is booked01100-1
Buildsys2009The Case for ApportionmentEnergy FootprintingApportion the total energy consumption into individual occupants100110READ Energy
WRITE find-grained Energy
(if visualizing too, READ find-grained Energy)
readread energy meters, occupants locationsundeterminedcontinuously000000110-1
Buildsys2009The Energy Dashboard: Improving the Visibility of Energy Consumption at a Campus-Wide ScaleWeb Displaysmedium-granularity data visualization ( e.g Plug load, Machine-room, lighting, etc )11010No specific target users.
(maybe building managers and occupants? Or other researchers who was approved to get access? The researchers may come from a group and we may define such group.)
READ Energy by userreadenergy metersanybodyread energy meters0000001000
Buildsys2009The Self-Programming Thermostat: Optimizing Setback Schedules based on Home Occupancy PatternsOccupancy-based controlOptimize between energy usage and thermal comfort given occupancy prediction.10110occupantsread, writeread occupancy sensor
actuate occupancy command
occupantscontinuously (or when it's scheduled.)0000011100
Buildsys2009Using Circuit-Level Power Measurements in Household Energy Management SystemsEnergy Disaggregation
circuit-level energy measurements to device-level estimates
state information (disabled/enabled) would be available to the energy disaggregation algorithm.
Integrate a control system and implement the logic required for automatic training and intelligent control.
100000App performing circuit-level energy measurement assumes access to real-time energy data of all devices. Assumes access to devices states (on/off) during the training phase.(1)Read,Actuate
Power Meter(1)Individual Users
(2)Sensor Drivers
passive continuous monitoring of data initial training, Later read based on state changes1device state0
1 (device state changes during training)
Buildsys2010A Limited-Data Model Of Building Energy ConsumptionEnergy Model00000Undeterminedreadread hvac, lighting, pc statuses, building energy meterundeterminedhistorically once, and continuously predict100001100-1
Buildsys2010Building-level Occupancy Data to Improve ARIMA-based Electricity Use ForecastsEnergy Modelfine grained occupancy using PIR, CO2 and network logs.00111non-determinedreadread occupancy sensors,
read energy meters
nondeterminedcontinuously (or once historical data)100001100-1
Buildsys2010Contactless Sensing of Appliance State Transitions Through Variations in Electromagnetic FieldsEnergy DisaggregationEMF sensor to detect power consumption state changes.
sensors can provide continuous feedback for a NILM system to adjust or re-train appliance signatures as devices change over time or if new devices are added.
000110NILM system assumes access to read data and states of the powerline and the EMF sensor. It also assumes control access. No explicit control on the sharing of the inferences.READMagnetic and Electric field fluctuations of appliancesNILM SystemDuring state changes.1device state0
1 (change in EM signals)
Buildsys2010Granger Causality Analysis on IP Traffic and Circuit-Level Energy MonitoringEnergy Disaggregationzone- level power meters with network traffic to draw causal relationships000110readread zone energy meters
read occupants' office
building manager or occupantscontinuously (or one time historically)1000011000
Buildsys2010HBCI: Human-Building-Computer InteractionRemote Controllerscan QR code on device , connect to cloud and get some display and control11000Users nearby the QR code (can be replaced as location based)
How do we enable QR-based access control? (The app should have full authority to controls... )
actuateactuate any designated setpoints/commandsanybodycontinuously0user request01 (User Request)011000
Buildsys2010NetBem: Business Equipment Energy Monitoring through Network AuditingEnergy Disaggregationnetwork traces with power consumption graph000000read, writeread coarse-grained energy meters
write fine-grained energy meters
Buildsys2010Occupancy Based Demand Response HVAC Control StrategyOccupancy-based controlmodel occupancy using MCMC, run EnergyPlus simulations. occupancy detection using cameras. This requires multi-zones access for predicting a single zone.000100read, actuateread rooms configuration (how close each other is)
read occupacny
actuate VAVs
building managercontinuously0000011001
Buildsys2010Occupancy-Driven Energy Management for Smart Building AutomationOccupancy-based controlOccupany sensor built from PIR and reed door switch. Granularity of occupancy - whether or not the room was occupied.000100read, actuateread occupancy, actuate VAVbuilding managercontinuously0000011001
Buildsys2010Private Memoirs of a Smart MeterEnergy DisaggregationDesign a privacy-enhancing smart meter architecture that allows an electric utility to achieve its net metering goals without compromising the privacy of its customers
Multi-party computation protocol for gateways to preserve the home’s privacy.
