Abstract: A method for dispatching buildings in a demand response program event including generating data sets for each of the buildings, each set having energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each set are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a non-linear parabolic analysis on each set to yield non-linear parabolic model parameters and a residual; determining a least valued residual from all residuals yielded, the least valued residual indicating a corresponding energy lag for the each of the buildings; and using energy lags for all of the buildings to generate a dispatch schedule for the demand response program event according to a prioritization of the energy lags.

Abstract: A method for characterizing buildings, including retrieving a plurality of baseline energy use data sets for the buildings from a baseline data stores; generating energy use data sets for each of the buildings, each of the energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each of the sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a non-linear parabolic analysis on the each of the plurality of energy use data sets to yield corresponding non-linear parabolic model parameters and a corresponding residual; determining a least valued residual from all residuals, the least valued residual indicating a corresponding energy lag for the each of the buildings; and categorizing the buildings into types according to simila

Abstract: A method for characterizing buildings, including retrieving a plurality of baseline energy use data sets for the buildings from a baseline data stores; generating energy use data sets for each of the buildings, each of the energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each of the sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a non-linear parabolic analysis on the each of the plurality of energy use data sets to yield corresponding non-linear parabolic model parameters and a corresponding residual; determining a least valued residual from all residuals yielded by the regression engine, the least valued residual indicating a corresponding energy lag for the each of the buildings; and categorizing the buildin

Abstract: A method for characterizing buildings, including retrieving a plurality of baseline energy use data sets for the buildings from a baseline data stores; generating energy use data sets for each of the buildings, each of the energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each of the sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a machine learning model analysis on the each of the plurality of energy use data sets to yield corresponding machine learning model parameters and a corresponding residual; determining a least valued residual from all residuals, the least valued residual indicating a corresponding energy lag for the each of the buildings; and categorizing the buildings into types according to similar

Abstract: An apparatus for managing energy consumption of one or more buildings of one or more building types based on occupancy is provided. The apparatus includes an occupancy estimator and a multiple facility controller. The occupancy estimator is configured to receive energy consumption and outside temperature streams corresponding to a portion of the one or more buildings, and is configured to employ occupancy components for each of the one or more buildings within the portion to process the streams, and is configured to generate occupancy levels corresponding to the one or more buildings within the portion, where the occupancy components and the occupancy levels are generated by exclusively processing the streams, and is configured to assign the occupancy levels to remaining ones of the one or more buildings not in the first portion according to building type.

Abstract: A method for prioritizing a demand response program event based on occupancy for one or more buildings of one or more building types participating in a demand response program, the method comprising: receiving energy consumption and outside temperature streams Ei(h,T) corresponding to a portion of the one or more buildings, and receiving and employing occupancy components for each of the one or more buildings within the portion to process the streams, and generating occupancy levels corresponding to the one or more buildings within the portion, and assigning the occupancy levels to remaining ones of the one or more buildings not in the portion; and optimizing execution of the demand response program event by employing the occupancy components to prioritize dispatch messages to the one or more buildings to achieve objectives of the demand response program event.

Abstract: A method for prioritizing a demand response program event based on occupancy for one or more buildings of one or more building types participating in a demand response program, the method comprising: receiving energy consumption and outside temperature streams Ei(h, T) corresponding to a portion of the one or more buildings, the energy consumption provided by streaming consumption sources, and receiving and employing occupancy components for each of the one or more buildings within the portion to process the streams, and generating occupancy levels corresponding to the one or more buildings within the portion, and assigning the occupancy levels to remaining ones of the one or more buildings not in the portion; and optimizing execution of the demand response program event by employing the occupancy components to prioritize dispatch messages to the one or more buildings to achieve objectives of the demand response program event.

Abstract: A method for dispatching buildings, including: generating data sets, each having energy values along with corresponding time and outside temperature values, where the energy values are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values; performing a machine learning model analysis on the each of the data sets; determining a least valued residual that indicates a corresponding energy lag for each of the buildings, the corresponding energy lag describes a transient energy consumption period preceding a change in outside temperature; using outside temperatures, model parameters, and energy lags for all of the buildings to estimate a cumulative energy consumption for the buildings, and to predict a dispatch order reception time for the demand response program event; and employing the dispatch order reception time to prepare actions required to control the each of the buildings to optimally shed energy specified in a dispatch order.

Abstract: A computer-implemented method for labeling images includes capturing, using an augmented-reality enabled device, a first set of images that include views of a first object; at the augmented-reality enabled device, for each of the first set of images, identifying the first object and generating a bounding box that is associated with the first object; receiving an input providing a first label for the first object; and at the augmented-reality enabled device, for each of at least some of the first set of images, associating the first label with the first object bound by the bounding box.

