An energy management system of the present invention can measure and integrate a power consumption amount of each device, can integrate and monitor regional total power consumption amounts, and allows energy to be effectively used by collecting, analyzing, storing and transmitting a use pattern and data through the Internet of Things (IoT) between devices and completely and automatically cutting off and controlling the power to be wasted in a device when the device is not used. The energy management system remotely controls devices and allows energy to be effectively managed through the minimization of power consumption by automatically and completely cutting off the power to be supplied to the devices when the devices are not used, and by cutting off the power to be supplied to the system when the power of all the devices connected to the system is cut off and when the system is in standby.

A method, a device, and a non-transitory storage medium to receive from customer devices, sensor messages indicating a power state of on or off, a location, and a timestamp; select an element of a utility system based on the sensor messages; determine a power state of on or off for the element based on the sensor messages and a location and time pertaining to the element; store a temporal and spatial model that includes an outage event; receive weather data pertaining to the element; generate an outage model based on the temporal and spatial model and the weather data; receive forecasted weather data; calculate a predicted outage pertaining to one or more elements of the utility system based on the outage model and the forecasted weather data; and transmit a message that includes the predicted outage.

The present disclosure provides methods, Internet of Things (IoT) systems, and mediums for correcting a smart gas flow. The method may be implemented by a smart gas device management platform of an IoT system for correcting a smart gas flow. The method may include: obtaining reading data of a gas meter; determining a first confidence level of the reading data based on the reading data; in response to a determination that the first confidence level is smaller than a confidence level threshold, obtaining a working condition parameter; and determining, based on the working condition parameter, a gas meter correction mode.

The present disclosure provides methods, Internet of Things (IoT) systems, and mediums for correcting a smart gas flow. The method may be implemented by a smart gas device management platform of an IoT system for correcting a smart gas flow. The method may include: obtaining reading data of a gas meter; determining a first confidence level of the reading data based on the reading data; in response to a determination that the first confidence level is smaller than a confidence level threshold, obtaining a working condition parameter; and determining, based on the working condition parameter, a gas meter correction mode.

The embodiments of the present disclosure provide method and Internet of Things (IoT) systems for predicting maintenance materials of a smart gas pipeline network. The method may be implemented based on a smart gas safety management platform of an Internet of Things (IoT) system for predicting maintenance materials of a smart gas pipeline network. The method may comprise: obtaining a pipeline network feature of a gas pipeline network; predicting fault probabilities of one or more point positions of the gas pipeline network based on the pipeline network feature, the fault probabilities including probabilities of one or more preset fault types of faults occurring at the point positions; and determining demand for the maintenance materials based on the fault probabilities of the one or more point positions.

The embodiments of the present disclosure provide method and Internet of Things (IoT) systems for predicting maintenance materials of a smart gas pipeline network. The method may be implemented based on a smart gas safety management platform of an Internet of Things (IoT) system for predicting maintenance materials of a smart gas pipeline network. The method may comprise: obtaining a pipeline network feature of a gas pipeline network; predicting fault probabilities of one or more point positions of the gas pipeline network based on the pipeline network feature, the fault probabilities including probabilities of one or more preset fault types of faults occurring at the point positions; and determining demand for the maintenance materials based on the fault probabilities of the one or more point positions.

The present disclosure provides methods and Internet of Things (IoT) systems for gas repair-reporting management based on a call center of smart gas. The method includes obtaining historical gas use data and historical gas repair-reporting data; generating, based on the historical gas use data and the historical gas repair-reporting data, first gas repair-reporting areas; generating, at least based on the historical gas use data and the historical gas repair-reporting data of the first gas repair-reporting areas, future gas repair-reporting data of the first gas repair-reporting areas; generating, based on the first gas repair-reporting areas and the future gas repair-reporting data of the first gas repair-reporting areas, second gas repair-reporting areas and future gas repair-reporting data corresponding to the second gas repair-reporting areas; and generating, based on the future gas repair-reporting data of the second gas repair-reporting areas, a maintenance personnel arrangement plan.

The present disclosure provides methods and Internet of Things (IoT) systems for gas repair-reporting management based on a call center of smart gas. The method includes obtaining historical gas use data and historical gas repair-reporting data; generating, based on the historical gas use data and the historical gas repair-reporting data, first gas repair-reporting areas; generating, at least based on the historical gas use data and the historical gas repair-reporting data of the first gas repair-reporting areas, future gas repair-reporting data of the first gas repair-reporting areas; generating, based on the first gas repair-reporting areas and the future gas repair-reporting data of the first gas repair-reporting areas, second gas repair-reporting areas and future gas repair-reporting data corresponding to the second gas repair-reporting areas; and generating, based on the future gas repair-reporting data of the second gas repair-reporting areas, a maintenance personnel arrangement plan.

A network of wireless nodes collects data from a fluid tank or gas usage device sensor and uploads the data to the cloud or the Internet. The network allows for a temporary node to integrate into the network such that technicians can access the network without access to the cloud or internet. Data from the sensor may then be used by the system, either locally or remotely, to control or adjust one or more Internet of Things (IoT) devices based on the values of parameters such as tank fluid level or gas usage, etc.

A network of wireless nodes collects data from a fluid tank or gas usage device sensor and uploads the data to the cloud or the Internet. The network allows for a temporary node to integrate into the network such that technicians can access the network without access to the cloud or internet. Data from the sensor may then be used by the system, either locally or remotely, to control or adjust one or more Internet of Things (IoT) devices based on the values of parameters such as tank fluid level or gas usage, etc.