001110The utility companies get only electricity used and other information for meeting the net metering goals but only the users get fine-grained measurements. Security: Encrypted communication b/w utility company and user’s power trace app. (1)READ, WRITE, ACTUATE
Smart Energy Meter(1) User
(2) Energy Utility company
Buildsys2010TinyEARS: Spying on House Appliances with Audio Sensor NodesEnergy Disaggregationuses device acoustic signatures000110READEnergy meterOccupantsAcoustic signatures0000011001
Buildsys2010Using Simple Light Sensors to Achieve Smart Daylight HarvestingModel-Predictive Controlhave sensors on windows which capture amount of light00010space managerread, actuateread illuminance sensors,
actuate light and window transparency
buliding manager or occupantscontinously0000011001
Buildsys2010Wireless, Collaborative Virtual Sensors for Thermal ComfortEnergy Modeluse analytical modeling to create virtual sensors where physical sensors don’t exist000110read, writeread room status, outside status,
write more room status
Buildsys2011A Living Laboratory Study in Personalized Automated Lighting ControlsRemote controllerMake user interact with software which controls lighting. lights turn off unless user specifically asks them to be turned on11000anybody (or registered users)actuateactuate lightanybody (or registered users)when the user is authenticated through the QR code0user request00011000
Buildsys2011COPOLAN: Non-Invasive Occupancy Profiling for Preliminary Assessment of HVAC Fixed Timing Strategies
Occupancy-Based Control
correlates power consumption and VLAN activity00011BuildingManagersReadRead: Power Meter, Computer's VLAN ActivityBuildingManagersContinuously0000001101
Buildsys2011Enabling Building Energy Auditing Using Adapted Occupancy ModelsOccupancy DetectionBuild occupancy model ( Gaussian, etc ) for one building and adapt parameters for another building with different floor plans00001energy auditors (or BuildingManagers)ReadRead: CameraEnergy AuditorsContinuously1000001101
Buildsys2011Exploiting Home Automation Protocols for Load Monitoring in Smart BuildingsEnergy DisaggregationUses Home Automation protocols and products to monitor power for individual loads100100Readread appliance activities, energy metersHome Occupants or Building ManagersQuery every 10seconds0000011001
Buildsys2011Managing Plug-Loads for Demand Response within BuildingsDemand responseUse different information sources ( network, PIR ) and smart meters to implement demand response00010Building managerRead,ActuateRead: Energy Meter Actuate: PlugloadBuildingManagersControl when DR request is sent0user location; dr event; user request0DR , Occupancy011101
Buildsys2011The Case for Efficient Renewable Energy Management in Smart Homesdemand responsecontrol strategy exploration - when homes use energy only from grid, or grid + local solar001100ReadRead: Battery Levels; occupancy, from PIR,phone etc.undeterminedContinuously000001100-1
Buildsys2011Towards an Understanding of Campus-Scale Power ConsumptionFDD;Occupancy DetectionUnsupervised Clustering different day's power usage using their frequency components. occupancy model includes classifier using HMM ( from network logs ) , time of day, day of week, etc000000Read,ActuateRead: Power Meter, Network switchesundeterminedEvery 30mins for network, Continous for power meter100001100-1
Buildsys2011WaterSense: Water Flow Disaggregation Using Motion SensorsEnergy Disaggregationuse motion sensors and water flow signatures to disaggregate water energy consumption000110ReadRead: WaterMeter, PIR sensorsHome Occupants or Building ManagersDuring any motion0000011001
Buildsys2012Accurate Real-Time Occupant Energy-Footprinting in Commercial BuildingsEnergy Footprinting100100readread energy meters and appliance statusany registered userscontinuously0user location 0location111100
Buildsys2012Active Actuator Fault Detection and Diagnostics in HVAC systemsFDDDetect stuck / malfunctioning actuators ( window closed / open etc ) by building a model, and perturbing the variables and seeing if the output matches up with the model.000100used cooling valves and windows particularly in the studyread, actuateread: sensors and setpoints that control the sensors,
actuate the setpoints
building manager
Buildsys2012Building the Case For Automated Building Energy Managementweb displays100000read occupant's activitiesReadRead: Power and energy meterOccupantsEvery 5 seconds.0000011001
