The present disclosure relates generally to building devices of building systems that operate a building. The present disclosure relates more particularly to building modeling.
Building modeling may represent contextual information regarding a building and may be defined according to various formats. Building equipment and/or building software applications can be built to operate on the different formats. However, because each piece of building equipment or software application may be built for a specific building model format, the use of the building equipment or software applications may be limited to only the specific building model format. Therefore, it would be advantageous for a schema for use in the building equipment or software applications where the universal schema encodes information of any building model format.
One implementation of the present disclosure is a building system of a building. The building system includes one or more memory devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive building metadata, the building metadata describing components of the building, generate, based on the building metadata, entities, each of the entities representing one the components, and determine, based on the building metadata, relationships between the entities. The instructions cause the one or more processors to generate metadata strings in a universal building schema, one metadata string of the metadata strings including characters representing a first entity of the entities, one or more second entities of the entities related to the first entity, and one or more relationships between the first entity and the one or more second entities.
In some embodiments, the characters represent each of the one or more relationships with at least one of a single reserved character, the single reserved character linked to a particular relationship of predefined relationships or a character set, the character set representing the particular relationship of the predefined relationships.
In some embodiments, the first entity and the one or more second entities are each represented by one or more type characters representing an entity type and one or more identifier characters identifying a particular instance of the entity type.
In some embodiments, the entity type is a particular entity type of a set of predefined entity types.
In some embodiments, the one metadata string of the metadata strings is referenced by a fully qualified name (FQN), wherein the FQN is an ending entity of the one metadata string.
In some embodiments, a second metadata string of the metadata strings includes a first part represented by first characters, wherein the first part is the FQN, a separation character separating the first part from a second part, and the second part, the second part representing one of one or more other entities related to the one metadata string.
In some embodiments, the building metadata is data of a building information model (BIM). In some embodiments, the BIM is defined by a user and represents the building and the components of the building, wherein the BIM is augmented by the user to include naming data for each of the components according to the universal building schema.
In some embodiments, the BIM is augmented by a user to include a definition of a second part relating a first component of the components to one or more second components of the components. In some embodiments, the instructions cause the one or more processors to generate a particular metadata string of the metadata strings including a first part representing the first component and the second part representing the one or more second components.
In some embodiments, the instructions cause the one or more processors to generate, based on the building metadata, the entities by identifying, based on the BIM, the naming data for each of the components, the naming data representing the entities with an entity type and an entity identifier.
In some embodiments, the instructions cause the one or more processors to determine, based on the building metadata, the relationships between the entities by identifying relational information between the components indicated by the BIM.
In some embodiments, each metadata string of the metadata strings include a first part represented by first characters, wherein the first part represents the first entity, one or more separation characters separating the first part from one or more second parts and the one or more second parts from each other, and the one or more second parts, each of the one or more second parts representing one of the one or more second entities.
In some embodiments, the first entity ordered within the first part with one or more other first entities according to a predefined entity type hierarchy of the universal building schema.
In some embodiments, the predefined entity type hierarchy lists entities according to entity type from a building entity type to a floor entity type to a room entity type to an equipment entity type to a point entity type.
Another implementation of the present disclosure is a method including receiving, by a processing circuit, building metadata, the building metadata describing components of a building, generating, by the processing circuit, based on the building metadata, entities, each of the entities representing one of the components, determining, by the processing circuit, based on the building metadata, relationships between the entities, and generating, by the processing circuit, metadata strings in a universal building schema, one metadata string of the metadata strings including characters representing a first entity of the entities, one or more second entities of the entities related to the first entity, and one or more relationships between the first entity and the one or more second entities.
In some embodiments, the characters represent each of the one or more relationships with at least one of a single reserved character, the single reserved character linked to a particular relationship of predefined relationships or a character set, the character set representing the particular relationship of the predefined relationships.
In some embodiments, the first entity and the one or more second entities are each represented by one or more type characters representing an entity type and one or more identifier characters identifying a particular instance of the entity type.
In some embodiments, the entity type is a particular entity type of a set of predefined entity types.
In some embodiments, the one metadata string of the metadata strings is referenced by a fully qualified name (FQN), wherein the FQN is an ending entity of the one metadata string.
In some embodiments, a second metadata string of the metadata strings includes a first part represented by first characters, wherein the first part is the FQN, a separation character separating the first part from a second part, and the second part, the second part representing one of one or more other entities related to the one metadata string.
Another implementation of the present disclosure is one or more computer readable storage media configured to store instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive building metadata, the building metadata describing components of a building, generate, based on the building metadata, entities, each of the entities representing one of the components, determine, based on the building metadata, relationships between the entities, and generate metadata strings in a universal building schema, one metadata string of the metadata strings including characters representing a first entity of the entities, one or more second entities of the entities related to the first entity, and one or more relationships between the first entity and the one or more second entities.
Various objects, aspects, features, and advantages of the disclosure will become more apparent and better understood by referring to the detailed description taken in conjunction with the accompanying drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements.
Overview
Referring generally to the FIGURES, systems and methods for a universal naming schema that encodes entity types and entity relationships for a building are shown, according to various exemplary embodiments. The universal naming schema can be a schema that can universally encode, in a single string, types and relationships of an entity in any building data format such as BACnet, BRICK, or Building Information Modeling (BIM). Entities may be data points (e.g., sensor points, actuator points, virtual points calculated from measured points), pieces of equipment (e.g., thermostats, boilers, chillers, air handler units (AHUs), variable air volume (VAV) units, controllers, etc.), spaces (e.g., rooms, zones, buildings, lobbies), people (building owners, tenants, office personal, etc.), and/or any other type of entity.
In some embodiments, the building system is configured to construct one or more strings in the universal naming schema that define the entity, the entity type, and the relationships between the entities. In some embodiments, the building system is configured to generate strings in the universal schema from manually entered information. For example, in some embodiments, a user may define each entity, the type of each entity, and relationships between each entity in a user interface. In some embodiments, the building system is configured to automatically construct the strings from one or more data sources. Data sources may be IFC files, BACnet objects, etc. In some embodiments, the building system is configured to receive data such as BACnet objects and is configured to extract the entities, entity types, and entity relationships from the BACnet objects and construct the strings in the universal naming schema.
In some embodiments, building applications can directly consume and/or operate based on one or more strings in the universal naming schema. Furthermore, when entities in buildings are named following the universal naming schema, the strings formatted in the universal naming schema can be translated into knowledge or space graphs that are consumed by the building applications. In some embodiments, the universal naming schema can be integrated with specific building systems, tools, and/or software processes. In some embodiments, the universal naming schema defines all the necessary elements and/or parts that could be used directly for integration with the building systems, tools, and/or software processes. In some embodiments, the vocabularies utilized in the universal naming schema are defined in BRICK, a unified semantic representation of building resources.
With respect to BACnet, it may be difficult for a user to understand the vocabulary used to define elements of the BACnet. However, the universal naming schema may provide a user readable schema. Because the universal naming schema is human readable and includes rich data, a user or system may gain greater information reading the universal naming schema as compared to BACnet where there are numeric values that do not provide significant contextual information. Furthermore, BACnet may have a limited number of available characters and/or character sets which reduce the amount of information that can be included with the BACnet. This is addressed by the context rich structure of the universal naming schema.
The universal naming schema can include a significant amount of information without needing a significant amount of characters. For example, the phrase, “hasLocation” could be represented by the character “@”. Furthermore, the character set “measures” could be represented by the character “?”. Furthermore, characters in the universal naming schema might not be legal in BACnet. In some embodiments, a building system can be configured to select an optimal small number of point names in the universal naming schema. In some embodiments, a query that retrieves strings in the universal naming schema may return more information in a single query (e.g., an entire string of elements) than compared to multiple queries in other systems. Without returning the entire string, a system might have to make multiple queries for each element.
It may be difficult to translate BRICK (e.g., RDF and/or turtle data) into BACnet. However, the universal naming schema may provide a method for translating BRICK data into BACnet. For example, data in the universal naming schema can be translated into BACnet without requiring a significant amount of processing. Furthermore, the BACnet data can be translated back into the universal naming schema without requiring a significant amount of processing.
Building with Building Systems
Referring now to
Both the building 100 and the parking lot 110 are at least partially in the field of view of the security camera 102. In some embodiments, multiple security cameras 102 may be used to capture the entire building 100 and parking lot 110 not in (or in to create multiple angles of overlapping or the same field of view) the field of view of a single security camera 102. The parking lot 110 can be used by one or more vehicles 104 where the vehicles 104 can be either stationary or moving (e.g. delivery vehicles). The building 100 and parking lot 110 can be further used by one or more pedestrians 106 who can traverse the parking lot 110 and/or enter and/or exit the building 100. The building 100 may be further surrounded or partially surrounded by a sidewalk 108 to facilitate the foot traffic of one or more pedestrians 106, facilitate deliveries, etc. In other embodiments, the building 100 may be one of many buildings belonging to a single industrial park, shopping mall, or commercial park having a common parking lot and security camera 102. In another embodiment, the building 100 may be a residential building or multiple residential buildings that share a common roadway or parking lot.
The building 100 is shown to include a door 112 and multiple windows 114. An access control system can be implemented within the building 100 to secure these potential entrance ways of the building 100. For example, badge readers can be positioned outside the door 112 to restrict access to the building 100. The pedestrians 106 can each be associated with access badges that they can utilize with the access control system to gain access to the building 100 through the door 112. Furthermore, other interior doors within the building 100 can include access readers. In some embodiments, the doors are secured through biometric information, e.g., facial recognition, fingerprint scanners, etc. The access control system can generate events, e.g., an indication that a particular user or particular badge has interacted with the door. Furthermore, if the door 112 is forced open, the access control system, via door sensor, can detect the door forced open (DFO) event.
The windows 114 can be secured by the access control system via burglar alarm sensors. These sensors can be configured to measure vibrations associated with the window 114. If vibration patterns or levels of vibrations are sensed by the sensors of the window 114, a burglar alarm can be generated by the access control system for the window 114.
The building 100 can further include HVAC systems. For example, waterside systems, airside systems, building management systems, and/or various other HVAC systems can be included within the building 100. For example, equipment such as chillers, boilers, rooftop units, air handler units, thermostats, sensors, actuators, dampers, valves, and other equipment can be implemented within the building 100 to control the environmental conditions of the building 100. Examples of building equipment that can be implemented within the building 100 can be found in U.S. patent application Ser. No. 16/048,052 filed Jul. 27, 2018, the entirety of which is incorporated by reference herein.
