G05B2219/163

SUBTENDED DEVICE MAPPING THROUGH CONTROLLER INTROSPECTION
20220147019 · 2022-05-12 ·

Described are platforms, systems, and methods to discover subtended devices through introspection of executive or supervisory controllers. The platforms, systems, and methods maintain a plurality of introspection directives, each introspection directive comprising a sequence of instructions specific to a communications protocol, the sequence of instructions comprising instructions to send at least one command to at least one controller associated with an automation environment in accordance with the communications protocol, instructions to receive a response to the at least one command, and instructions to parse the response; identify an appropriate introspection directive for the at least one controller; and execute the sequence of instructions with respect to the at least one controller to perform operations comprising: sending at least one command to at least one controller; receiving a response; and parsing the response.

GRAPH DATA ENRICHMENT
20220147569 · 2022-05-12 ·

Described are platforms, systems, and methods for real-time enrichment of vertices, edges, and related data within a graph database. The platforms, systems, and methods maintain a graph database comprising a representation of a current state of an automation environment comprising a plurality of data sources, wherein the data sources are represented as vertices in the graph database and relationships between the individual data sources are represented as edges in the graph database; operate a plurality of software agents, each software agent configured to perform operations comprising: applying an algorithm to identify patterns in the graph database; and generating a specific data enrichment based on one or more identified patterns; and contribute the generated data enrichment back to the graph database.

AUTOMATIC DISCOVERY OF RELATIONSHIPS AMONG EQUIPMENT THROUGH AUTOMATED CYCLING AND OBSERVATION
20220147018 · 2022-05-12 ·

Described are platforms, systems, and methods to discover relationships among equipment in automated industrial or commercial environments by cycling each individual piece of equipment while observing sensors in all other equipment in order to measure how each part reacts to each other part. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; issue one or more commands to cycle a current data source in the a plurality of data sources; monitor the automation environment for events or state changes in the data sources; detect one or more events or one or more state changes in one or more other data sources in the a plurality of data sources; and determine one or more relationships between the current data source and the one or more other data sources.

AUTOMATED DATA INTEGRATION PIPELINE WITH STORAGE AND ENRICHMENT
20220147000 · 2022-05-12 ·

Described are platforms, systems, and methods to automatically discover, extract, map, merge, and enrich data found in on-premises in automated industrial and commercial environments and cloud systems for purposes of providing developers access to normalized, merged, and enriched data through an API. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; retrieve data from at least one of the identified data sources; apply a first algorithm to map the retrieved data to a predetermined ontology; merge the mapped data into a data store comprising timeseries of the mapped data; apply a second algorithm to identify patterns in the merged data and enriching the data based on one or more identified patterns; and provide one or more APIs or one or more real-time streams to provide access to the enriched data.

AUTOMATIC DISCOVERY OF RELATIONSHIPS AMONG EQUIPMENT THROUGH OBSERVATION OVER TIME
20220147008 · 2022-05-12 ·

Described are platforms, systems, and methods to discover relationships among equipment in automated industrial or commercial environments by looking for synchrony in state changes among the equipment. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; detect one or more events or one or more state changes in the data sources; store the detected events or state changes; detect synchrony in the detected events or state changes by performing operations comprising: identifying combinatorial pairs of data sources having an event or state change within a predetermined time window; and conducting pairwise testing for each identified combinatorial pair of data sources by applying an algorithm to the stored detected events or state changes; and determine one or more relationships for at least one identified combinatorial pair of data sources.

Control environment command execution

An automation control system is provided that includes one or more components. The components include an embedded execution engine that is configured to execute one or more commands based upon data communicated to the one or more components from another component of the automation control system. The data is representative of a change to an object in the control system.

System and methods for cloud-based monitoring and control of physical environments

Disclosed are systems and methods for cloud-based monitoring and control of physical environments. A system comprises a computing cloud with at least one processor configured to execute one or more application modules and a data analytics module for analyzing diagnostic and environmental metric data. The system further comprises a building server communicatively coupled with the computing cloud, at least one gateway communicatively coupled with the building server, and at least one system device communicatively coupled with the at least one gateway. The at least one system device generates environmental metric data for further analysis and display, and the data is communicated to the computing cloud by way of the at least one gateway and the at least one building server.

Central plant control system based on load prediction through mass storage model

Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system generates a regression model of a produced thermal energy load produced by a supply device of the plurality of devices. The system predicts the produced thermal energy load produced by the supply device for a first time period based on the regression model. The system determines a heat capacity of gas or liquid in the loop based on the predicted produced thermal energy load. The system generates a model of mass storage based on the heat capacity. The system predicts an induced thermal energy load during a second time period at a consuming device of the plurality of devices based on the model of the mass storage. The system operates the energy plant according to the predicted induced thermal energy load.

Control device and control method
11307553 · 2022-04-19 · ·

A control device includes a first processor that acquires a synchronization signal that is generated every first period, and a second processor that generates a second period that is obtained by dividing the first period by n (n≥1), generates a control signal, using a timer, every third period that is obtained by dividing the second period by m (m≥2), where at least one of a plurality of control signals generated in the first period is a control signal that should be synchronous with the synchronization signal, and in a case where occurrence of an error between timings of the synchronization signal and the control signal that should be synchronous with the synchronization signal is detected, the second processor corrects the error by temporarily changing a width of the timer that is to be started at next and later times.

Systems and methods for homeowner-directed risk of property damage mitigation

Methods and systems for homeowner-directed risk mitigation for damage to a property associated with insurance-related events are provided. A smart home controller may analyze data received from a plurality of smart devices disposed on, or proximate to, a property as well as data received from an insurance provider. If it is determined that an actual or potential risk of property damage exists, the smart home controller may transmit an alert to a homeowner detailing the risk. The homeowner may respond to the alert by transmitting an instruction to mitigate or prevent damage associated with the risk back to the smart home controller. Subsequently, the smart home controller may transmit information about the actual or potential risks and any homeowner-directed mitigative actions to an insurance provider. The insurance provider may interpret the transmitted data and perform insurance activities, such as providing discounts and adjusting an insurance policy associated with the property.