Buildsys2012Creating a Room Connectivity Graph of a Building from Per-Room Sensor UnitStructural Modelfigure out which rooms are connected using : spillover of artificial light
between rooms; occupancy detections due to movement between
rooms; and a fusion of the two
000110readlight and motion sensorsPassive active monitoring1000011000
Buildsys2012Designing Cost-Efficient Wireless Sensor/Actuator Networks for Building Control SystemsOccupancy-Based Controloptimize communication cost of sensor network. then apply model . shows savings in lighting energy00011read,actuateread luminance sensors, occupancy sensors
actuate windows, light controllers
building manager or room ownercontinuously0000011000
Buildsys2012Energy-Aware Meeting Scheduling Algorithms for Smart BuildingsOccupancy-Based Controlsmall meetings held in smaller rooms, meetings more packed into same room, etc strategies.000110readread calendarapproved usersanytime0000001000
Buildsys2012Hot Water DJ: Saving Energy by Pre-mixing Hot WaterDemand Responsesupply hot water on-demand and only hot enough for device. adds additional sensors to figure out find hot-water events, and temperature needed for those events.00010undeterminedRead, ActuateRead: Water flow sensors, Pressure Sensors.
Actuate: Water Heater
when water event occurs indicated by the pressures sensors.0state change01 (Water Event)01100-1
Buildsys2012Semi-Automated Modular Modeling of Buildings for Model Predictive ControlModel-Predictive Controle standard geometry and construction
data to derive in an automated way a physical first-principles
based linear model of the building’s thermal dynamics. This
describes the evolution of room, wall, floor and ceiling temperatures
on a per zone level as a function of external heat
fluxes (e.g., solar gains, heating/cooling system heat fluxes
etc.). Second, we model the external heat fluxes as linear
functions of control inputs and predictable disturbances.
Third, we tune a limited number of physically meaningful
parameters. Finally, we use model reduction to derive a loworder
model that is suitable for MPC.
000100ReadRead: read vav status, actuate: vav setpointsBuildingManagercontinuously0000011001
Buildsys2012Thermovote: Participatory Sensing for Efficient Building HVAC ConditioningParticipatory Sensingcell-phone based app which tells you whether a user a hot ,cold, etc. Use that feedback in a control strategy to optimize temperature. Actuation done. results on real deployment.100000read, actuateRead: User Feedback, Temperature;
Acutate: Temperature set point, VAVs
Occupantsbased on user feedback0user request01001101
Buildsys2012Toward Adaptive Comfort Management in Office Buildings Using Participatory Sensing for End User Driven ControlParticipatory Sensingcell-phone based participatory sensing. Users give HVAC preferences. No actuation.10000OccupantsReadSensor box (PIR, humidity, light, CO2, sound, magnetic, infrared, and motion)OccupantsContinuously1000011101
Buildsys2013A Scalable Low-Cost Solution to Provide Personalised Home Heating Advice to HouseholdsEnergy ModelUSB temperature logger, placed on top of the thermostat,
in order to build a thermal model of the home and to infer the operational
settings of the heating system
100110readroom tempPassive active monitoring0000011000
Buildsys2013Carrying My Environment with Me: A Participatory-sensing Approach to Enhance Thermal ComfortThermal Comfort Model;participatory sensingcreate model for user using his vote, and create profile. every room he goes to, carry his profile with him ( through phone ) . optimize thermal conditions in that zone based on his profile.100000assume access to occupant's phone for their location and thermal preferecens, BMS control for the corresponding room 0user location00111100
Buildsys2013EnergyTrack : Sensor-Driven Energy Use Analysis SystemEnergy Modelpropose an analysis model for energy usage that
jointly considers occupancy levels and the utility provided by end-loads. Our occupancy estimation algorithm uses
PIR and CO2 sensors, and has a lightweight training requirement
001100readvarious sensorsPassive active monitoring1000011000