Referring now to
BMS 200 provides a system architecture that facilitates automatic equipment discovery and equipment model distribution. Equipment discovery can occur on multiple levels of BMS 200 across multiple different communications busses (e.g., a system bus 254, zone buses 256-260 and 264, sensor/actuator bus 266, etc.) and across multiple different communications protocols. In some embodiments, equipment discovery is accomplished using active node tables, which provide status information for devices connected to each communications bus. For example, each communications bus can be monitored for new devices by monitoring the corresponding active node table for new nodes. When a new device is detected, BMS 200 can begin interacting with the new device (e.g., sending control signals, using data from the device) without user interaction.
Some devices in BMS 200 present themselves to the network using equipment models. An equipment model defines equipment object attributes, view definitions, schedules, trends, and the associated BACnet value objects (e.g., analog value, binary value, multistate value, etc.) that are used for integration with other systems. Some devices in BMS 200 store their own equipment models. Other devices in BMS 200 have equipment models stored externally (e.g., within other devices). For example, a zone coordinator 208 can store the equipment model for a bypass damper 228. In some embodiments, zone coordinator 208 automatically creates the equipment model for bypass damper 228 or other devices on zone bus 258. Other zone coordinators can also create equipment models for devices connected to their zone busses. The equipment model for a device can be created automatically based on the types of data points exposed by the device on the zone bus, device type, and/or other device attributes. Several examples of automatic equipment discovery and equipment model distribution are discussed in greater detail below.
Still referring to
In some embodiments, system manager 202 is connected with zone coordinators 206-210 and 218 via a system bus 254. System manager 202 can be configured to communicate with zone coordinators 206-210 and 218 via system bus 254 using a master-slave token passing (MSTP) protocol or any other communications protocol. System bus 254 can also connect system manager 202 with other devices such as a constant volume (CV) rooftop unit (RTU) 212, an input/output module (TOM) 214, a thermostat controller 216 (e.g., a TEC2000 series thermostat controller), and a network automation engine (NAE) or third-party controller 220. RTU 212 can be configured to communicate directly with system manager 202 and can be connected directly to system bus 254. Other RTUs can communicate with system manager 202 via an intermediate device. For example, a wired input 262 can connect a third-party RTU 242 to thermostat controller 216, which connects to system bus 254.
System manager 202 can provide a user interface for any device containing an equipment model. Devices such as zone coordinators 206-210 and 218 and thermostat controller 216 can provide their equipment models to system manager 202 via system bus 254. In some embodiments, system manager 202 automatically creates equipment models for connected devices that do not contain an equipment model (e.g., IOM 214, third party controller 220, etc.). For example, system manager 202 can create an equipment model for any device that responds to a device tree request. The equipment models created by system manager 202 can be stored within system manager 202. System manager 202 can then provide a user interface for devices that do not contain their own equipment models using the equipment models created by system manager 202. In some embodiments, system manager 202 stores a view definition for each type of equipment connected via system bus 254 and uses the stored view definition to generate a user interface for the equipment.
Each zone coordinator 206-210 and 218 can be connected with one or more of zone controllers 224, 230-232, 236, and 248-250 via zone buses 256, 258, 260, and 264. Zone coordinators 206-210 and 218 can communicate with zone controllers 224, 230-232, 236, and 248-250 via zone busses 256-260 and 264 using a MSTP protocol or any other communications protocol. Zone busses 256-260 and 264 can also connect zone coordinators 206-210 and 218 with other types of devices such as variable air volume (VAV) RTUs 222 and 240, changeover bypass (COBP) RTUs 226 and 252, bypass dampers 228 and 246, and PEAK controllers 234 and 244.
Zone coordinators 206-210 and 218 can be configured to monitor and command various zoning systems. In some embodiments, each zone coordinator 206-210 and 218 monitors and commands a separate zoning system and is connected to the zoning system via a separate zone bus. For example, zone coordinator 206 can be connected to VAV RTU 222 and zone controller 224 via zone bus 256. Zone coordinator 208 can be connected to COBP RTU 226, bypass damper 228, COBP zone controller 230, and VAV zone controller 232 via zone bus 258. Zone coordinator 210 can be connected to PEAK controller 234 and VAV zone controller 236 via zone bus 260. Zone coordinator 218 can be connected to PEAK controller 244, bypass damper 246, COBP zone controller 248, and VAV zone controller 250 via zone bus 264.
A single model of zone coordinator 206-210 and 218 can be configured to handle multiple different types of zoning systems (e.g., a VAV zoning system, a COBP zoning system, etc.). Each zoning system can include a RTU, one or more zone controllers, and/or a bypass damper. For example, zone coordinators 206 and 210 are shown as Verasys VAV engines (VVEs) connected to VAV RTUs 222 and 240, respectively. Zone coordinator 206 is connected directly to VAV RTU 222 via zone bus 256, whereas zone coordinator 210 is connected to a third-party VAV RTU 240 via a wired input 268 provided to PEAK controller 234. Zone coordinators 208 and 218 are shown as Verasys COBP engines (VCEs) connected to COBP RTUs 226 and 252, respectively. Zone coordinator 208 is connected directly to COBP RTU 226 via zone bus 258, whereas zone coordinator 218 is connected to a third-party COBP RTU 252 via a wired input 270 provided to PEAK controller 244.
Zone controllers 224, 230-232, 236, and 248-250 can communicate with individual BMS devices (e.g., sensors, actuators, etc.) via sensor/actuator (SA) busses. For example, VAV zone controller 236 is shown connected to networked sensors 238 via SA bus 266. Zone controller 236 can communicate with networked sensors 238 using a MSTP protocol or any other communications protocol. Although only one SA bus 266 is shown in
Each zone controller 224, 230-232, 236, and 248-250 can be configured to monitor and control a different building zone. Zone controllers 224, 230-232, 236, and 248-250 can use the inputs and outputs provided via their SA busses to monitor and control various building zones. For example, a zone controller 236 can use a temperature input received from networked sensors 238 via SA bus 266 (e.g., a measured temperature of a building zone) as feedback in a temperature control algorithm. Zone controllers 224, 230-232, 236, and 248-250 can use various types of control algorithms (e.g., state-based algorithms, extremum seeking control (ESC) algorithms, proportional-integral (PI) control algorithms, proportional-integral-derivative (PID) control algorithms, model predictive control (MPC) algorithms, feedback control algorithms, etc.) to control a variable state or condition (e.g., temperature, humidity, airflow, lighting, etc.) in or around building 10.
Referring now to
In some embodiments, the entities 302-320 are nodes of a graph while the relationships 322-338 are edges of the graph. The relationships 322-338 represent semantic relationships between the entities 302-320. The relationships 322-338 can be directional, i.e., represent a relationship between a first entity and a second entity. In some embodiments, the relationships 322-338 can be bidirectional, i.e., a first relationship between the first entity and the second entity and a second relationship between the second entity and the first entity. In some embodiments, the relationships 322-338 are defined according to types and are identified with words and/or phrases.
The entities include an air handler unit (AHU) entity 302 that “hasPoint” relationship 322 to a power meter entity 304. The AHU entity 302 has a “controls” relationship 3211 to a VAV entity 312. The VAV entity 312 includes components, represented by a damper entity 320 and a “hasPart” relationship 338 between the VAV entity 312 and the damper entity 320. The VAV entity 312 also has a point. The point is represented by a temperature sensor entity 318. A “hasPoint” relationship 336 between the VAV entity 312 and the temperature sensor entity 318 indicates that the VAV has the temperature sensor point.
Furthermore, the VAV entity 312 operates a particular area of a building, i.e., the VAV entity 312 feeds, represented by the “feeds” relationship 331, the HVAC zone entity 310. The HVAC zone entity 310 represents a zone that includes a room, i.e., room 101 entity 316. The relationship between the HVAC zone and the room 101 is represented by the “hasPart” relationship 330 between the HVAC zone entity 310 and the room 101 entity 316. The room 101 is further part of a lighting zone represented by lighting zone entity 308. A “hasPart” relationship 326 between the lighting zone entity 308 and the room 101 entity 316 indicates that the room 101 is part of the lighting zone.
Furthermore, the lighting zone includes another room, a room 102. This is represented by the lighting zone entity 308, the room 102 entity 314, and the “hasPart” relationship 328 between the lighting zone entity 308 and the room 102 entity 314. Finally, a lighting controller is configured to control lighting in the lighting zone. This is represented by the lighting controller entity 306 and the “controls” relationship 324 between the lighting controller entity 306 and the lighting zone entity 308.
Universal Naming Schema
Referring now to
The client devices 404, the building devices 402, the client devices 406, the building systems 414, and/or the building platform 420 can communicate via a network 458. The network 458 can include network components (e.g., routers, switches, transceivers, range extenders, coordinators, etc.) for implementing LANs, wide area networks (WANs), metropolitan area networks (MANs), the Internet, Zigbee, Bluetooth, CAN, BACnet, etc.), in some embodiments.
The building platform 420 includes a processing circuit 422. The processing circuit 422 includes a processor 424 and a memory 436. Although only one processor and one memory are shown in
The memory 426 can include one or more devices (e.g., memory units, memory devices, storage devices, etc.) for storing data and/or computer code for completing and/or facilitating the various processes described in the present disclosure. The memory 426 can include random access memory (RAM), read-only memory (ROM), hard drive storage, temporary storage, non-volatile memory, flash memory, optical memory, or any other suitable memory for storing software objects and/or computer instructions. The memory 426 can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present disclosure. The memory 426 can be communicably connected to the processor 424 and can include computer code for executing (e.g., by the processor 424) one or more processes described herein. The memory 426 can include multiple components (e.g., software modules, computer code, etc.) that can be performed by the processor 424 (e.g., executed by the processor 424).
The memory 426 includes building applications 428, a universal naming schema manager 426, and universal naming schema definitions 444. The universal naming schema manager 436 includes an ingestion service 438, a translator 440, and universal naming schema data 442. The universal naming schema manager 436 can be configured to receive data, e.g., from a universal naming schema tool 412 that is manually entered by a user of the client devices 406, or alternatively building schema data 416 that the building systems 414 may store and/or operate on. The universal naming schema manager 436 can generate the universal naming schema data 442 based on the data entered via the universal naming schema tool 412 and/or via the building schema data 416.
The ingestion service 438 can receive data identifying entity names, entity types, and/or relationships between the entities via the universal naming schema tool 412. The ingestion service 438 can compile the data into the universal naming schema. The ingestion service 438 can translate the data received from the universal naming schema tool 408 into the universal naming schema based on the universal naming schema definition 444 that defines the format and/or character assignments for the universal naming schema. Similarly, the ingestion service 438 can receive manually entered data as BIM schema data 410. A BIM modeling tool 408 that allows a user to generate and/or edit a BIM model (e.g., an IFC model) can allow a user to enter entity names, entity types, and/or entity relationships according to the universal naming schema. The BIM schema data 410 can be ingested by the ingestion service 438 and converted into the universal naming schema data 442 by the ingestion service 438.
