Embodiments relate to a closed loop communication system. The system can include a consumer mobile device configured with a mobile application to identify its load consumption pattern and communicate the identified load consumption pattern to a utility device. The mobile device also sets a limit for maximum energy consumption through the mobile application. The system can also include the utility device that receives the identified load consumption pattern, and configured to send a short message service (SMS) alert to the mobile device to alert the mobile device to read meter energy consumption reading from energy meter and share with utility device due to direct connection failure with an energy meter. The system can also include an energy meter configured to communicate with the utility device, wherein the utility device attempts to receive the meter energy consumption reading from the energy meter.

A system for discovering the topology and phase of an electrical power distribution system is provided. For example, a group of meters connected to an electrical power distribution system can process sensor data obtained at the meters and generate descriptors based on the processed data and transmit the descriptors to a headend system. The headend system can, after receiving the descriptors from the various meters in the system, group these meters to generate a grouping by applying clustering algorithms to the descriptors of these meters. The headend system can further compare the current grouping with past groupings to determine a confidence level of the current grouping and assign a segment identifier or a phase identifier or both to one or more of the meters based on the confidence level.

An implementation of a utility meter is connected to a resource and to a customer premises. The utility meter includes a sensor, a converter, and a radio. The sensor is configured to detect a characteristic of resource usage by the customer premises. The converter is configured to convert the characteristic to raw consumption data describing the resource usage. The radio is configured to transmit the raw consumption data output by the converter to a remote processing system. The remote processing system includes one or both of a fog and a cloud. The fog is associated with a geographic region of the utility meter and performs data processing on the raw consumption data and on regional raw consumption data received from other endpoints in the geographic region. The cloud performs data processing on the raw consumption data as well as on data received from other endpoints across various geographic regions.

Embodiments relate to a closed loop communication system. The system can include a consumer mobile device configured with a mobile application to identify its load consumption pattern and communicate the identified load consumption pattern to a utility device. The mobile device also sets a limit for maximum energy consumption through the mobile application. The system can also include the utility device that receives the identified load consumption pattern, and configured to send a short message service (SMS) alert to the mobile device to alert the mobile device to read meter energy consumption reading from energy meter and share with utility device due to direct connection failure with an energy meter. The system can also include an energy meter configured to communicate with the utility device, wherein the utility device attempts to receive the meter energy consumption reading from the energy meter.

A system for discovering the topology and phase of an electrical power distribution system is provided. For example, a group of meters connected to an electrical power distribution system can process sensor data obtained at the meters and generate descriptors based on the processed data and transmit the descriptors to a headend system. The headend system can, after receiving the descriptors from the various meters in the system, group these meters to generate a grouping by applying clustering algorithms to the descriptors of these meters. The headend system can further compare the current grouping with past groupings to determine a confidence level of the current grouping and assign a segment identifier or a phase identifier or both to one or more of the meters based on the confidence level.

A system for discovering the topology and phase of an electrical power distribution system is provided. For example, a group of meters connected to an electrical power distribution system can process sensor data obtained at the meters and generate descriptors based on the processed data and transmit the descriptors to a headend system. The headend system can, after receiving the descriptors from the various meters in the system, group these meters to generate a grouping by applying clustering algorithms to the descriptors of these meters. The headend system can further compare the current grouping with past groupings to determine a confidence level of the current grouping and assign a segment identifier or a phase identifier or both to one or more of the meters based on the confidence level.

This present disclosure presents a method for metering the amount of tap water usage, while a tap water metering device including multiple measuring sensors is supplied with power through a constant power source, including a step of the tap water metering device receiving tap water from a distribution pipe, a step of the tap water metering device metering the amount of tap water delivered to each of multiple households through a meter in the process of delivering the received tap water to multiple households, and a step of the tap water metering device transmitting the data of multiple meter readings obtained from the multiple meters to the analysis server via telecommunication.

A system for discovering the topology and phase of an electrical power distribution system is provided. For example, a group of meters connected to an electrical power distribution system can process sensor data obtained at the meters and generate descriptors based on the processed data and transmit the descriptors to a headend system. The headend system can, after receiving the descriptors from the various meters in the system, group these meters to generate a grouping by applying clustering algorithms to the descriptors of these meters. The headend system can further compare the current grouping with past groupings to determine a confidence level of the current grouping and assign a segment identifier or a phase identifier or both to one or more of the meters based on the confidence level.

Provided is a controller of a smart meter that includes a processor incorporating a debugging module configured to stop execution of instructions when a stop point is reached and to generate an associated hardware interrupt. For applying a correction to a set of instructions, the controller: receives a new-correction message that supplies the correction to be applied and a point of stopping application of the correction in the set of instructions executed by the controller; records correction instructions in non-volatile memory for future restarting of the smart meter, and in random access memory for the purpose of taking into account without restarting the smart meter; configures the debugging module with the point of stopping application of the correction; and applies on the fly the correction instructions of which are recorded in random access memory, when detecting a hardware interrupt associated with the point of stopping application of the correction.

Provided is a controller of a smart meter that includes a processor incorporating a debugging module configured to stop execution of instructions when a stop point is reached and to generate an associated hardware interrupt. For applying a correction to a set of instructions, the controller: receives a new-correction message that supplies the correction to be applied and a point of stopping application of the correction in the set of instructions executed by the controller; records correction instructions in non-volatile memory for future restarting of the smart meter, and in random access memory for the purpose of taking into account without restarting the smart meter; configures the debugging module with the point of stopping application of the correction; and applies on the fly the correction instructions of which are recorded in random access memory, when detecting a hardware interrupt associated with the point of stopping application of the correction.