Buildsys2013Estimation of building occupancy levels through environmental signals deconvolutionOccupancy DetectionGives exact number of occupants. occupancy estimation problem is formulated as a regularized deconvolution problem, where the estimated occupancy is the input that, when injected into the identified model, best explains the currently measured CO2 levels000110For short period of time access to direct measurements of the true occupancy levels.readvarious parameters: temp, co2, airflow, occPassive active monitoring1000011000
Buildsys2013Exploiting Generalized Additive Models for Diagnosing Abnormal Energy Use in BuildingsFDDUsed models ( building sub-meter power data and time of day modeling ) to figure out anomalies000100readpower meterPassive active monitoring0000011000
Buildsys2013Incentivizing Advanced Load Scheduling in Smart Homesdemand responsewe argue that variable rate pricing plans do not incentivize consumers to adopt advanced load scheduling algorithms. proposes flat-power pricing, which directly incentivizes consumers to flatten
their own demand profile
001100readvarious parameters: power demand, load schedules, renewable generation, batter capacity, etcPassive active monitoring0000011000
Buildsys2013It’s Different: Insights into home energy consumption in IndiaEnergy DisaggregationLocal-store upload architecture for NILM in areas with unreliable electricity and network.
Monitor different physical and non-physical parameter
100000SLSU (Sense Local-store Upload) app assumes access all the physical and non-physical sensors deployed in the home. Cloud Data visualization app assumed access to all sensor streams and inferences. Everybody at home assumed access to data.
(1) READPhysical and Non Physical sensors deployed at home. (1) Users and Cloud Visualization AppPassive active monitoring0000011101
Buildsys2013Non-Intrusive Occupancy Monitoring using Smart MetersOccupancy Detection0 or 1 occupancy. observe that a home’s pattern of electricity usage generally changes when occupants
are present due to their interact with electrical loads. empirically evaluate these interactions by monitoring ground truth occupancy in two homes, then correlating it with changes in statistical
metrics of smart meter data, such as power’s mean and variance, over short intervals. In particular, we use each metric’s maximum value at night as a proxy for its maximum value in an unoccupied home, and then signal occupancy whenever the daytime value exceeds it
000010readpower meterPassive active monitoring0000011000
Buildsys2013Occupancy Detection from Electricity Consumption DataOccupancy Detectionfigures out whether home is occupied or not using high granularity overall energy meter000110readpower meter,
Passive active monitoring0000011000
Buildsys2013Online Learning for Personalized Room-Level Thermal Control: A Multi-Armed Bandit FrameworkThermal Comfort Model;participatory sensingautomatically 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
100000read, writeread thermal comfort, write znt stptevery N mins0user location00111100
Buildsys2013Optimal Personal Comfort Management Using SPOT+Thermal Comfort Model; Occupancy Detection; Model-Predictive ControlSPOT+ system performs predictive control. Specifically, SPOT+ uses the knearest-neighbour algorithm to predict room occupancy and learning-based model predictive control (LBMPC) to predict future room temperature and to compute the optimal sequence of control inputs. T100000read, writeread infrared and znt, write znt stptevery 10 mins0000011100
Buildsys2013Randomized Model Predictive Control for HVAC SystemsModel-Predictive Controlto save HVAC energy consumption.000100assuming occupancy info, and control access to parameters in HVAC such as mass air flow rate, a ventilation system air
temperature, and a radiators mean radiant temperature; no explicit access control
read, actuateread vav status, actaute vav setpointsbuilding managercontinuously0000011000
Buildsys2013Reduce the Number of Sensors: Sensing Acoustic Emissions to Estimate Appliance Energy UsageActivity Recognition;Energy Modela system that
allows to identify the energy demand incurred by a user’s
action based on audio recordings using smartphones. More
precisely, we capture the user’s ambient sounds and applying
suitable filtering steps in order to determine the user’s
current activity. Our results indicate that our system is capable
of detecting 16 typical household activities at an accuracy
of 92%. By annotating the detectable household activities