In some embodiments, the building systems 414 may store and/or operate on building schema data 416. The building schema data 416 can be BRICK data, BACnet data, IFC data, BIM data, and/or any other data schema that defines entities, entity types, and/or entity relationships. The translator 440 can extract and/or infer the entities, entity types, and/or entity relationships from the building schema data 416 and convert the building schema data 416 into the universal naming schema data 442. Extracting entity names, entity types, and/or entity relationships from building data such as BACnet is described in U.S. patent application Ser. No. 16/663,623 filed Oct. 25, 2019, the entirety of which is incorporated by reference herein.
The universal naming schema data 442 may be one or multiple strings that represent entities, entity types, and/or entity relationships. One string may be configured to represent a first entity, a type of the first entity, and/or relationships to other entities of the first entity. The universal naming schema data 442 can be in a format defined by the universal naming schema definitions 444. The definitions 444 include part definitions 446, relationship definitions 448, entity definitions 450, reserved characters 452, and FQN definitions 454.
The part definitions 446 can include definitions for parts of the strings of the universal naming schema data 442. Each part may be a substring of a string. For example, the part definitions 446 can include a first part and a second part. The first part can define a particular entity and a type of the entity. The second part can identify entities related to the particular entity and the type of those entities. Parts are shown in greater detail in
The relationship definitions 448 indicate the various relationships that can be defined between entities. The relationships of the relationship definitions 448 can be relationships such as “feeds,” “controls,” “hasPart,” etc. The relationships can be relationships defined according to the BRICK schema.
The entity definitions 450 can define the entities of the universal naming schema data 442. The entity definitions 450 include indications of the various types of entities, e.g., VAVs, AHUs, lighting controllers, zones, rooms, etc. The entity types can be entity types defined according to the BRICK schema. The entity definitions 450 can be names or acronyms describing a defined set of entities.
The reserved characters 452 can be characters that are reserved to represent particular meanings within the string. For example, the character, “:”, may be used to encode an entity and an entity type. For example, “AHU_3:AHU” could indicate that an “AHU_3,” a name of a particular entity, is of an entity type, “AHU.” For example, some characters may be reserved to define relationships as defined according to the relationship definitions 448. For example, the character “/” may represent a “hasPart” relationship. The fully qualified name (FQN) definitions 454 can be a section of the string that uniquely identifies an entity. Other entities can utilize the FQN to reference themselves. FQNs are described in greater detail in
The building applications 428 include visualization applications 430, building monitoring applications 432, and building control applications 434. The visualization applications 430 generate one or more user interfaces that present visualizations to an end user based on the universal naming schema data 442. In some embodiments, the visualization applications 430 cause a user interface of the client devices 404 to display information based on the universal naming schema data 442. For example, the visualization applications 430 can render a graph data structure for display via the universal naming schema data 442. In some embodiments, visual BIM representations can be rendered for display, at least partly based on the universal naming schema data 442.
The building monitoring applications 432 can be applications that operate on the universal naming schema data 442 to monitor the building devices 402 and/or the building control system 418. For example, the building monitoring applications 432 can organize data based on the relationships encoded in the universal naming schema data 442. In some embodiments, the building monitoring applications 432 can perform fault detection and diagnostics. The fault detection and diagnostics can be performed based on operational data collected from the building devices 402 and/or the building control system 418 and the universal naming schema data 442.
The building control applications 434 can operate to control the building devices 402 and/or the building control system 418. The building control applications 434 can generate operating settings (e.g., motor speeds, duct pressure setpoints, temperature setpoints, damper positions, etc.) and communicate the operating settings to the building devices 402 and/or the building control system 418. The building control applications 434 can generate the settings based on the universal naming schema data 442.
Referring now to
The string 504 illustrates the string 502 reduced in size with reserved relational characters. The characters “/” and “>” represent the relationships “[hasPart]” and “[feeds]” respectively. The string 502, with the relationships “[hasPart]” and “[feeds]” replaced with the reserved relational characters, is the string 504.
The universal naming schema has two parts separated by a comma in the format, “Part1,Part2.” “Part1” is referred to herein as the first part while “Part2” is referred to herein as the second part. The first part and the second part can each be a portion or sub-string of a string, i.e., different components of a particular string. The second part can further divided into one or more sub-parts also separated by commas in the format, “Part2a, Part2b, Part2c, . . . ” (e.g., the second part 508 and the second part 510). In those cases, the strings may be in the form of, “Part1.” As shown in
Referring now to
The types 608 can include a predefined set of strings that represent common elements of a building. For example, the types may be the buildings, rooms, zones, controllers, VAVs, thermostats, AHUs, etc. In some embodiments, the type 608 can be a type defined in BRICK schema. Some entity types might be “AHU_Automatic_Mode_Command,” “Building,” “AHU,” or “VAV.” The entity 610 can be defined as “T:ID” where T is the type and ID is an identifier, e.g., an entity name. The identifier can be a string that a user or system provides to uniquely identify a particular entity. Examples of entities formed with a type and an identifier may be “Building:EBU3B,” “VAV:2229,” and “AHU_Automatic_Mode_Command:c1.”
The relationships 612 can include a predefined set of strings that represent common relationships between components a building. The relationship 612 is defined in the format “[relationship].” The relationship 612 can be defined in the BRICK schema. For example, the relationship 612 can be “[hasPart],” “[hasPoint],” and “[feeds].” In some embodiments, an application specific table could be defined to map frequently used relationships to a shortcut character. For example, the character “/” could be mapped to the “[hasPart]” relationship while “>” could be mapped to “[feeds]” relationship.
Three strings 602-606 are shown in the block diagram 600, the string 602 is “Building:EBU3B/AHU:1.” The second string 604 is “>VAV:2229.” The third string 606 is “>VAV:3119.” The type 608 for the string 602 is shown as building 614 and AHU 616. The type 608 for the string 604 is shown as VAV 618. The type 608 for the string 606 is shown as VAV 618.
Furthermore, each entity of the strings 602-606 is defined in each string. Each entity includes a name and a reference to the entity type. For example, for entity 622, “Building:EBU3B,” the name is EBU3B identifying a unique instance of the entity type “Building.” Similarly, for the entity 624, the entity name is “1” while the entity type is “AHU,” resulting in an entity “AHU:1.” The entities 626 and 628 define the entities of the strings 604 and 606 respectively.
Each of the strings 602-606 include a relationship. In the string 602, the relationship 632 is the character 630, “/”. The character “/” encodes the relationships 634, i.e., “hasPart.” In the strings 604 and 606, the relationships 634 are both the character, “>”. The character “>” encodes the relationships 636, i.e., “feeds” for the strings 604 and 606.
Referring now to
The block diagram 700 includes an entity hierarchy 702 of entities from entity En to entity E0. The entity hierarchy 702 can indicate the format “En/En−1/ . . . E1/.” The entities can be equipment, point, space, or any other type of entity. Entity E0 defines the main entity (i.e., entity type and entity identifier) that is described by a particular string. Furthermore, the entity type hierarchy 704 defines the order of entities in the string by type, i.e., building, floor, room, equipment, and point. The locations of the entity type hierarchy 704 may be the physical location of an entity and may be separate from the location that the entity controls or feeds. The strings 706-710 are in the hierarchy formats defined by the hierarchies 702 and 704. The string 706 is “Building:507/Floor:2/AHU:A2.” The string 708 is “Building:cork/AHU:1/Supply_Fan:1/Supply_Fan_Status:1.” The string 710 is “Building:cork.”
The string 706 is built up of three entities 712-716, i.e., “Building:507,” “Floor:2,” and “AHU:A2.” The string 708 is built up of four entities 718-724, i.e., “Building:cork,” “AHU:1,” “Supply_Fan:1,” and “Supply_Fan_Status:1.” The string 710 is built of a single entity 726, i.e., “Building:cork.” Each of the strings 706-710 is ordered according to the entity hierarchy 702 and the entity type hierarchy 704.
Referring now to
In
The FQN can be used in both the first part and the second part. In the case of the first part, the alias to a FQN could be used to reduce the length of the first part. For example, given a piece of equipment defined by the string 806, i.e., “Building:EBU3BNAV:4106/Reheat_Valve:4106,” the FQN 814 could be “Reheat_Valve:4106.” The points of the “reheat_Valve:4106” could be defined using the FQN 814. For example, the string 816, i.e., “Reheat_Valve:4106/Reheat_Valve_Command:4106” uses the FQN 814. This is also equivalent to the string 818, i.e., “Building:EBU3BNAV:4106/Reheat_Valve:4106/Reheat_Valve_Command:4106” which can is built from the FQN 812. As can be seen, using the FQN 814 significantly reduces the length of the string 816 as compared to the string 818 that uses the FQN 812.
Referring now to
The second part can be is divided into one or more sub-parts separated by commas. The FQN can be used to define a sub-part. The FQN can be in in format 902, i.e., “FQNEx[relation]E0.” In some embodiments, the FQN can be in the format 904, i.e., “E0[relation]FQNEx.” The FQN formats 902 and 904 can be fully qualified names of an entity Ex. The element, “[relation]” of the FQN formats 902 and 904 defines the relationship that an entity E0 has with the entity Ex. In some cases, the entity E0 can be skipped. The strings 906 and 908 can both be used as an FQN to reference another entity, i.e., an entity “VAV:2.” A string 910 references the “VAV:2” with an FQN, i.e., “>VAV:1.”
Referring now to
In the table 1000, the character “,” is indicated as encoding a separation of parts, i.e., the first part and/or one or more second parts. The character “:” is indicated as encoding entities in the universal naming schema, i.e., encode the entity type and entity name. For example, for an entity type “VAV” and an entity name “1,” the character “:” can be used to encode the entity “VAV:1.” Furthermore, the table 1000 indicates that brackets, “[ ]” can be used to encode a relationship, e.g., “[hasPart],” “[isA],” “[controls]” etc.
Referring now to
The table 1100 illustrates characters reserved for two different types of relationships. However, in some embodiments, any number of relationships can be represented by a single character or multiple characters. In the table 1100, the character, “/” can encode the relationship “[hasPart].” Furthermore, in the table 1100, the character, “>” can encode the relationship “[feeds].”
