ADAPTIVE VENTILATION SYSTEM

Abstract

An adaptive ventilation system directs air within an environment. The system includes vents with flaps configured to be progressively actuated to redirect air from the vent into the environment at a different angle and speed. The vents each include a processing core and are in communication with a plurality of sensors and a central hub. At least one return is configured to control air flow from the environment into a return duct. The return includes a processing core and is in communication with a plurality of sensors and the central hub.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to and the benefit of U.S. Provisional Patent Application No. 62/715,455, filed on Aug. 7, 2018, and titled “ADAPTIVE VENTILATION SYSTEM”, the contents of which are incorporated herein by reference as though fully set forth herein.

FIELD OF THE TECHNOLOGY

HVAC systems generally work as follows: they collect air from some space (e.g. a room) in an environment; they heat or cool the air; they return the heated or cooled air to the space. Devices in a given HVAC system tend to include a set number of vent units, X, for a given number of returns, Y. One problem that arises is that often these returns are not properly positioned due to construction limitations or contractor error, which leads to a less efficient air retrieval capacity. Also, because of the returns' positioning relative to vents, the returns may receive already cooled/heated air from neighboring areas, resulting in a false reading of the environmental temperature within the HVAC unit.

A large amount of the typical monthly electricity and gas bill goes to HVAC systems heating or cooling areas based on the weather outside and one input setting selected by a user. Current systems are not ready to fully control air diffusion and they lack any smart decision making at a unit level because of the rigid nature of the existing vents. Many spaces will be cooled down or heated up too much in comparison to other spaces because of the way the air is pushed through the ducted system, which is mostly based on the first reached first served method. That is, the closest vent to the main duct body will get most of the air through its duct terminal and the vent that is the furthest away from the main duct body will get the least amount of the air from the duct terminal with minimal air diffused through this vent. This will make only certain places in the controlled space comfortable and in accordance with the set temperature (through a thermostat or other means), while the rest of the space is either too low or it is too high in temperature, making living and doing activities in the space uncomfortable.

The existing vents on the market will only let users manually control the air flow volume to the unit (which usually gets set by the owner, the HVAC company or the building maintenance team), that will result in poor environmental conditions within the given space, or room. Some of the vents are built as one rigid piece that cannot be adjusted, having certain fixed dampers installed in the ceiling or floors of the buildings to regulate the percentage of air flow through the ducts.

In the last 25 years, industrial vents for ducted systems have not changed and the residential vent improvements have not been significant, lacking precision, functionality and design. Most important is that this system is not capable to auto-calibrate, that is to adjust for both the seasonal temperature and humidity dynamic changes, and the temperature requirements for the interior of the building, preset by the users or defaulted by certain industry standards (like ASHRAE table of temperature settings for different categories of spaces).

BACKGROUND OF THE TECHNOLOGY

The subject technology resolves the inefficiencies of current systems with the adaptive vents and returns that will detect temperature, humidity, barometric pressure and air quality at a unit level, as well as the temperature at opposite side from the unit (if the unit is in the ceiling it will detect the temperature at the ground level, and vice-versa), and more.

The subject technology relates to systems, apparatus, and methods for enhancing a ducted cooling and heating system (HVAC). The subject technology is applicable in spaces where there is a heating and cooling system installed and built to deliver the air through a series of ducts to different locations within a building, using end openings called vents. Apparatus in accordance with the subject technology work together in order to calibrate and manipulate air flow within a given space. This includes the vents and custom built motherboards with a multitude of sensors attached (also known as a “SmartCore” or “processing core”, discussed in more detail below) on each vent. Methods for air diffusion and distribution and algorithms enhance the capabilities of this system using typical machine learning, improving functionality based on collected data.

Systems in accordance with the subject technology learn about the environmental changes, and work together to make smart decisions on controlling air flow, while working in perfect harmony with the existing HVAC system (as per ASHRAE practices) and increasing its life expectancy. This will result in an improvement of the overall air distribution, calibration and diffusion for higher user satisfaction.