with information about typical energy consumptions,
extracted from 950 real-world power consumption traces, a
good estimate of the energy intensity of the users’ lifestyles
can be made
000110read occupant's smartphone audioread
occupant's smartphone audio
Passive active monitoring1000011100
Buildsys2013ThermoSense: Occupancy Thermal Based Sensing for HVAC ControlOccupancy-Based Controloccupancy modeling utilizes thermal based sensing and PIR sensors. Estimate number of people in room and optimize HVAC system that way.100100readthermoimage, pirPassive active monitoring0000011000
Buildsys2013ZonePAC: Zonal Power Estimation and Control via HVAC Metering and Occupant FeedbackEnergy Disaggregationestimates the heating, cooling and electrical power
consumption of each zone in a Variable Air Volume (VAV) type system using existing infrastructure sensors installed as part of the Building Management System (BMS). We provide the estimated zone power consumption as feedback to the occupants of the building over the web and on mobile devices along with other thermal comfort related measurements such as temperature and setpoin
10001occupants or other appscentral unit and individual user's room's pointsreadbunch of sensors in existing vavPassive active monitoring0000011100
Buildsys2014BlueSentinel: a first approach using iBeacon for an energy efficient occupancy detection systemOccupancy Detectionuse Apple iBeacons00001building manager to set policies
occupants specifying personal rules
READ, WRITEread occupancy
write so that energy mgmt app can read it
proximity to the BLE sensor000001110
1 (building manager, occupants)
Buildsys2014PresenceSense: Zero-training Algorithm for Individual Presence Detection based on Power MonitoringOccupancy Detection;occupancy identificationuses ultrasonic sensors, acceleration sensors, wifi points and individual power monitoring data , trains semi-supervised learning and detects presense of particular user.000110see summary1000011100
Buildsys2014WattShare: Detailed Energy Apportionment in Shared Living Spaces within Commercial BuildingsEnergy Disaggregationutilizes signal strength values from WiFi scans
and audio signals from the microphone as input data sources from the smartphone, per phase power consumption from the 3–phase smart meter and some metadata that can be easily collected (e.g. type of appliances in each room and distribution of the three electrical phases across different rooms)
to achieve room level energy apportionment. We use WiFi signal strength to estimate the room occupancy while the audio data is used to differentiate between the events occurring across different rooms
100110The app may be able to access individual user's wifi log if targetted for just energy viewing. If it wants to share the result with external apps, it requires the entire building access.READ, WRITEREAD energy meter, wifi signals and mic data from smartphonesindividual users or other appsregular intervals0user location00111100
Buildsys2015A multidimensional continuous contextual lighting control system using Google Glass
Occupancy-Based Control
Control lighting contextually to reduce energy consumption100000Read, ActuateLighting Systems and Google GlassHome occupants Continous monitoring0000001101
Buildsys2015Centralized Management of HVAC Energy in Large Multi-AHU Zones
Occupancy-Based Control
Leverage occupancy traces and HVAC system configuration from large multi-AHU zones to save energy 00010Occupants, Building Managers(1) Read, Write and Actuate
(2) Read
Read HVAC data, Temperature, sensors, system configuration
Write system configuration
Acutate AHUs
(1) Building Managers
(2) Home Occupants
Capture Occupancy traces every 30mins from the READ access devices0000011101
Buildsys2015Cross-Space Building Occupancy Modeling by Contextual Information Based LearningOccupancy Detectionsystematic framework for cross-space occupancy modeling through non-intrusive ambient sensing and relationship learning, by which the model was trained in one space and then applied to other geometrically similar spaces100110READSensor boxes ( Light, Sound, Motion, CO2, Temperature, Humidity, PIR, Switch)Building Managers, OccupantsCapture data every minute1state change01 (door)101
1 (Each User --(has)--> sensors)