In some embodiments, if a relationship is not defined in the universal naming schema (or is not defined in BRICK schema), a user can provide input via the client devices 404 that indicate custom relationships. The custom relationships can be defined in the format, “CUSTOME_RELATION_XYZ” where “XYZ” defines a name that the user provides for the custom relationship. For example, for a relationship, “Forward,” that a user provides to the universal naming schema manager 436, the universal naming schema manager 436 could define a relationship, “CUSTOME_RELATION_Forward.” In addition to defining custom relationships in the universal naming schema, the universal naming schema manager 436 can be configured to allow a user to input type definitions. For example, for an entity type, “Switch,” that a user can provide to the universal naming schema manager 436, the universal naming schema can store an entity type, “CUSTOME_TYPE_Switch.”
Referring now to
The table 1200 further includes use recommendations for the first part and the second part of the universal naming schema for the various entity types. For the building entity type, the recommendations indicate that building names can be used as identifiers in entity E0. The table 1200 further indicates that information such as street address and site reference can be referenced for the building through a second part.
The table 1200 further includes a floor entity type and indicates that integers can be used as identifiers for entity E0 to identify floors as opposed to words, e.g., “Floor:1” as opposed to “Floor:first.” The table 1200 indicates that an entity type, “Room,” can be identified with numbers for entity E0. Furthermore, the table 1200 indicate that, for an entity type, “HVAC_Zone,” entities of the type “HVAC_Zone” can be referenced with room number of section number as identifiers for entity E0.
Referring now to
Referring now to
The strings 1402 are strings that describe spaces of a building. The building is represented as entity “Building:EBU3B” and is further related to a floor, i.e., “Floor:2,” a room, i.e., “Room:2144,” and an “HVAC_Zone,” i.e., “HVAC_Zone:2144.” The string “Building:EBU3B/Floor:2/Room:2144” indicates that the building entity “Building:EBU3B” has a floor, “Floor:2,” and that the floor has a room, “Room:2144.”
The string “Building:EBU3B/Floor:2/HVAC_Zone:2144,/Room:2144” indicates that the floor further includes an HVAC zone, “HVAC_Zone:2144.” The string sub-section “Building:EBU3B/Floor:2/HVAC_Zone:2144” is a first part while the string subsection “/Room:2144” is a second part. The denotation of the first part and the second part is shown with the character, “,”. The second part indicates that the HVAC_Zone:2144 has the room, “Room:2144,” already referenced in the string “Building:EBU3B/Floor:2/Room:2144.”
The strings 1404 represent points. With reference to the string “Building:EBU3B/Chilled_Water_System:3B/Pump:4/VFD:4/Power_Meter:4,” the string indicates that a building, “Building:EBU3B” has a chilled water system, “Chilled_Water_System:3B.” The chilled water system has a pump, “Pump:4,” which in turn has a variable frequency drive (VFD), “VFD:4.” Furthermore, the VFD includes a power meter, “Power_Meter:4.”
The strings 1406 indicate equipment. For example, the string “Building:EBU3B/AHU:1” indicates that the building references in the strings 1402 and 1406 includes an air handler unit (AHU), “AHU:1.” The strings “Building:EBU3B/VAV:4154,/HVAC_Zone:4154,AHU:1>” and “Building:EBU3BNAV:275,/HVAC_Zone:275,AHU:1>” include multiple parts, i.e. the first part and the second part to indicate multiple VAVs that are associated with various HVAC zones in addition to the AHU.
Referring now to
In step 1502, the universal naming schema manager 436 receives building metadata in a specific building data schema. The universal naming schema manager 436 can receive data in a BRICK format, a BACnet format, BIM data, and/or manually entered data input by a user in the universal naming schema. The data can be received from the client devices 404, the building devices 402, the client devices 406 (e.g., the BIM modeling tool 408 and/or the universal naming schema tool 412), the building systems 414, and/or the building control system 418.
In step 1504, the universal naming schema manager 436 can identity one or more entity types, one or more entity identifiers, and/or one or more relationships in the building metadata received in the step 1502. The universal naming schema manager 436 can, in some embodiments, identity the one or more entity types, entity identifiers, and/or relationships in the building metadata by performing string analysis. For example, string analysis may be performed when the data is BACnet data. The string analysis can be the same as, or similar to, the analysis described in U.S. patent application Ser. No. 16/048,052 filed Jul. 27, 2018, the entirety of which is incorporated by reference herein. In some embodiments, if the data is entered manually or is BRICK data, a mapping or script may be used to identify the various entity types, entity identifiers, and/or entity relationships in the building metadata.
In step 1506, the universal naming schema manager 436 can generate one or more entities based on the entity types and the entity identifiers identified in the step 1504. Generating the entities can include generating a string that is a concatenation of the entity type, the character “:”, and the entity identifier. For example, for an entity type, “AHU” and an entity identifier “3”, the entity may be “AHU:3.”
In step 1508, the universal naming schema manager 436 generates one or more universal naming schema strings based on the one or more entities and/or the one or more relationships. The strings can be the same as or similar to the strings 1400 described in
The universal naming schema manager 436 can apply the universal naming schema definitions 444 in generating the one or more strings. For example, the string parts described in
In step 1510, the building applications 428 can operate based on the universal building schema strings. The operations can include equipment control and/or interface visualization. For example, the building applications 428 can utilize the universal building schema strings to control an environmental condition of a space. For example, one string may indicate a value of a temperature setpoint while other strings may relate the space and equipment to the temperature setpoint. The building applications 428 can determine the appropriate control operations for the building applications 428 to perform. In some embodiments, the building applications 428 can generate building visualizations based on the strings, for example, graph data structure visualizations. Furthermore, in some embodiments, the building devices 402 and/or the building control system 418 can operate based on the universal building schema strings.
Referring generally to
The universal naming schema and/or the BRICK schema can define more entity types and/or relationship types than those defined in BIM (e.g., within Revit or an IFC file). Accordingly, the BIM modeling tool 408 may include an augmentation that allows an entity of a BIM file to be ingested by the universal naming schema manager 436 into universal naming schema data 442. In some embodiments, entities of the BIM file can include a name that a user can encode with an entity type, entity identifier, and/or one or more relationships between entities.
The universal naming schema manager 436 can extract the names from the BIM file and construct strings in the universal naming schema. In some embodiments, the strings constructed by the universal naming schema manager 436 from the BIM files can be used by the building applications 428 to perform equipment control or data visualization. In some embodiments, the strings can be used to manage data storage. For example, the strings can be used to derive relationships between data collected from the building equipment (e.g., timeseries data) and nodes of a BRICK graph (e.g., the graph of
In some embodiments, existing entities and/or relationships of a BIM can be utilized by the universal naming schema manager 436 for translating from BIM to the strings of the universal naming schema. Furthermore, in some embodiments, users can enter entity names, entity types, and/or relationships for identification by the universal naming schema manager 436 via a user interface of a piece of BIM modeling software such as REVIT. Furthermore, the tree structure of a BIM file can be used by the universal naming schema manager 436 to generate the strings in the universal naming schema.
In some embodiments, a user can add entity types and/or relationships directly into the BIM modeling tool 408. The BIM schema data 410 that the BIM modeling tool 408 exports can be analyzed by the universal naming schema manager 436. The universal naming schema manager 436 can extract a brick graph and/or export strings following the universal naming schema. An example of a string generated by the universal naming schema manager 436 from the BIM schema data 410 may be: “Building:1AlbertQuay/Floor:F4/Meeting Room:north/VAV:401/VAV Damper Position Sens or:1”.
Referring now to
Referring now to
The parameter value can be used as the entity identifier and/or entity type. The universal naming schema manager 436 can identify a type of the entity represented by the BIM element with the first word of the string, “Floor,” and identity the entity identifier with the following characters of the string, “2”. The universal naming schema manager 436 can concatenate the characters with a “:” to form the entity, “Floor:2.” Other examples of strings that a user might enter into the user interface 1700 are “Floor 1,” “Floor 2,” “Floor Basement,” “Floor F4,” etc.
Referring now to
As an example, in the user interface 1800, the parameter value of the name parameter is “Server Room:CLG-102.” Other examples of rooms could be “Conference Room:103.” The universal naming schema manager 436 can be configured to extract the strings from the BIM file for generating strings in the universal naming schema. The universal naming schema manager 436 can be configured to search the BIM for values of the name parameter for rooms (e.g., user entered values) and generate the strings in the universal naming schema based on the values of the name parameter.
Additional relationships for the room entity can be introduced as the second parts elements. These elements can be entered as “[X]part2” These additional relationships can be entered by a user into the user interface 1800 via the parameter values for the comments parameter. If there is no second part element, a user may enter “[X]” as is shown in the user interface 1800.
Referring now to
Referring now to
A user can enter an entity into the name parameter uniquely identifying the piece of equipment and the type of the entity via the interface 2000 in the format “Equipment Type:ID.” The user can enter a type of the equipment into the type parameter via the interface 2002. Furthermore, related entities and relationships can be entered as the second part and can be entered as a parameter value of the comments parameter via the interface 2000.
Referring now to
Referring now to
Referring now to
In step 2302, the universal naming schema tool 412 receives user input defining components of a BIM with universal naming schema data. The user may define components of a building, equipment, spaces, people, etc. via interfaces, e.g., the interfaces shown in
In step 2304, the information received in the step 2302 can be compiled. For example, BIM modeling tool 408 can compile the data to generate a BIM file and/or an IFC file. The result of compiling the information received in the step 2303 can be the BIM schema data 410.
In step 2306, the universal naming schema manager 436 can generate the universal naming schema data based on the components of the compiled BIM and the universal naming schema data of the BIM. The universal naming schema manager 436 can extract universal naming schema data from the BIM and generate the universal naming schema model by generating strings based on the extracted universal naming schema data and the components of the BIM. Based on the generated universal naming schema model, in step 2308, the building applications 428 can operate to control equipment of a building and/or generate graphic visualizations for display on a user interface of the client devices 404.
The construction and arrangement of the systems and methods as shown in the various exemplary embodiments are illustrative only. Although only a few embodiments have been described in detail in this disclosure, many modifications are possible (e.g., variations in sizes, dimensions, structures, shapes and proportions of the various elements, values of parameters, mounting arrangements, use of materials, colors, orientations, etc.). For example, the position of elements may be reversed or otherwise varied and the nature or number of discrete elements or positions may be altered or varied. Accordingly, all such modifications are intended to be included within the scope of the present disclosure. The order or sequence of any process or method steps may be varied or re-sequenced according to alternative embodiments. Other substitutions, modifications, changes, and omissions may be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present disclosure.
The present disclosure contemplates methods, systems and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure may be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a machine, the machine properly views the connection as a machine-readable medium. Thus, any such connection is properly termed a machine-readable medium. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions.
Although the figures show a specific order of method steps, the order of the steps may differ from what is depicted. Also two or more steps may be performed concurrently or with partial concurrence. Such variation will depend on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations could be accomplished with standard programming techniques with rule based logic and other logic to accomplish the various connection steps, processing steps, comparison steps and decision steps.
