A distributed, parallel, image capture and processing architecture provides significant advantages over prior art systems. A very large array of computational circuits—in some embodiments, matching the size of the pixel array—is distributed around, within, or beneath the pixel array of an image sensor. Each computational circuit is dedicated to, and in some embodiments is physically proximal to, one, two, or more associated pixels. Each computational circuit is operative to perform computations on one, two, or more pixel values generated by its associated pixels. The computational circuits all perform the same operation(s), in parallel. In this manner, a very large number of pixel-level operations are performed in parallel, physically and electrically near the pixels. This obviates the need to transfer very large amounts of pixel data from a pixel array to a CPU/memory, for at least many pixel-level image processing operations, thus alleviating the significant high-speed performance constraints placed on modern image sensors.

A power management system obtains first data regarding several groups of electrical devices, including a budget and a respective priority metric associated with each of the groups. The system allots a respective amount of electrical power for use by each of the groups based on the first data. Further, the system obtains second data regarding the groups, including a respective amount of electrical power consumed by each of the groups. The system determines that a first group has consumed a first amount of electrical power that is greater than or equal to a second amount of electrical power that had been allotted for use by the first group. In response, the system re-allots at least a portion of a third amount of electrical power that had been allotted for use by a second group for use by the first group instead.

A power management system obtains first data regarding several groups of electrical devices, including a budget and a respective priority metric associated with each of the groups. The system allots a respective amount of electrical power for use by each of the groups based on the first data. Further, the system obtains second data regarding the groups, including a respective amount of electrical power consumed by each of the groups. The system determines that a first group has consumed a first amount of electrical power that is greater than or equal to a second amount of electrical power that had been allotted for use by the first group. In response, the system re-allots at least a portion of a third amount of electrical power that had been allotted for use by a second group for use by the first group instead.

Disclosed herein is a method and system for sharing power or energy across various power supply and control modules. More specifically, disclosed herein are systems and methods for distributing energy. As explained herein, the method discloses receiving, at a microgrid, data from a plurality of data sources. The data is then analyzed to forecast power needs associated with the microgrid. Using the data, the microgrid may determine whether and when to share power with the requesting module.

Disclosed herein is a method and system for sharing power or energy across various power supply and control modules. More specifically, disclosed herein are systems and methods for distributing energy. As explained herein, the method discloses receiving, at a microgrid, data from a plurality of data sources. The data is then analyzed to forecast power needs associated with the microgrid. Using the data, the microgrid may determine whether and when to share power with the requesting module.

An information processing apparatus incudes a schedule determination unit configured to determine a schedule of an operating status for causing a temperature of an air-conditioned space of each of a plurality of load-side units to reach a specified set temperature at a specified set time, based on a learning model representing an input-output relationship between input data indicating an influencing factor of a thermal load of each of the load-side units and output data indicating the thermal load.

Provided are a method and apparatus for dynamically controlling electrical loads, a storage medium and an electronic apparatus. The method includes that: a current capacity balance of a user sub-region is acquired from an intelligent electricity monitoring and metering terminal through a mobile terminal; when the current capacity balance is smaller than a load power of an electric consumption device to be started in the user sub-region, a regional coordination control apparatus or a server is requested through the mobile terminal to adjust and increase a capacity allocated for the user sub-region, such that a capacity balance will be greater than or equal to the load power; and whether to allow to start the electric consumption device is determined according to a decision replied by the regional coordination control apparatus or the server.

Provided are a method and apparatus for dynamically controlling electrical loads, a storage medium and an electronic apparatus. The method includes that: a current capacity balance of a user sub-region is acquired from an intelligent electricity monitoring and metering terminal through a mobile terminal; when the current capacity balance is smaller than a load power of an electric consumption device to be started in the user sub-region, a regional coordination control apparatus or a server is requested through the mobile terminal to adjust and increase a capacity allocated for the user sub-region, such that a capacity balance will be greater than or equal to the load power; and whether to allow to start the electric consumption device is determined according to a decision replied by the regional coordination control apparatus or the server.

A hierarchical resource management system for a building includes one or more processors. The processors implement a plurality of agents that each monitor sensed values, and generate operating scenarios based on the sensed values for corresponding resources. The processors also implement a coordinator that filters the operating scenarios to remove the operating scenarios that violate internal laws of the agents to form an aggregate validated set of operating scenarios. The processors further implement a supervisor that, responsive to receipt of target conditions for the zones and the aggregate validated set of operating scenarios from the coordinator, selects a combination of the operating scenarios from the aggregate validated set of operating scenarios that achieves target conditions and minimizes overall energy consumption by the resources such that some of the operating scenarios of the combination do not minimize energy consumption of the resources corresponding to the some of the operating scenarios.

Sub-systems of air handling units in infrastructures face unresolved problem of conflict in the rules that activate in a contradictory manner at the same time resulting in sub-optimal performance of the subsystems. The present disclosure provides a system and method for optimizing performance parameters of air handling units in infrastructures. Rule sets having conflicting conditions are identified after verification of rules which are specific to air handling units. Further, frequency of the rule sets having conflicting conditions is determined to generate a ranked list of the rule sets having conflicting conditions. Another ranking procedure is implemented for the rules comprised in the ranked list of the rule sets having conflicting conditions. The system dynamically optimizes one or more parameters specific to the performance criteria based on the ranking of rules.