Buildsys2015Health Monitoring of Elderly Residents via Disaggregated Smart Meter Data and Log Gaussian Cox ProcessesEnergy Disaggregation;Activity Recognitionuses aggregate electricity data provided by existing and planned deployments of smart meters to monitor the Activities of Daily Living of elderly residents in their own homes, which is used as a proxy to the elderly resident’s health10010Home OccupantsRead Read : Smart MetersHome occupantsContinous monitoring0000111101
Buildsys2015iProgram: Inferring Smart Schedules for Dumb Thermostats
Occupancy-Based Control
Provide smart energy schedules for thermostats by inferring home occupancy from smart meters 100000Read and ActuateAcutate: Thermostat, System Configuration; Read: Smart MetersHome occupantsData from Thermostat and smart meter logged once every minute0010001101
Buildsys2015LocED: Location-aware Energy Disaggregation FrameworkEnergy DisaggregationUsing User's location to perform energy disaggregation of appliances. 000110READ, WRITEelectricity, occupancy and ambient parameters of the household.Home occupantsuser location1user location00101101
Buildsys2015Neural NILM: Deep Neural Networks Applied to Energy DisaggregationEnergy DisaggregationUsing DNNs to find real time energy disagregation from five appliances in a home00001Home occupantREADsmart energy meterHome occupantsContinous monitoring1000011001
Buildsys2015ThermoCoach: Reducing Home Energy Consumption with Personalized Thermostat Recommendations
Occupancy-Based Control
Models Home occupancy patterns to improve thermostat usability 100100Read and ActuateAcutate: Thermostat, System Configuration; Read: BLE, Motion sensor Home occupantsData from Thermostat logged once every minute0state change0
1 (Occupany, User's schedule)
Buildsys2016AURES: A Wide-Band Ultrasonic Occupancy Sensing PlatformOccupancy Detectionwide-band ultrasonic signal into a room and then processes the superposition of the reflections recorded by a microphone for presence detection and one for estimating the number of occupants in a region100000Read, ActuateRead: Ultrasonic Sensors
Write: HVAC
OccupantEvery 10mins0000001001
Buildsys2016Can computers visually quantify human thermal comfort?Thermal Comfort Modelvisually identify human thermal comfort by using digital videos. Uses videos to amplifies subtle changes in the human physiological signals (like blood flow variation) that are associated with thermoregulation00000OccupantRead, ActuateRead: Web Camera
Actuate: HVAC
OccupantCapture video 30 frames a second.0000001100
Buildsys2016Channel State Information Based Human Presence Detection using Non-linear TechniquesOccupancy DetectionUses sub-carrier amplitude variation of CSI to model human presence in a room.10011OccupantReadRead: 20Mhz Wifi channelOccupantEvery 60s1000001001
Buildsys2016MotionSync: Personal Energy Analytics through Motion Tags and Wearable SensingEnergy FootprintingUses the user's wrist motion to detect motion detect user-appliance interaction, which is then integrated with the information available through the smartmeter for accurate energy apportionment10001OccupantsReadUser's smart watch, Motion Tag attached to the appliances and Smart MeterOccupantEvent based. Wrist motion of the hand when in interaction with motion tag enable appliance triggers reading the smart meter data.0state change0
1 (Wrist motion)
1 (motion sensing tag associated with appliance)
1 (User's watch)
Buildsys2016Non-Intrusive Techniques for Establishing Occupancy Related Energy Savings in Commercial Buildings
Occupancy-Based Control
Using occupancy sensors through BMS to perform customized per-zone schedule to increase energy savings10010Occupants and Building ManagersRead, ActuateHVAC Occupancy sensorsOccupants and Building ManagersContinous monitoring0Calendar Schedule00101101
Buildsys2016Nonintrusive Occupant Identification by Sensing Body Shape and MovementOccupancy Identificationa system that identifies occupants by combining computed girth with the time they spend walking under the door100000ReadUltrasonic sensors Home occupantsPeriodic polling every 29ms 0000001000
Buildsys2016SPOCK: A Sensor Value Prediction and Online Control Algorithm for Building Resource ManagementModel-Predictive ControlUses raw historical sensors reading to predict future readings and perform control actions based on predictions. Used the method to make control decisions for a water softener
on the basis of our sensor forecasts.