Number | Name | Date | Kind |
---|---|---|---|
5301109 | Landauer et al. | Apr 1994 | A |
5446677 | Jensen et al. | Aug 1995 | A |
5581478 | Cruse et al. | Dec 1996 | A |
5812962 | Kovac | Sep 1998 | A |
5960381 | Singers et al. | Sep 1999 | A |
5973662 | Singers et al. | Oct 1999 | A |
6014612 | Larson et al. | Jan 2000 | A |
6031547 | Kennedy | Feb 2000 | A |
6134511 | Subbarao | Oct 2000 | A |
6157943 | Meyer | Dec 2000 | A |
6285966 | Brown et al. | Sep 2001 | B1 |
6363422 | Hunter et al. | Mar 2002 | B1 |
6385510 | Hoog et al. | May 2002 | B1 |
6389331 | Jensen et al. | May 2002 | B1 |
6401027 | Xu et al. | Jun 2002 | B1 |
6437691 | Sandelman et al. | Aug 2002 | B1 |
6477518 | Li et al. | Nov 2002 | B1 |
6487457 | Hull et al. | Nov 2002 | B1 |
6493755 | Hansen et al. | Dec 2002 | B1 |
6577323 | Jamieson et al. | Jun 2003 | B1 |
6626366 | Kayahara et al. | Sep 2003 | B2 |
6646660 | Patty | Nov 2003 | B1 |
6704016 | Oliver et al. | Mar 2004 | B1 |
6732540 | Sugihara et al. | May 2004 | B2 |
6764019 | Kayahara et al. | Jul 2004 | B1 |
6782385 | Natsumeda et al. | Aug 2004 | B2 |
6813532 | Eryurek et al. | Nov 2004 | B2 |
6816811 | Seem | Nov 2004 | B2 |
6823680 | Jayanth | Nov 2004 | B2 |
6826454 | Sulfstede | Nov 2004 | B2 |
6865511 | Frerichs et al. | Mar 2005 | B2 |
6925338 | Eryurek et al. | Aug 2005 | B2 |
6986138 | Sakaguchi et al. | Jan 2006 | B1 |
7031880 | Seem et al. | Apr 2006 | B1 |
7401057 | Eder | Jul 2008 | B2 |
7552467 | Lindsay | Jun 2009 | B2 |
7627544 | Chkodrov et al. | Dec 2009 | B2 |
7818249 | Lovejoy et al. | Oct 2010 | B2 |
7889051 | Billig et al. | Feb 2011 | B1 |
7996488 | Casabella et al. | Aug 2011 | B1 |
8078330 | Brickfield et al. | Dec 2011 | B2 |
8104044 | Scofield et al. | Jan 2012 | B1 |
8229470 | Ranjan et al. | Jul 2012 | B1 |
8401991 | Wu et al. | Mar 2013 | B2 |
8495745 | Schrecker et al. | Jul 2013 | B1 |
8516016 | Park et al. | Aug 2013 | B2 |
8532808 | Drees et al. | Sep 2013 | B2 |
8532839 | Drees et al. | Sep 2013 | B2 |
8600556 | Nesler et al. | Dec 2013 | B2 |
8635182 | Mackay | Jan 2014 | B2 |
8682921 | Park et al. | Mar 2014 | B2 |
8731724 | Drees et al. | May 2014 | B2 |
8737334 | Ahn et al. | May 2014 | B2 |
8738334 | Jiang et al. | May 2014 | B2 |
8751487 | Byrne et al. | Jun 2014 | B2 |
8788097 | Drees et al. | Jul 2014 | B2 |
8805995 | Oliver | Aug 2014 | B1 |
8843238 | Wenzel et al. | Sep 2014 | B2 |
8874071 | Sherman et al. | Oct 2014 | B2 |
8941465 | Pineau et al. | Jan 2015 | B2 |
8990127 | Taylor | Mar 2015 | B2 |
9070113 | Shafiee et al. | Jun 2015 | B2 |
9116978 | Park et al. | Aug 2015 | B2 |
9185095 | Moritz et al. | Nov 2015 | B1 |
9189527 | Park et al. | Nov 2015 | B2 |
9196009 | Drees et al. | Nov 2015 | B2 |
9229966 | Aymeloglu et al. | Jan 2016 | B2 |
9286582 | Drees et al. | Mar 2016 | B2 |
9311807 | Schultz et al. | Apr 2016 | B2 |
9344751 | Ream et al. | May 2016 | B1 |
9354968 | Wenzel et al. | May 2016 | B2 |
9507686 | Horn et al. | Nov 2016 | B2 |
9524594 | Ouyang et al. | Dec 2016 | B2 |
9558196 | Johnston et al. | Jan 2017 | B2 |
9652813 | Gifford et al. | May 2017 | B2 |
9753455 | Drees | Sep 2017 | B2 |
9811249 | Chen et al. | Nov 2017 | B2 |
9838844 | Emeis et al. | Dec 2017 | B2 |
9886478 | Mukherjee | Feb 2018 | B2 |
9948359 | Horton | Apr 2018 | B2 |
10055114 | Shah et al. | Aug 2018 | B2 |
10055206 | Park et al. | Aug 2018 | B2 |
10116461 | Fairweather et al. | Oct 2018 | B2 |
10169454 | Ait-Mokhtar et al. | Jan 2019 | B2 |
10171297 | Stewart et al. | Jan 2019 | B2 |
10171586 | Shaashua et al. | Jan 2019 | B2 |
10187258 | Nagesh et al. | Jan 2019 | B2 |
10417451 | Park et al. | Sep 2019 | B2 |
10514963 | Shrivastava et al. | Dec 2019 | B2 |
10515098 | Park et al. | Dec 2019 | B2 |
10534326 | Sridharan et al. | Jan 2020 | B2 |
10536295 | Fairweather et al. | Jan 2020 | B2 |
10564993 | Deutsch et al. | Feb 2020 | B2 |
10705492 | Harvey | Jul 2020 | B2 |
10708078 | Harvey | Jul 2020 | B2 |
10760815 | Janakiraman et al. | Sep 2020 | B2 |
10762475 | Song et al. | Sep 2020 | B2 |
10824120 | Ahmed | Nov 2020 | B2 |
10845771 | Harvey | Nov 2020 | B2 |
10854194 | Park et al. | Dec 2020 | B2 |
10862928 | Badawy et al. | Dec 2020 | B1 |
10921760 | Harvey | Feb 2021 | B2 |
10921972 | Park et al. | Feb 2021 | B2 |
10969133 | Harvey | Apr 2021 | B2 |
10976068 | Hallendy et al. | Apr 2021 | B2 |
10986121 | Stockdale et al. | Apr 2021 | B2 |
11016998 | Park et al. | May 2021 | B2 |
11024292 | Park et al. | Jun 2021 | B2 |
11038709 | Park et al. | Jun 2021 | B2 |
11041650 | Li et al. | Jun 2021 | B2 |
11054796 | Holaso | Jul 2021 | B2 |
11070390 | Park et al. | Jul 2021 | B2 |
11073976 | Park et al. | Jul 2021 | B2 |
11108587 | Park et al. | Aug 2021 | B2 |
11113295 | Park et al. | Sep 2021 | B2 |
11229138 | Harvey et al. | Jan 2022 | B1 |
11314726 | Park et al. | Apr 2022 | B2 |
11314788 | Park et al. | Apr 2022 | B2 |
11556105 | Cooley et al. | Jan 2023 | B2 |
11561522 | Cooley et al. | Jan 2023 | B2 |
11561523 | Cooley et al. | Jan 2023 | B2 |
11573551 | Cooley et al. | Feb 2023 | B2 |
11586167 | Cooley et al. | Feb 2023 | B2 |
20020010562 | Schleiss et al. | Jan 2002 | A1 |
20020016639 | Smith et al. | Feb 2002 | A1 |
20020059229 | Natsumeda et al. | May 2002 | A1 |
20020123864 | Eryurek et al. | Sep 2002 | A1 |
20020147506 | Eryurek et al. | Oct 2002 | A1 |
20020177909 | Fu et al. | Nov 2002 | A1 |
20030005486 | Ridolfo et al. | Jan 2003 | A1 |
20030014130 | Grumelart | Jan 2003 | A1 |
20030073432 | Meade, II | Apr 2003 | A1 |
20030158704 | Triginai et al. | Aug 2003 | A1 |
20030171851 | Brickfield et al. | Sep 2003 | A1 |
20030200059 | Ignatowski et al. | Oct 2003 | A1 |
20040068390 | Saunders | Apr 2004 | A1 |
20040128314 | Katibah et al. | Jul 2004 | A1 |
20040133314 | Ehlers et al. | Jul 2004 | A1 |
20040199360 | Friman et al. | Oct 2004 | A1 |
20050055308 | Meyer et al. | Mar 2005 | A1 |
20050108262 | Fawcett et al. | May 2005 | A1 |
20050154494 | Ahmed | Jul 2005 | A1 |
20050278703 | Lo et al. | Dec 2005 | A1 |
20050283337 | Sayal | Dec 2005 | A1 |
20060095521 | Patinkin | May 2006 | A1 |
20060136179 | Sit | Jun 2006 | A1 |
20060140207 | Eschbach et al. | Jun 2006 | A1 |
20060184479 | Levine | Aug 2006 | A1 |
20060200476 | Gottumukkala et al. | Sep 2006 | A1 |
20060265751 | Cosquer et al. | Nov 2006 | A1 |
20060271589 | Horowitz et al. | Nov 2006 | A1 |
20070028179 | Levin et al. | Feb 2007 | A1 |
20070203693 | Estes | Aug 2007 | A1 |
20070261062 | Bansal et al. | Nov 2007 | A1 |
20070273497 | Kuroda et al. | Nov 2007 | A1 |
20070273610 | Baillot | Nov 2007 | A1 |
20080034425 | Overcash et al. | Feb 2008 | A1 |
20080094230 | Mock et al. | Apr 2008 | A1 |
20080097816 | Freire et al. | Apr 2008 | A1 |
20080186160 | Kim et al. | Aug 2008 | A1 |
20080249756 | Chaisuparasmikul | Oct 2008 | A1 |
20080252723 | Park | Oct 2008 | A1 |
20080281472 | Podgorny et al. | Nov 2008 | A1 |
20090195349 | Frader-Thompson et al. | Aug 2009 | A1 |
20100045439 | Tak et al. | Feb 2010 | A1 |
20100058248 | Park | Mar 2010 | A1 |
20100131533 | Ortiz | May 2010 | A1 |
20100274366 | Fata et al. | Oct 2010 | A1 |
20100281387 | Holland et al. | Nov 2010 | A1 |
20100286937 | Hedley et al. | Nov 2010 | A1 |
20100324962 | Nesler et al. | Dec 2010 | A1 |
20110015802 | Imes | Jan 2011 | A1 |
20110047418 | Drees et al. | Feb 2011 | A1 |
20110061015 | Drees et al. | Mar 2011 | A1 |
20110071685 | Huneycutt et al. | Mar 2011 | A1 |
20110077950 | Hughston | Mar 2011 | A1 |
20110087650 | Mackay et al. | Apr 2011 | A1 |
20110087988 | Ray et al. | Apr 2011 | A1 |
20110088000 | Mackay | Apr 2011 | A1 |
20110125737 | Pothering et al. | May 2011 | A1 |
20110137853 | Mackay | Jun 2011 | A1 |
20110153603 | Adiba et al. | Jun 2011 | A1 |
20110154363 | Karmarkar | Jun 2011 | A1 |
20110157357 | Weisensale et al. | Jun 2011 | A1 |
20110178977 | Drees | Jul 2011 | A1 |
20110191343 | Heaton et al. | Aug 2011 | A1 |