The data collected by these systems and the algorithm perfecting mechanisms may be used in future system updates to trigger automatic calibration, detection and issue resolution capabilities. The same data can be used to extrapolate certain system disorders, system maintenance or system upgrade requirements which will give the building owner a better planning tool to manage certain costs.

The subject technology involves configuring how these systems work at an individual vent level, configuring the connections between components at a mesh network level, and configuring how clusters of devices hook up to certain main nodes, called hubs, that will interoperate with the components of an HVAC system.

BRIEF DESCRIPTION OF THE DRAWINGS

So that those having ordinary skill in the art to which the disclosed system pertains will more readily understand how to make and use the same, reference may be had to the following drawings.

FIG. 1 is a block diagram of a mesh network of a system in accordance with the subject technology.

FIG. 2 is a block diagram of the initialization process of a new device being added to a network in accordance with the subject technology.

FIG. 3 is a flowchart of device calibration in accordance with the subject technology.

FIG. 4 is a block diagram of the decision making of a device in accordance with the subject technology.

FIG. 5 is a schematic diagram showing connectivity between various devices in accordance with the subject technology.

FIG. 6 is a block diagram of the workflow of a processing hub in accordance with the subject technology.

FIG. 7a shows simplified cross sections of the air flow through a vent in accordance with the subject technology during heating of a space.

FIG. 7b shows simplified cross sections of the air flow through a vent in accordance with the subject technology during cooling of a space.

FIG. 7c shows cross sections of the gate and flap control of a vent in accordance with the subject technology.

FIGS. 8a-8c show stepwise installation of a vent in accordance with the subject technology.

FIG. 9a is a bottom perspective view of a fully installed vent in accordance with the subject technology.

FIG. 9b is a top perspective view of a fully installed vent in accordance with the subject technology.

FIG. 10 is an exploded view of a vent in accordance with the subject technology.

FIG. 11 is an exploded view of a uni-body of a vent in accordance with the subject technology.

FIG. 12 is an exploded view of a control subassembly of a vent in accordance with the subject technology.

FIG. 13 shows the building of a uni-body of a vent in accordance with the subject technology.

FIG. 14 is a space with an exemplary HVAC setup in accordance with the subject technology.

FIG. 15 is a space with another exemplary HVAC setup in accordance with the subject technology.

FIG. 16 is a space with another exemplary HVAC setup in accordance with the subject technology.

FIG. 17 is a space with another exemplary HVAC setup in accordance with the subject technology.

FIG. 18 is a space with another exemplary HVAC setup in accordance with the subject technology.

FIG. 19 is a block diagram of various exemplary components of a processing core in accordance with the subject technology.

DETAILED DESCRIPTION

The subject technology overcomes many of the prior art problems associated with HVAC systems. The advantages, and other features of the systems and methods disclosed herein, will become more readily apparent to those having ordinary skill in the art from the following detailed description of certain preferred embodiments taken in conjunction with the drawings which set forth representative embodiments of the subject technology. Like reference numerals are used herein to denote like parts. Further, words denoting orientation such as “upper”, “lower”, “distal”, and “proximate” are merely used to help describe the location of components with respect to one another. For example, an “upper” surface of a part is merely meant to describe a surface that is separate from the “lower” surface of that same part. No words denoting orientation are used to describe an absolute orientation (i.e. where an “upper” part must always be on top).

In brief summary, the subject technology relates to adaptive devices (i.e. vents and returns) which adapt their functionality to transform the environmental settings of one or multiple spaces in a building, based on default settings (as recommended by ASHRAE standards) or based on user desired input settings, using methods like automatic air calibration for the entire space. The returns communicate with the vents in one or more rooms in the environment to ensure that each zone has its own priority set when initiating the process of circulating the air, either for the purpose of heating/cooling or just for dehumidifying. The vents and returns rely on a set of sensors to collect environmental data from surroundings. The data is fed to the machine learning models, improving the overall software of the HVAC system for a better and more efficient HVAC system performance. Since the vents work so closely with the returns, the system ensures the volume of displaced air from a specific area is in conformity with the ASHRAE HVAC standard specifications. By controlling the air flow between vents and/or returns, a targeted temperature is reached faster (cooling or heating), thus extending the life of the entire HVAC system overall.