000100Read, ActuateRead: Water Quality Sensor, Softner controller
Write: Water Softner
SystemEvery minute000001100-1
Buildsys2016The SPOT* Personal Thermal Comfort System
Occupancy-Based Control
Personal Environment control system that is easily deployable. Uses PIR, Kinect to detect the occupancy.100000Read, ActuateRead:PIR sensor, Kinect, Temperature Sensor; Actuate:HVACOccupantsevery 30 read the sensors1state change01 (Occupany)011101
Buildsys2016WalkSense: Classifying Home Occupancy States Using Walkway SensingOccupancy Detectionuse motion sensors to detect occupancy in the walkways between zones, such as hallways, foyers, or doorways for Occupancy sensing in zones.000110ReadRead: PIR SensorsOccupant0000001101
Buildsys2017Efficient probabilistic model checking of smart building maintenance using fault maintenance treesFDDa method that builds a Fault Maintenance Tree based on maintenance and degradation models of HVAC, to detect faults00010building managerreadhvac maintenance log and degradation status data1000011000
Buildsys2017ePrints: a real-time and scalable system for fair apportionment and tracking of personal energy footprints in commercial buildingsenergy footprintinginstalled BLE to localize people at room/cubile level; instrumented power meters at each outlet; users can access their energy consumpition data on a central server via phone100110readvarious types of sensor data
wireless power meters, indirect sensing nodes and BACnet monitors
continuous monitoring0device state,
occupant location
1(appliance use,
occupant location changes)
Buildsys2017Estimation of physical buildings parameters using interval thermostat dataEnvironment Modelestimate the overall building insulation level, HVAC system efficiency, and building airtightness from the communicating thermostat data, in order to predict indoor temperature and energy consumption 000100read indoor temp, heating system status0000011000
Buildsys2017Exploring fairness in participatory thermal comfort control in smart buildingsParticipatory Sensinga method to ensure thermal fairness and do HVAC control based on it100100assume user thermal preference is given, no explicit discussion on how to get itread, actuateread user thermal preference, actuate AC0000001100
Buildsys2017Incentive design for demand-response based on building constraints: a utility perspectiveDemand Responsepredicts demand-response savings regarding DR incentives, based on data like temperature, AHU and chiller power001100readrun as wished000-1001000
Buildsys2017Indoor environmental quality monitoring by autonomous mobile sensingEnvironment Modela robot provides sparse samples and interpolate for indoor env quality, e.g., co2, pm2.500010building managerreadvarious types of sensor data0000011000
Buildsys2017Inverting HVAC for energy efficient thermal comfort in populous emerging countriesOccupancy-Based Controlinstrumented AC units and run a central control algo to control on/off of each AC000100read sensor data, actuate AC0000011000
Buildsys2017Longitudinal Energy Waste Detection with VisualizationFDDused IR+low-res camera to detect temperature extremas and compare with znt stpt10010building owner?readcamera outpout; znt stptcontinuous monitoring0000001000
Buildsys2017Sensetribute: smart home occupant identification via fusion across on-object sensing devicesOccupancy Identificationsupervised classificaition using IMU sensors on objects (fridge, window, etc)100100readimu sensor datacontinuous monitoring0000011000
Buildsys2017Sonicdoor: scaling person identification with ultrasonic sensors by novel modeling of shape, behavior and walking patternsOccupancy Identificationinstrumented each door with 3 ultrasonic sensors to identify occupants000110readultrasonic sensor data on doorcontinuous monitoring0000001000
Buildsys2017Towards integration of doppler radar sensors into personalized thermoregulation-based control of HVACThermal Comfort Model;Occupancy-Based Controluse Doppler radar sensors to monitor occupant's respiration rate, as an indicator to control HVAC000100read, actuateread doppler radar sensor, actutate AC0000001100
Buildsys2017Using simple predictive models to improve control of complex building systemsModel-Predictive Controlpull bacnet device data via volttron to learn a simple predictive model and control HVAC000100read device data, write control parametervarious kinds of bacnet devicesdecide the control as wished0000011000
Buildsys2018Good set-points make good neighbors: user seating and temperature control in uberized workspaces
Occupancy-Based Control;Space Management
00010space managerreaduser thermal preference1000011110