20110205022 | Cavallaro et al. | Aug 2011 | A1 |
20110218777 | Chen et al. | Sep 2011 | A1 |
20120011126 | Park et al. | Jan 2012 | A1 |
20120011141 | Park et al. | Jan 2012 | A1 |
20120022698 | Mackay | Jan 2012 | A1 |
20120062577 | Nixon | Mar 2012 | A1 |
20120064923 | Imes et al. | Mar 2012 | A1 |
20120083930 | Ilic et al. | Apr 2012 | A1 |
20120100825 | Sherman et al. | Apr 2012 | A1 |
20120101637 | Imes et al. | Apr 2012 | A1 |
20120135759 | Imes et al. | May 2012 | A1 |
20120136485 | Weber et al. | May 2012 | A1 |
20120158633 | Eder | Jun 2012 | A1 |
20120259583 | Noboa et al. | Oct 2012 | A1 |
20120272228 | Marndi et al. | Oct 2012 | A1 |
20120278051 | Jiang et al. | Nov 2012 | A1 |
20130007063 | Kalra et al. | Jan 2013 | A1 |
20130038430 | Blower et al. | Feb 2013 | A1 |
20130038707 | Cunningham et al. | Feb 2013 | A1 |
20130060820 | Bulusu et al. | Mar 2013 | A1 |
20130086497 | Ambuhl et al. | Apr 2013 | A1 |
20130097706 | Titonis et al. | Apr 2013 | A1 |
20130103221 | Raman et al. | Apr 2013 | A1 |
20130167035 | Imes et al. | Jun 2013 | A1 |
20130170710 | Kuoch et al. | Jul 2013 | A1 |
20130204836 | Choi et al. | Aug 2013 | A1 |
20130246916 | Reimann et al. | Sep 2013 | A1 |
20130247205 | Schrecker et al. | Sep 2013 | A1 |
20130262035 | Mills | Oct 2013 | A1 |
20130275174 | Bennett et al. | Oct 2013 | A1 |
20130275908 | Reichard | Oct 2013 | A1 |
20130297050 | Reichard et al. | Nov 2013 | A1 |
20130298244 | Kumar et al. | Nov 2013 | A1 |
20130331995 | Rosen | Dec 2013 | A1 |
20130338970 | Reghetti | Dec 2013 | A1 |
20140032506 | Hoey et al. | Jan 2014 | A1 |
20140059483 | Mairs et al. | Feb 2014 | A1 |
20140081652 | Klindworth | Mar 2014 | A1 |
20140135952 | Maehara | May 2014 | A1 |
20140152651 | Chen et al. | Jun 2014 | A1 |
20140172184 | Schmidt et al. | Jun 2014 | A1 |
20140189861 | Gupta et al. | Jul 2014 | A1 |
20140207282 | Angle et al. | Jul 2014 | A1 |
20140258052 | Khuti et al. | Sep 2014 | A1 |
20140269614 | Maguire et al. | Sep 2014 | A1 |
20140277765 | Karimi et al. | Sep 2014 | A1 |
20140278461 | Artz | Sep 2014 | A1 |
20140327555 | Sager et al. | Nov 2014 | A1 |
20150019174 | Kiff et al. | Jan 2015 | A1 |
20150042240 | Aggarwal et al. | Feb 2015 | A1 |
20150105917 | Sasaki et al. | Apr 2015 | A1 |
20150145468 | Ma et al. | May 2015 | A1 |
20150156031 | Fadell et al. | Jun 2015 | A1 |
20150168931 | Jin | Jun 2015 | A1 |
20150172300 | Cochenour | Jun 2015 | A1 |
20150178421 | Borrelli et al. | Jun 2015 | A1 |
20150185261 | Frader-Thompson et al. | Jul 2015 | A1 |
20150186777 | Lecue et al. | Jul 2015 | A1 |
20150202962 | Habashima et al. | Jul 2015 | A1 |
20150204563 | Imes et al. | Jul 2015 | A1 |
20150235267 | Steube et al. | Aug 2015 | A1 |
20150241895 | Lu et al. | Aug 2015 | A1 |
20150244730 | Vu et al. | Aug 2015 | A1 |
20150244732 | Golshan et al. | Aug 2015 | A1 |
20150261863 | Dey et al. | Sep 2015 | A1 |
20150263900 | Polyakov et al. | Sep 2015 | A1 |
20150286969 | Warner et al. | Oct 2015 | A1 |
20150295796 | Hsiao et al. | Oct 2015 | A1 |
20150304193 | Ishii et al. | Oct 2015 | A1 |
20150316918 | Schleiss et al. | Nov 2015 | A1 |
20150324422 | Elder | Nov 2015 | A1 |
20150341212 | Hsiao et al. | Nov 2015 | A1 |
20150348417 | Ignaczak et al. | Dec 2015 | A1 |
20150379080 | Jochimski | Dec 2015 | A1 |
20160011753 | Mcfarland et al. | Jan 2016 | A1 |
20160033946 | Zhu et al. | Feb 2016 | A1 |
20160035246 | Curtis | Feb 2016 | A1 |
20160065601 | Gong et al. | Mar 2016 | A1 |
20160070736 | Swan et al. | Mar 2016 | A1 |
20160078229 | Gong et al. | Mar 2016 | A1 |
20160090839 | Stolarczyk | Mar 2016 | A1 |
20160119434 | Dong et al. | Apr 2016 | A1 |
20160127712 | Alfredsson et al. | May 2016 | A1 |
20160139752 | Shim et al. | May 2016 | A1 |
20160163186 | Davidson et al. | Jun 2016 | A1 |
20160170390 | Xie et al. | Jun 2016 | A1 |
20160171862 | Das et al. | Jun 2016 | A1 |
20160173816 | Huenerfauth et al. | Jun 2016 | A1 |
20160179315 | Sarao et al. | Jun 2016 | A1 |
20160179342 | Sarao et al. | Jun 2016 | A1 |
20160179990 | Sarao et al. | Jun 2016 | A1 |
20160195856 | Spero | Jul 2016 | A1 |
20160212165 | Singla et al. | Jul 2016 | A1 |
20160239660 | Azvine et al. | Aug 2016 | A1 |
20160239756 | Aggour et al. | Aug 2016 | A1 |
20160247129 | Song et al. | Aug 2016 | A1 |
20160260063 | Harris et al. | Sep 2016 | A1 |
20160313751 | Risbeck et al. | Oct 2016 | A1 |
20160313752 | Przybylski | Oct 2016 | A1 |
20160313902 | Hill et al. | Oct 2016 | A1 |
20160350364 | Anicic et al. | Dec 2016 | A1 |
20160357521 | Zhang et al. | Dec 2016 | A1 |
20160357828 | Tobin et al. | Dec 2016 | A1 |
20160358432 | Branscomb et al. | Dec 2016 | A1 |
20160363336 | Roth et al. | Dec 2016 | A1 |
20160370258 | Perez | Dec 2016 | A1 |
20160378306 | Kresl et al. | Dec 2016 | A1 |
20160379326 | Chan-Gove et al. | Dec 2016 | A1 |
20170006135 | Siebel | Jan 2017 | A1 |
20170011318 | Vigano et al. | Jan 2017 | A1 |
20170017221 | Lamparter et al. | Jan 2017 | A1 |
20170039255 | Raj et al. | Feb 2017 | A1 |
20170052536 | Warner et al. | Feb 2017 | A1 |
20170053441 | Nadumane et al. | Feb 2017 | A1 |
20170063894 | Muddu et al. | Mar 2017 | A1 |
20170068409 | Nair | Mar 2017 | A1 |
20170070775 | Taxier et al. | Mar 2017 | A1 |
20170075984 | Deshpande et al. | Mar 2017 | A1 |
20170084168 | Janchookiat | Mar 2017 | A1 |
20170090437 | Veeramani et al. | Mar 2017 | A1 |
20170093700 | Gilley et al. | Mar 2017 | A1 |
20170098086 | Hoernecke et al. | Apr 2017 | A1 |
20170103327 | Penilla et al. | Apr 2017 | A1 |
20170103403 | Chu et al. | Apr 2017 | A1 |
20170123389 | Baez et al. | May 2017 | A1 |
20170134415 | Muddu et al. | May 2017 | A1 |
20170177715 | Chang et al. | Jun 2017 | A1 |
20170180147 | Brandman et al. | Jun 2017 | A1 |
20170188216 | Koskas et al. | Jun 2017 | A1 |
20170212482 | Boettcher et al. | Jul 2017 | A1 |
20170212668 | Shah et al. | Jul 2017 | A1 |
20170220641 | Chi et al. | Aug 2017 | A1 |
20170230930 | Frey | Aug 2017 | A1 |
20170235817 | Deodhar et al. | Aug 2017 | A1 |
20170251182 | Siminoff et al. | Aug 2017 | A1 |
20170270124 | Nagano | Sep 2017 | A1 |
20170277769 | Pasupathy et al. | Sep 2017 | A1 |
20170278003 | Liu | Sep 2017 | A1 |
20170294132 | Colmenares | Oct 2017 | A1 |
20170315522 | Kwon et al. | Nov 2017 | A1 |
20170315697 | Jacobson et al. | Nov 2017 | A1 |
20170322534 | Sinha et al. | Nov 2017 | A1 |
20170323389 | Vavrasek | Nov 2017 | A1 |
20170329289 | Kohn et al. | Nov 2017 | A1 |
20170336770 | Macmillan | Nov 2017 | A1 |
20170345287 | Fuller et al. | Nov 2017 | A1 |
20170351957 | Lecue et al. | Dec 2017 | A1 |
20170357225 | Asp et al. | Dec 2017 | A1 |
20170357490 | Park et al. | Dec 2017 | A1 |
20170357908 | Cabadi et al. | Dec 2017 | A1 |
20180012159 | Kozloski et al. | Jan 2018 | A1 |
20180013579 | Fairweather et al. | Jan 2018 | A1 |
20180024520 | Sinha et al. | Jan 2018 | A1 |
20180039238 | Gärtner et al. | Feb 2018 | A1 |
20180048485 | Pelton et al. | Feb 2018 | A1 |
20180069932 | Tiwari et al. | Mar 2018 | A1 |
20180114140 | Chen et al. | Apr 2018 | A1 |
20180137288 | Polyakov | May 2018 | A1 |
20180157930 | Rutschman et al. | Jun 2018 | A1 |
20180162400 | Abdar | Jun 2018 | A1 |
20180176241 | Manadhata et al. | Jun 2018 | A1 |
20180198627 | Mullins | Jul 2018 | A1 |
20180203961 | Aisu et al. | Jul 2018 | A1 |
20180239982 | Rutschman et al. | Aug 2018 | A1 |
20180275625 | Park et al. | Sep 2018 | A1 |
20180276962 | Butler et al. | Sep 2018 | A1 |
20180292797 | Lamparter et al. | Oct 2018 | A1 |
20180336785 | Ghannam et al. | Nov 2018 | A1 |
20180356775 | Harvey | Dec 2018 | A1 |
20180359111 | Harvey | Dec 2018 | A1 |
20180364654 | Locke et al. | Dec 2018 | A1 |
20190005025 | Malabarba | Jan 2019 | A1 |
20190013023 | Pourmohammad et al. | Jan 2019 | A1 |
20190025771 | Park et al. | Jan 2019 | A1 |
20190037135 | Hedge | Jan 2019 | A1 |
20190042988 | Brown et al. | Feb 2019 | A1 |
20190050942 | Dalal | Feb 2019 | A1 |
20190088106 | Grundstrom | Mar 2019 | A1 |
