System and method of environmental monitoring. In an embodiment, a remote monitoring device comprises power-consuming components comprising at least one sensor and a radio interface component, and a power source comprising a battery and a solar panel. The device stores mode information on operating modes defining differing levels of sensing capabilities and have different power consumption profiles. The device accumulates energy information regarding solar energy collected by the solar panel over a prior time period, obtains environmental information over a future time period, calculates estimated battery capacity data of the battery for the future time period based on the energy information and environmental information, calculates estimated operating times of the device when operating in the operating modes during the future time period based on the estimated battery capacity data and power consumption profiles, and selects between the operating modes during the future time period using the estimated operating times.

The control system includes an electrical meter and a processor. The electrical meter may be configured to monitor the current draw of the electrical system. The processor is communicatively coupled to the electrical meter. The processor also includes an optimization algorithm. The processor may accept input information about the electrical system, such as an electrical capacity of the electrical system, a performance limit of the electrical system, and building electrical usage characteristics. The processor performs the optimization algorithm and outputs a control protocol of a first appliance and a second appliance to maintain the current draw below the predetermined amperage.

A load control environment may be controlled by adjusting load control devices, such as a lighting intensity level, a level of the covering material for a motorized window treatment, and/or a temperature level to reduce and/or optimize the consumption of power. The optimization of power may include reducing the total cost and consumption of power, while maintaining a target or minimum level of comfort for occupants and/or a net monetary gain. The optimization of power consumption may be performed by adaptively controlling the load control devices to reduce the total power consumption of the load control environment, while maintaining a minimum level for comfort metrics indicating a level of occupant comfort and/or the net monetary gain associated with the comfort metrics.

The system may have an energy load data interface to receive energy load data originating from energy use sensors for the building; a weather data interface to receive weather data for a location that includes the building; a weather adjustment pre-processor to process the energy load data and the weather data and to determine a weather-dependent energy use component of the energy load data and a weather-independent energy use component of the energy load data; a baseline adjustment pre-processor to process the weather-independent energy use component of the energy load data and determine a baseline energy use component of the energy load data, wherein the baseline adjustment pre-processor is configured to remove the baseline energy use component from the weather-independent energy use component to determine a variable energy use component of the energy load data; and an energy use disaggregator to process the variable energy use component of the energy load data and determine a plurality of time varying load components of the energy load data.

Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. Power consumption of power-drawing devices (e.g., hosts, servers, etc.) may be monitored with respect to a power threshold. When the current power consumption corresponding to those devices breaches the power threshold, or at any suitable time, the system may identify a set of reduction actions configured to reduce aggregate power consumption. The power threshold may be updated dynamically based on the operational status of related systems and environmental factors. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

A computer-implemented method, performed by a first node (101). The method is for determining a source of power. The first node (111) operates in a communications system (100). The first node (111) obtains (301) information about a first passive equipment power source (121), a second passive equipment power source (122) and an active power source (123) of a network node (110). The first node (111) then determines (302), using machine learning and the obtained information, a source of power to be used by the network node (110) at a future time period, out of the first passive equipment power source (121) and the second passive equipment power source (122). The determining (306) is based on an estimated cost of the power, and an estimated load at the power source during the time period. The first node (111) also provides (306) a first indication indicating the determined source of power to at least one of the network node (110) and a second node (102) operating in the communications system (100).

Systems and techniques may generally be used to individually and selectively enable or disable a plurality of power channels based on detection of activity (or lack thereof) on a workstation. An example system may include a medical cart battery and a power channel for connecting peripheral devices. The system may incorporate an inertial measurement unit (IMU) sensor interface for monitoring cart functions. The system may include a controller in communication with the sensor interface and battery to determine if connected peripheral devices should be powered off based on IMU sensor data. The controller may generate power control instructions which may be executed by a power switch that enables or disables the power channel accordingly. The system may provide automated power management for peripheral devices based on cart movement and usage conditions detected by the IMU sensor.

Methods and systems describe multicasting the messages over a broadcast medium (e.g., a TV network). In particular, the methods and systems recite the use of Advanced Television Systems Committee (ATSC) 3.0, a new broadcast television transmission standard in the United States. Using ATSC 3.0, the methods and systems can disseminate messages to all the electrical equipment.