Buildsys2018Inferring occupant ties: automated inference of occupant network structure in commercial buildingsBehavior Modelinguse plug load energy consumption sensor data to infer the relationships between occupants, which help understand how people utilize the space and thus enables contextual control00011owner?read plug load energy consumption sensors0000001111
Buildsys2018Practical implementation and evaluation of deep reinforcement learning control for a radiant heating systemModel-Predictive ControlRL for HVAC control100110read, writeread indoor air temperature, air temperature setpoint, occupancy
status, heating demand; write suppply water temp stpt
every 5 mins0000011000
Buildsys2018Rimor: towards identifying anomalous appliances in buildingsFDDuse appliance level power meter data to detect anomaly by 1) learning a historical model and 2) flagging significant deviations000100readpower meter 0000011000
Buildsys2018Shopping intent recognition and location prediction from cyber-physical activities via wi-fi logsBehavior Modelinguse wifi access and browsing logs to learn the correlation between users' activities and physical context. which helps predict user's future location00010retailer/advertising companyreadconnection logs and user queries from wifi appassive continuous monitoring0000011100
Buildsys2018Smart lighting control using oblivious mobile sensorsOccupancy-Based Controlsense luminosity from smartphones and control smart light bulbs based on preference100100read, actuate0user location00111101
E-Energy2010Managing End-User Preferences in the Smart GridDemand responseHave utility function for each device. On a demand-response event, apply optimization function and utility functions to decide power level of devices101100read occupants feedback and control the buildingREAD
DR event0dr event0dr001100
E-energy2010Policy-Driven Distributed and Collaborative Demand Response in Multi-Domain Commercial BuildingsDemand responseelectrical devices communicate among themselves to organize autonomously into appropriate organizational control groups (possibly hierarchical), and negotiate among themselves the most appropriate form of collective DR adaptation.001100any eletrical controllerREAD, WRITE, ACTUATEREAD (to communicate and negotiate DR)
WRITE (to central EMS in the alternative model)
ACTUATE (to turn off equipments based on needs)
DR event0dr event01 (DR)01100
1 (only admin entity can define DR behaviour )
E-Energy2010Profiling Energy Use in Households and Office SpacesEnergy Disaggregationlocal and remote storage of data collected from power meter sensors. Analysis on how much energy can be saved in each house10011building manager or other apps.
Individual users may receive energy feedback based on the result
Need to access the whole meter and individual appliances for calculating occupants individual energy useREADREAD clamp sensors (meters and fuse boards)every 6 seconds0000001000
E-Energy2011EnergyPULSE: Tracking Sustainable Behavior in Office EnvironmentsEnergy FootprintingPIR sensors for occupancy, track light (LDR sensor) and power usage (smart power meter) for each individual office10010READREAD various sensors: pir, light, power, magnetic, temp for radiatorPassive Continuos Monitoring0000011100
E-Energy2012nPlug: A Smart Plug for Alleviating Peak LoadsDemand ResponsenPlug, a smart plug that sits between
the wall socket and deferrable loads such as water
heaters, washing machines, and electric vehicles. nPlugs combine real-time sensing and analytics to infer peak periods as well as supply-demand imbalance and reschedule attached appliances in a decentralized manner to alleviate peaks whenever possible
00110OccupantsREAD, WRITE, ACTUATEREAD (Voltage line and frequency)
WRITE (Store PAA data and user preferences),
ACTUATE (run equipment at desired time for desired duration)
Regular intervals30 mins between 4 AM to 7 AM temporal?calendar schedule10011000
E-Energy2012SmartCharge: cutting the electricity bill in smart homes with energy storageDemand Responsean on-site battery array to store low-cost energy for use during high-cost periods. SmartCharge's algorithm reduces electricity costs by determining when to switch the home's power supply between the grid and the battery array. The algorithm leverages a prediction model we develop, which forecasts future demand using statistical machine learning techniques100000READ, ACTUATEREAD (energy/voltage sensors),
ACTUATE (switch between battery and live power)
Occupantswhen electricity prices go from low-cost periods to high-cost or vice versa000 (have to grant access for 24 hour as it uses its own forcasting algorithm to switch)0
0 (app uses location but for weather forecast, etc | not for access control)