Abstract: A system for enabling spot cleaning includes a mobile computing device and a mobile cleaning robot. The mobile computing device includes at least one camera configured to capture images of an environment, and at least one data processor configured to (a) establish, based at least in part on first information provided by the at least one image sensor, a coordinate system in the environment, (b) determine, based at least in part on second information provided by the at least one camera, a first set of coordinates of a region at a first location, (c) determine, based at least in part on third information provided by the at least one camera, a second set of coordinates of a mobile cleaning robot at a second location, (d) send the first set of coordinates and second set of coordinates, or coordinates of the first location relative to the second location, to the mobile cleaning robot, and (e) send an instruction to the mobile cleaning robot to request the mobile cleaning robot to travel to the first location.

Abstract: An apparatus for prioritizing a demand response program event based on occupancy for one or more buildings of one or more building types participating in a demand response program is provided. The apparatus has an occupancy estimator and a dispatch controller. The occupancy estimator is configured to receive energy consumption and outside temperature streams corresponding to a portion of the one or more buildings, and is configured to employ occupancy components for each of the one or more buildings within the portion to process the streams, and is configured to generate occupancy levels corresponding to the one or more buildings within the portion, where the occupancy components and the occupancy levels are generated by exclusively processing the streams, and is configured to assign the occupancy levels to remaining ones of the one or more buildings not in the first portion.

Abstract: An occupancy-based traffic control system for augmenting traffic control mechanisms corresponding to buildings of one or more building types within a geographic subsector is provided. The system includes, a subsector aggregator, an other facility occupancy estimator, and a subsector processor. The subsector aggregator receives energy consumption and outside temperature streams corresponding to a portion of the buildings, and employs occupancy components to generate average occupancy components corresponding to each building type. The other facility occupancy estimator matches the average occupancy components to remaining ones of the buildings not in the first portion according to building type. The subsector processor uses the first and second aggregated occupancy components modify defaults of traffic control devices based on the occupancy estimate to optimize flow of pedestrians.

Abstract: An occupancy-based traffic control system for augmenting traffic control mechanisms corresponding to buildings of one or more building types within a geographic subsector is provided. The system includes, a subsector aggregator, an other facility occupancy estimator, and a subsector processor. The subsector aggregator receives energy consumption and outside temperature streams corresponding to a portion of the buildings, and employs occupancy components to generate average occupancy components corresponding to each building type. The other facility occupancy estimator matches the average occupancy components to remaining ones of the buildings not in the first portion according to building type. The subsector processor uses the first and second aggregated occupancy components modify defaults of traffic control devices based on the occupancy estimate to optimize flow of automotive vehicles.

Abstract: An apparatus for controlling consumption of a resource by a facility includes devices, a network operations center (NOC), and control nodes. The devices each consume a portion of the resource and perform a function. The NOC generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An apparatus for controlling consumption of a resource by a facility includes devices, an occupancy determination system, and control nodes. The devices each consume a portion of the resource and perform a function. The occupancy determination system is disposed in a network operations center that is external to the facility and generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An apparatus for controlling consumption of a resource by a facility includes devices, an occupancy determination system, control nodes, and monitor nodes. The devices each consume a portion of the resource and perform a function. The occupancy determination system is disposed in a network operations center that is external to the facility and generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An apparatus for controlling facility resource consumption includes devices, a network operations center (NOC), and control nodes. The devices each consume a portion of the resource and perform a function. The NOC generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An occupancy based traffic control system for augmenting traffic control mechanisms corresponding to one or more buildings of one or more building types within a geographic subsector is provided. The system includes, a subsector aggregator, an other facility occupancy estimator, and a subsector processor. The subsector aggregator receives energy consumption and outside temperature streams corresponding to a portion of the one or more buildings, and employs occupancy components to generate average occupancy components corresponding to each building type. The other facility occupancy estimator matches the average occupancy components to remaining ones of the one or more buildings not in the first portion according to building type. The subsector processor uses the first and second aggregated occupancy components modify defaults of traffic control devices based on the occupancy estimate to optimize flow of pedestrians and automotive vehicles.

Abstract: An apparatus for controlling consumption of an energy resource includes devices, a network operations center (NOC), and control nodes. The devices are within the facility. The NOC is external to the facility, and generates run time schedules that coordinate run times for the each of the devices to control consumption while maintaining local environments and desired level of performance, and adjusts the run time schedules based upon resource utilization levels generated by the NOC, where the resource utilization levels are exclusively generated based on the consumption of the energy resource and outside temperature. The control nodes are coupled together via an energy management network that is operatively coupled to the NOC, and transmit sensor data and device status to the NOC for generation of the run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An apparatus for controlling consumption of a resource includes devices, a network operations center (NOC), and control nodes. The devices are within the facility. The NOC is external to the facility, and generates run time schedules that coordinate run times for each of the devices to control consumption while maintaining local environments, and adjusts the schedules based upon occupancy levels generated by the NOC, where the levels are exclusively generated based on the consumption of the resource and outside temperature. The control are coupled together via an energy management network that is operatively coupled to the NOC, and transmit sensor data and device status to the NOC for generation of the plurality of run time schedules. The nodes execute selected ones of the run time schedules to cycle the devices on and off.