20190094824 | Xie et al. | Mar 2019 | A1 |
20190096217 | Pourmohammad et al. | Mar 2019 | A1 |
20190102840 | Perl et al. | Apr 2019 | A1 |
20190121801 | Jethwa et al. | Apr 2019 | A1 |
20190138512 | Pourmohammad et al. | May 2019 | A1 |
20190147883 | Mellenthin et al. | May 2019 | A1 |
20190158309 | Park et al. | May 2019 | A1 |
20190163152 | Worrall et al. | May 2019 | A1 |
20190268178 | Fairweather et al. | Aug 2019 | A1 |
20190310979 | Masuzaki et al. | Oct 2019 | A1 |
20190377306 | Harvey | Dec 2019 | A1 |
20200133978 | Ramamurti et al. | Apr 2020 | A1 |
20200226156 | Borra et al. | Jul 2020 | A1 |
20200285203 | Thakur et al. | Sep 2020 | A1 |
20200336328 | Harvey | Oct 2020 | A1 |
20200348632 | Harvey | Nov 2020 | A1 |
20200387576 | Brett et al. | Dec 2020 | A1 |
20200396208 | Brett et al. | Dec 2020 | A1 |
20210042299 | Migliori | Feb 2021 | A1 |
20210043221 | Yelchuru et al. | Feb 2021 | A1 |
20210232724 | Tierney | Jul 2021 | A1 |
20210325070 | Endel et al. | Oct 2021 | A1 |
20210342961 | Winter et al. | Nov 2021 | A1 |
20210381711 | Harvey et al. | Dec 2021 | A1 |
20210381712 | Harvey et al. | Dec 2021 | A1 |
20210382445 | Harvey et al. | Dec 2021 | A1 |
20210383041 | Harvey et al. | Dec 2021 | A1 |
20210383042 | Harvey et al. | Dec 2021 | A1 |
20210383200 | Harvey et al. | Dec 2021 | A1 |
20210383219 | Harvey et al. | Dec 2021 | A1 |
20210383235 | Harvey et al. | Dec 2021 | A1 |
20210383236 | Harvey et al. | Dec 2021 | A1 |
20220066402 | Harvey et al. | Mar 2022 | A1 |
20220066405 | Harvey | Mar 2022 | A1 |
20220066432 | Harvey et al. | Mar 2022 | A1 |
20220066434 | Harvey et al. | Mar 2022 | A1 |
20220066528 | Harvey et al. | Mar 2022 | A1 |
20220066722 | Harvey et al. | Mar 2022 | A1 |
20220066754 | Harvey et al. | Mar 2022 | A1 |
20220066761 | Harvey et al. | Mar 2022 | A1 |
20220067226 | Harvey et al. | Mar 2022 | A1 |
20220067227 | Harvey et al. | Mar 2022 | A1 |
20220067230 | Harvey et al. | Mar 2022 | A1 |
20220069863 | Harvey et al. | Mar 2022 | A1 |
20220070293 | Harvey et al. | Mar 2022 | A1 |
20220121965 | Chatterji et al. | Apr 2022 | A1 |
20220138684 | Harvey | May 2022 | A1 |
20220147000 | Cooley et al. | May 2022 | A1 |
20220150124 | Cooley et al. | May 2022 | A1 |
20220215264 | Harvey et al. | Jul 2022 | A1 |
20230010757 | Preciado | Jan 2023 | A1 |
20230071312 | Preciado et al. | Mar 2023 | A1 |
20230076011 | Preciado et al. | Mar 2023 | A1 |
20230083703 | Meiners | Mar 2023 | A1 |
Number | Date | Country |
---|---|---|
2019226217 | Nov 2020 | AU |
2019226264 | Nov 2020 | AU |
2019351573 | May 2021 | AU |
101415011 | Apr 2009 | CN |
102136099 | Jul 2011 | CN |
102136100 | Jul 2011 | CN |
102650876 | Aug 2012 | CN |
104040583 | Sep 2014 | CN |
104603832 | May 2015 | CN |
104919484 | Sep 2015 | CN |
106204392 | Dec 2016 | CN |
106406806 | Feb 2017 | CN |
106960269 | Jul 2017 | CN |
107147639 | Sep 2017 | CN |
107598928 | Jan 2018 | CN |
2 528 033 | Nov 2012 | EP |
3 268 821 | Jan 2018 | EP |
3 324 306 | May 2018 | EP |
4 226 263 | Aug 2023 | EP |
H10-049552 | Feb 1998 | JP |
2003-162573 | Jun 2003 | JP |
2007-018322 | Jan 2007 | JP |
4073946 | Apr 2008 | JP |
2008-107930 | May 2008 | JP |
2013-152618 | Aug 2013 | JP |
2014-044457 | Mar 2014 | JP |
20160102923 | Aug 2016 | KR |
WO-2009020158 | Feb 2009 | WO |
WO-2011100255 | Aug 2011 | WO |
WO-2013050333 | Apr 2013 | WO |
WO-2015106702 | Jul 2015 | WO |
WO-2015145648 | Oct 2015 | WO |
WO-2017035536 | Mar 2017 | WO |
WO-2017192422 | Nov 2017 | WO |
WO-2017194244 | Nov 2017 | WO |
WO-2017205330 | Nov 2017 | WO |
WO-2017213918 | Dec 2017 | WO |
WO-2018132112 | Jul 2018 | WO |
WO-2020061621 | Apr 2020 | WO |
WO-2022042925 | Mar 2022 | WO |
WO-2022103812 | May 2022 | WO |
WO-2022103813 | May 2022 | WO |
WO-2022103820 | May 2022 | WO |
WO-2022103822 | May 2022 | WO |
WO-2022103824 | May 2022 | WO |
WO-2022103829 | May 2022 | WO |
WO-2022103831 | May 2022 | WO |
Entry |
---|
Gamer et al., EP 3 156 856 A1 , Application No. 15002934.6, Date of filing : Oct. 15, 2015 (Year: 2015). |
Lelewer, Debra A., and Daniel S. Hirschberg. “Data compression.” ACM Computing Surveys (CSUR) 19.3 (1987): 261-296. (Year: 1987). |
“vCard Ontology—for describing People and Organizations,” W3C Interest Group Note, May 22, 2014, 31 pages. |
Balaji et al, “Brick: Towards a Unified Metadata Schema for Buildings,” dated Nov. 16-17, 2016, 10 pages. |
Balaji et al, “Brick: Metadata schema for portable smart building applications,” Applied Energy, 2018 (20 pages). |
Balaji et al, “Brick: Metadata schema for portable smart building applications,” Applied Energy, Sep. 15, 2018, 3 pages, (Abstract). |
Balaji et al, “Demo Abstract: Portable Queries Using the Brick Schema for Building Applications,” BuildSys '16, Palo Alto, CA, USA, Nov. 16-17, 2016 (2 pages). |
Bhattacharya et al., “Short Paper: Analyzing Metadata Schemas for Buildings—The Good, The Bad and The Ugly,” BuildSys '15, Seoul, South Korea, Nov. 4-5, 2015 (4 pages). |
Bhattacharya, A., “Enabling Scalable Smart-Building Analytics,” Electrical Engineering and Computer Sciences, University of California at Berkeley, Technical Report No. UCB/EECS-2016-201, Dec. 15, 2016 (121 pages). |
Brick, “Brick Schema: Building Blocks for Smart Buildings,” URL: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.memoori.com/wp-content/uploads/2016/06/Brick_Schema_Whitepaper.pdf, Mar. 2019 (17 pages). |
Brick, “Brick: Towards a Unified Metadata Schema For Buildings,” URL: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://brickschema.org/papers/Brick_BuildSys_Presentation.pdf, Presented at BuildSys '16, Nov. 2016 (46 pages). |
Brick, “Metadata Schema for Buildings,” URL: https://brickschema.org/docs/Brick-Leaflet.pdf, retrieved from internet Dec. 24, 2019 (3 pages). |
Chinese Office Action on CN Appl. No. 201780003995.9 dated Apr. 8, 2021 (21 pages with English language translation). |
Chinese Office action on CN Appl. No. 201780043400.2 dated Apr. 25, 2021 (15 pages with English language translation). |
Curry, E. et al., “Linking building data in the cloud: Integrating cross-domain building data using linked data.” Advanced Engineering Informatics, 2013, 27 (pp. 206-219). |
Digital Platform Litigation Documents Part 1, includes cover letter, dismissal of case DDE-1-21-cv-01796, IPR2023-00022 (documents filed Jan. 26, 2023-Oct. 7, 2022), and IPR2023-00085 (documents filed Jan. 26, 2023-Oct. 20, 2022) (748 pages total). |
Digital Platform Litigation Documents Part 10, includes DDE-1-21-cv-01796 (documents filed Nov. 1, 2022-Dec. 22, 2021 (1795 pages total). |
Digital Platform Litigation Documents Part 2, includes IPR2023-00085 (documents filed Oct. 20, 2022) (172 pages total). |
Digital Platform Litigation Documents Part 3, includes IPR2023-00085 (documents filed Oct. 20, 2022) and IPR2023-00170 (documents filed Nov. 28, 2022-Nov. 7, 2022) (397 pages total). |
Digital Platform Litigation Documents Part 4, includes IPR2023-00170 (documents filed Nov. 7, 2022) and IPR2023-00217 (documents filed Jan. 18, 2023-Nov. 15, 2022) (434 pages total). |
Digital Platform Litigation Documents Part 5, includes IPR2023-00217 (documents filed Nov. 15, 2022) and IPR2023-00257 (documents filed Jan. 25, 2023-Nov. 23, 2022) (316 pages total). |
Digital Platform Litigation Documents Part 6, includes IPR2023-00257 (documents filed Nov. 23, 2022) and IPR 2023-00346 (documents filed Jan. 3, 2023-Dec. 13, 2022) (295 pages total). |
Digital Platform Litigation Documents Part 7, includes IPR 2023-00346 (documents filed Dec. 13, 2022) and IPR2023-00347 (documents filed Jan. 3, 2023-Dec. 13, 2022) (217 pages total). |
Digital Platform Litigation Documents Part 8, includes IPR2023-00347 (documents filed Dec. 13, 2022), EDTX-2-22-cv-00243 (documents filed Sep. 20, 2022-Jun. 29, 2022), and DDE-1-21-cv-01796 (documents filed Feb. 3, 2023-Jan. 10, 2023 (480 pages total). |