Referring now to FIG. 1, a block diagram of a mesh network 100 of adaptive devices 102 is shown. The mesh network 100 is a high level representation of exemplary communication between the components of a system in accordance with the subject technology. The devices 102 interact with a SmartHub unit 104 and a cloud server 106. The SmartHub 104 (or “processing hub”), is a central computer which controls the system of the subject technology. The adaptive devices 102 are either vents for directing air from an air duct into a space or returns for directing air back from a space to a return duct. The devices 102 are “smart”, meaning they are connected to a processor, memory, and the like. For example, each device 102 can include a “SmartCore” which includes a processor, memory, and programming to cause the device 102 to carry out the functions described herein (“SmartCores” are discussed in more detail with respect to FIG. 19 below). In particular, the devices 102 include computer and electrical components configured to effect changes in the physical components of the devices 102 based on input received. In some cases, the devices 102 can also include, or be connected to, input/output devices, such as sensors, for receiving additional information. The devices 102 communicate with one another to increase the coverage area of the mesh network 100, meaning that a device 102 considered out of range from a physical connectivity perspective (physical direct connection out of bounds limit) will be able to communicate with the SmartHub 104, through the mesh network 100. This provides a way to send data to the hub 104 from any corner of this topology.

The SmartHub 104 also collects all the different data points broadcasted by the devices 102, creating an atmospheric environment variation timeline that will then be sent over to the cloud server 106, which is connected to infrastructure for further analysis. Further analysis can be accomplished through algorithm improvement and coefficients recalculations.

Referring now to FIG. 2, a block diagram of a method of adding a new device 102 to a network, such as the network 100 shown in FIG. 1, is shown. First, a new device 102 is installed into a duct of an existing HVAC system. Once the new device 102 has been installed into the duct system, and the power is turned on for the unit, the initialization phase 201A will begin for the aforementioned unit.

After initialization, at 201B, the device 102 will broadcast its ID and meta information to the existing mesh network 100 where the information will be sent to the SmartHub 104 at 201C for authorization purposes. The SmartHub 104 registers the new device 102 into its device registry and sends a network connection token and registration acknowledgement to the mesh network 100 at 201D. Next, at 201E, the device 102 is identified and a message is broadcast to the new device at 201E, indicating the connection to the SmartHub 104. Once the new device 102 receives the network connection token and the registration acknowledgement, it will finalize the installation process and send an initial diagnostic message to the SmartHub 104, at 201F, that will serve as a first recording identifier for the device 102.

Such initial message can be delivered over secure communication protocols like HTTPS in a JSON format that would be similar to the following schema:

{
“$schema”: “http://json-schema.org/draft-06/schema#”,
“type”: “object”,
“properties”: {
“message”: {
“$id”: “a32831af9c78603cb2176b13899f11be”,
“timestamp”: “2018-03-24 9:54:36”,
“context”: “init”
},
“device”: {
“$id”: “123”,
“type”: “vent”,
“hardware”: {
“model”: “v12-36b”,
“ip”: “1.0.0.123”,
“title”: “vent123”,
“description”: “Vent close to the window near the cubicle section
143B”,
“status”: “ok”,
“communication”: {
“channels”: {
“wifi”: “”,
“bluetooth”: “”,
“zigbee”: “”
}
},
“sensors”: {
“airflow”: “”,
“airquality”: “”,
“ambientlight”: “”,
“barometer”: “”,
“co”: “”,
“co2”: “”,
“humidity”: “”,
“infrared”: “”,
“motion”: “”,
“pressure”: “”,
“temperature”: “”,
“vibration”: “”
},
“actuators”: {
“motor1”: “0”,
“motor2”: “0”
}
},
“software”: {
“versioning”: {
“current”: “v1.0.35”,
“previous”: “v1.0.34”
}
}
}
}
}

When a new device 102 is initialized and the diagnostic message is sent at 201F, the SmartHub 104 will synchronize its device list with the cloud based service provider 106 at 211A. The cloud based service provider 106 then acknowledges the new device registration and sends a confirmation back to the SmartHub 104 to close the new device registration loop at 211B.

