A distributed device management system specifies a device capable of supplying request data used for providing a service, from among a plurality of devices connected to a network. Device management function units are disposed so as to be geographically distributed and manage the states of the devices located in deployed areas. A device specifying function unit has a device inquiry cache in which a response log including the type of data which was previously required for the service and an identifier of the device management function unit that manages the device which was capable of supplying the data is recorded. In a case where this request data coincides with the type of data included in the response log, an inquiry is transmitted to the device management function unit associated with the request data in the response log.

A distributed device management system specifies a device capable of supplying request data used for providing a service, from among a plurality of devices connected to a network. Device management function units are disposed so as to be geographically distributed and manage the states of the devices located in deployed areas. A device specifying function unit has a device inquiry cache in which a response log including the type of data which was previously required for the service and an identifier of the device management function unit that manages the device which was capable of supplying the data is recorded. In a case where this request data coincides with the type of data included in the response log, an inquiry is transmitted to the device management function unit associated with the request data in the response log.

A method, computer program product, and computing system for tracking encounter participants is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information obtained via one or more machine vision systems. The machine vision encounter information is processed to identify one or more humanoid shapes.

A method, computer program product, and computing system for tracking encounter participants is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information obtained via one or more machine vision systems. The machine vision encounter information is processed to identify one or more humanoid shapes.

In some examples, a system includes: a plurality of different articles of personal protection equipment (PPE) that are all controlled by a particular user, and a computing device. The computing device may include one or more computer processors configured to receive sets of data from each of the different articles of PPE, wherein each set of data is based at least in part on a type of each of the different articles of PPE; generate for display a user interface that contemporaneously includes a plurality of graphical elements that are based at least in part on at least two sets of data that correspond to at least two different articles of PPE of the plurality of different articles of PPE; and in response to receiving an indication of user input that corresponds to at least one of the plurality of graphical elements, perform at least one operation.

In some examples, a system includes: a plurality of different articles of personal protection equipment (PPE) that are all controlled by a particular user, and a computing device. The computing device may include one or more computer processors configured to receive sets of data from each of the different articles of PPE, wherein each set of data is based at least in part on a type of each of the different articles of PPE; generate for display a user interface that contemporaneously includes a plurality of graphical elements that are based at least in part on at least two sets of data that correspond to at least two different articles of PPE of the plurality of different articles of PPE; and in response to receiving an indication of user input that corresponds to at least one of the plurality of graphical elements, perform at least one operation.

A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

An information processing device includes: a communication unit that communicates with a plurality of IoT (Internet of Things) sensors; and a configuration unit that configures a management table that manages timings of access to the IoT sensors. Using a smallest value of sampling cycles of the plurality of IoT sensors as one cycle, the configuration unit configures the management table having a plurality of slots divided within the one cycle, and stores a frequency parameter indicating an access frequency to each of the IoT sensors in a different one of the slots.

The embodiment of the present disclosure provides a method for pipeline network inspection zone generation based on smart gas and an Internet of Things system thereof. The method is implemented based on the Internet of Things system. The Internet of Things system includes a smart gas pipeline network safety management platform, a smart gas sensor network platform, and a smart gas object platform which interact in turn. The method includes: obtaining area feature information of a target inspection area of a gas network based on the smart gas object platform through the smart gas sensor network platform; generating one or more key inspection points in the target inspection area based on the area feature information of the target inspection area; and generating one or more inspection zones in the target inspection area based on the one or more key inspection points.