Digital Platform Litigation Documents Part 9, includes DDE-1-21-cv-01796 (documents filed Jan. 10, 2023-Nov. 1, 2022 (203 pages total). |
El Kaed, C. et al., “Building management insights driven by a multi-system semantic representation approach,” 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), Dec. 12-14, 2016, (pp. 520-525). |
Ellis, C et al., “Creating a room connectivity graph of a building from per-room sensor units.” BuildSys '12, Toronto, ON, Canada, Nov. 6, 2012 (7 pages). |
Extended European Search Report on EP Application No. 18196948.6 dated Apr. 10, 2019 (9 pages). |
Fierro et al., “Beyond a House of Sticks: Formalizing Metadata Tags with Brick,” BuildSys '19, New York, NY, USA, Nov. 13-14, 2019 (10 pages). |
Fierro et al., “Dataset: An Open Dataset and Collection Tool for BMS Point Labels,” DATA'19, New York, NY, USA, Nov. 10, 2019 (3 pages). |
Fierro et al., “Design and Analysis of a Query Processor for Brick,” ACM Transactions on Sensor Networks, Jan. 2018, vol. 1, No. 1, art. 1 (25 pages). |
Fierro et al., “Design and Analysis of a Query Processor for Brick,” BuildSys '17, Delft, Netherlands, Nov. 8-9, 2017 (10 pages). |
Fierro et al., “Mortar: An Open Testbed for Portable Building Analytics,” BuildSys '18, Shenzhen, China, Nov. 7-8, 2018 (10 pages). |
Fierro et al., “Why Brick is a Game Changer for Smart Buildings,” URL: https://brickschema.org/papers/Brick_Memoori_Webinar_Presentation.pdf, Memoori Webinar, 2019 (67 pages). |
Fierro, “Writing Portable Building Analytics with the Brick Metadata Schema,” UC Berkeley, ACM E-Energy, 2019 (39 pages). |
Fierro, G., “Design of an Effective Ontology and Query Processor Enabling Portable Building Applications,” Electrical Engineering and Computer Sciences, University of California at Berkeley, Technical Report No. UCB/EECS-2019-106, Jue 27, 2019 (118 pages). |
File History for U.S. Appl. No. 12/776,159, filed May 7, 2010 (722 pages). |
Final Conference Program, ACM BuildSys 2016, Stanford, CA, USA, Nov. 15-17, 2016 (7 pages). |
Gao et al., “A large-scale evaluation of automated metadata inference approaches on sensors from air handling units,” Advanced Engineering Informatics, 2018, 37 (pp. 14-30). |
Harvey, T., “Quantum Part 3: The Tools of Autonomy, How PassiveLogic's Quantum Creator and Autonomy Studio software works,” URL: https://www.automatedbuildings.com/news/jan22/articles/passive/211224010000passive.html, Jan. 2022 (7 pages). |
Harvey, T., “Quantum: The Digital Twin Standard for Buildings,” URL: https://www.automatedbuildings.com/news/feb21/articles/passivelogic/210127124501passivelogic.html, Feb. 2021 (6 pages). |
Hu, S. et al., “Building performance optimisation: A hybrid architecture for the integration of contextual information and time-series data,” Automation in Construction, 2016, 70 (pp. 51-61). |
International Search Report and Written Opinion for PCT Appl. Ser. No. PCT/US2017/013831 dated Mar. 31, 2017 (14 pages). |
International Search Report and Written Opinion for PCT Appl. Ser. No. PCT/US2017/035524 dated Jul. 24, 2017 (14 pages). |
International Search Report and Written Opinion on PCT/US2017/052060, dated Oct. 5, 2017, 11 pages. |
International Search Report and Written Opinion on PCT/US2017/052633, dated Oct. 23, 2017, 9 pages. |
International Search Report and Written Opinion on PCT/US2017/052829, dated Nov. 27, 2017, 24 pages. |
International Search Report and Written Opinion on PCT/US2018/024068, dated Jun. 15, 2018, 22 pages. |
International Search Report and Written Opinion on PCT/US2018/052971, dated Mar. 1, 2019, 19 pages. |
International Search Report and Written Opinion on PCT/US2018/052974, dated Dec. 19, 2018, 13 pages. |
International Search Report and Written Opinion on PCT/US2018/052975, dated Jan. 2, 2019, 13 pages. |
International Search Report and Written Opinion on PCT/US2018/052994, dated Jan. 7, 2019, 15 pages. |
International Search Report and Written Opinion on PCT/US2019/015481, dated May 17, 2019, 78 pages. |
International Search Report and Written Opinion on PCT/US2020/058381, dated Jan. 27, 2021, 30 pages. |
Japanese Office Action on JP Appl. No. 2018-534963 dated May 11, 2021 (16 pages with English language translation). |
Koh et al., “Plaster: An Integration, Benchmark, and Development Framework for Metadata Normalization Methods,” BuildSys '18, Shenzhen, China, Nov. 7-8, 2018 (10 pages). |
Koh et al., “Scrabble: Transferrable Semi-Automated Semantic Metadata Normalization using Intermediate Representation,” BuildSys '18, Shenzhen, China, Nov. 7-8, 2018 (10 pages). |
Koh et al., “Who can Access What, and When?” BuildSys '19, New York, NY, USA, Nov. 13-14, 2019 (4 pages). |
Li et al., “Event Stream Processing with Out-of-Order Data Arrival,” International Conferences on Distributed Computing Systems, 2007, (8 pages). |
Nissin Electric Co., Ltd., “Smart power supply system (SPSS),” Outline of the scale verification plan, Nissin Electric Technical Report, Japan, Apr. 23, 2014, vol. 59, No. 1 (23 pages). |
Passivelogic, “Explorer: Digital Twin Standard for Autonomous Systems. Made interactive.” URL: https://passivelogic.com/software/quantum-explorer/, retrieved from internet Jan. 4, 2023 (13 pages). |
Passivelogic, “Quantum: The Digital Twin Standard for Autonomous Systems, A physics-based ontology for next-generation control and AI.” URL: https://passivelogic.com/software/quantum-standard/, retrieved from internet Jan. 4, 2023 (20 pages). |
Quantum Alliance, “Quantum Explorer Walkthrough,” 2022, (7 pages) (screenshots from video). |
Results of the Partial International Search for PCT/US2018/052971, dated Jan. 3, 2019, 3 pages. |
Sinha, Sudhi and Al Huraimel, Khaled, “Reimagining Businesses with AI” John Wiley & Sons, Inc., Hoboken, NJ, USA, 2021 (156 pages). |
Sinha, Sudhi R. and Park, Youngchoon, “Building an Effective IoT Ecosystem for Your Business,” Johnson Controls International, Springer International Publishing, 2017 (286 pages). |
Sinha, Sudhi, “Making Big Data Work For Your Business: A guide to effective Big Data analytics,” Impackt Publishing LTD., Birmingham, UK, Oct. 2014 (170 pages). |
The Virtual Nuclear Tourist, “Calvert Cliffs Nuclear Power Plant,” URL: http://www.nucleartourist.com/us/calvert.htm, Jan. 11, 2006 (2 pages). |
University of California At Berkeley, EECS Department, “Enabling Scalable Smart-Building Analytics,” URL: https://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-201.html, retrieved from internet Feb. 15, 2022 (7 pages). |
Van Hoof, Bert, “Announcing Azure Digital Twins: Create digital replicas of spaces and infrastructure using cloud, AI and IoT,” URL: https://azure.microsoft.com/en-us/blog/announcing-azure-digital-twins-create-digital-replicas-of-spaces-and-infrastructure-using-cloud-ai-and-iot/, Sep. 24, 2018 (11 pages). |
W3c, “SPARQL: Query Language for RDF,” located on The Wayback Machine, URL: https://web.archive.org/web/20161230061728/http://www.w3.org/TR/rdf-sparql-query/), retrieved from internet Nov. 15, 2022 (89 pages). |
Wei et al., “Development and Implementation of Software Gateways of Fire Fighting Subsystem Running on EBI,” Control, Automation and Systems Engineering, IITA International Conference on, IEEE, Jul. 2009 (pp. 9-12). |
White et al., “Reduce building maintenance costs with AWS IoT TwinMaker Knowledge Graph,” The Internet of Things on AWS—Official Blog, URL: https://aws.amazon.com/blogs/iot/reduce-building-maintenance-costs-with-aws-iot-twinmaker-knowledge-graph/, Nov. 18, 2022 (10 pages). |
Zhou, Q. et al., “Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams,” Further Generation Computer Systems, 2017, 76 (pp. 391-406). |
U.S. Appl. No. 17/566,029, filed Jul. 6, 2023, Passivelogic, Inc. |
U.S. Appl. No. 17/567,275, filed Feb. 9, 2022, Passivelogic, Inc. |
U.S. Appl. No. 17/722,115, filed Feb. 9, 2022, Passivelogic, Inc. |
Number | Date | Country | |
---|---|---|---|
20210382861 A1 | Dec 2021 | US |