Next, at 212A, the device 102 starts collecting data from sensors and records the data locally as a first point of reference. After recording data for a few minutes, the device 102 will start the auto calibration process at 212B. During the auto calibration process 212B, the device 102 physical components can be controlled to affect ventilation of the HVAC system. For example, the device 102 can be a vent with orifices and flaps which direct airflow from a duct through the vent. During the auto calibration process 212B, the opening of orifices and tilt of the flaps can be modified to get the desired air flow through the vent, into the space in the surrounding environment. The relevant sensor data is sent to the SmartHub 104 over secure protocol like HTTPS in a JSON format that would be similar to this schema:

{
“$schema”: “http://json-schema.org/draft-06/schema#”,
“type”: “object”,
“properties”: {
“device”: {
“$id”: “123”,
“type”: “vent”,
“timestamp”: “2018-03-24 9:54:36”,
“cluster”: “34”,
“sensors”: {
“airflow”: “2 cmm”,
“airquality”: “10”,
“ambientlight”: “1”,
“barometer”: “”,
“co”: “0.0”,
“co2”: “0.0”,
“humidity”: “”,
“infrared”: “22C”,
“motion”: “978”,
“pressure”: “988Hg”,
“temperature”: “22C”,
“vibration”: “0.1”
},
“actuators”: {
“motor1”: “90”,
“motor2”: “100”
}
}
}
}

The software for each device 102 is built on a set of formulas and coefficients for closing and opening the air flow to each individual vent or return unit. The device sensors will rely on data read at regular intervals or on alerts related to considerable changes in the environmental readings. After collecting essential data for a considerable amount of time, machine learning or deep learning generated algorithms (formulas and coefficients) will get updated, to achieve the optimal energy consumption required for the building layout. There are two ways in which the software on the devices are improved. The first is by upgrading the actual code that makes all components interoperate seamlessly. The second is by upgrading the algorithmic formulas and/or coefficients in the main software, to adjust the units' performance.

Upgrades to machine and deep learning happens within the cloud, or through a processor linked to the cloud. In general, the processing power required for machine learning and deep learnings is too great to be provided at the device or hub level. There are many ways in which machine learning and deep learning work to achieve a more effective system, some examples of which are described below.

For example, a device can use an algorithm, formula, and/or coefficient to open and close the vent which initially will be established at the time of the full system calibration process of the units. In time, based on the data gathered and from different system calibrations, the precision of the algorithm, formula, and/or coefficient will get better and better. The vents and returns, being “smart”, will receive the updated algorithm, formula, and/or coefficient from the cloud services themselves as an update or upgrade. The firmware of the vents, SmartCores, SmartHubs, and the like can then be upgraded. In this way, upgrading the algorithms, formulas, and/or coefficients improves the software running on vents, SmartCores, SmartHubs, and the like, which is dynamic. Thus, the components can be upgraded over time based on the machine learning and deep learning results.

Referring now to FIG. 3, a flowchart of a process of device calibration is shown generally at 300. The process 300 involves collecting and verifying data for false positives before engaging the rest of the components of the systems.

The process 300 begins, at step 301, when sensor data is read in response to a sensor data retrieval request. Once the data is retrieved, an algorithm analyzes whether the reading is positive and whether action is required at step 302. The reading is positive, meaning action is required, when there is a temperature anomaly in the area of the device. When a temperature anomaly is detected, the unit will send the data to the hub for processing, analysis, and storage at step 303, while also initiating the calibration protocol at step 304. An algorithm then determines whether the particular unit that detected the temperature anomaly can recover the temperature deficiency by itself, at step 305. If the device can recover the temperature deficiency by itself, the device is caused to do so at step 308. If it cannot, then other devices, such as vents, in the vicinity will be notified of the required action at step 306. At step 307, each of those devices then starts their own process of retrieving data (e.g. step 301), notifying the hub, calibrating the units and notifying the closest units, etc., in accordance with the process 300.

Referring now to FIG. 4, the decision making of a device based on the sensor data received, in accordance with the subject technology, is shown at 400. At specific time intervals the vent wakes up and requests a complete sensors readout at 401. If the vent recorded previous data, it can compare and identify considerable variations (for example a ±1.5 F difference in temperature from the previous reading) and take the appropriate action. If the vent reads the sensors data for the first time, it will save it locally at step 401A and wait for a specific amount of time. After the time has passed, the data collection process re-initializes at step 402, and the vent determines if there is a considerable enough variation in the readouts. If there is an insignificant variation in the readouts, the system waits a few minutes at step 416 before taking another sensor readout at 401.

If the data variation is confirmed, then at step 404 the vent checks to see if there is enough air flow in the duct system to start performing the calibration protocol. If there is not enough air circulating through the duct system, then the hub is notified to request an air flow increase from the HVAC system, at step 405, in order to complete the calibration of the system and resolve the detected deficiencies. The system then waits a few minutes at step 417 before again checking if there is enough airflow at step 404.

If there is enough air flow in the ductwork to perform the calibration, the next step is to retrieve air flow data from the corresponding return. At step 406, a determination is made as to whether air from the space is being retrieved from the closest return in the HVAC system. If air is being retrieved through the return, a complimentary check is done, at step 408, to see if that air shows similar variations to those detected by the sensors for the vent that initiated the process. If the air returned from the return closest to the area does not detect similar variations to those detected by the vent, then the system waits for a few minutes, at step 409, before restarting the process at step 401. This helps limit false positive readings.

If no air is retrieved from the specific space where the temperature difference was recorded, and if the HVAC system does not bring more air volume from outside, then a request is sent to the SmartHub, at step 407, to identify, wake up, initiate data retrieval process and start calibration process for the closest return unit. At step 407A, the system waits a few minutes. Then, step 406 of checking for air retrieved through the closest return is repeated.

If, at step 406, it is determined that air is being retrieved from the specific space where the temperature difference was recorded and if, at step 408, is determined that there is a considerable difference in sensor readings, then the system proceeds to step 410. At step 410, a check is performed to see if the air pressure in the duct system near the vent is sufficient to satisfy the calibration process for that vent in the specific space.

If the air pressure is not sufficient, the return notifies the SmartHub to request air volume increase from the HVAC system at step 411. Once this process is complete the system waits for a specific time interval at step 413, before again testing for sufficient air pressure required to perform calibration at step 410. The system can also include an air particle sensor. When the air particle sensor measures a high level of particles and/or contamination, the SmartHub requests the HVAC system to pull-in more fresh air from the outside, if this feature is available from an HVAC installation/setting. In this case the return stays open at max flow for the time interval needed to clean the indoor air in that specific area.

At step 410, if the air pressure is sufficient, all the vents adjacent to and including the one that identified the problem start compensating for the air difference at step 412. The vents send all the collected data and flow parameters to the SmartHub for processing, storage and analysis at step 414. After the processing, storage, and analysis are complete, at step 415 the SmartCore goes into sleep mode while the orifices stay opened, allowing air delivery to the space. The system then waits for a set interval, at step 409, before a new sensor readout is conducted at step 401.

Referring now to FIG. 5, a schematic diagram 500 shows interactions between various components of a system in accordance with the subject technology. A SmartHub 501 acts as the base unit for all the SmartCores 502a (central part of the smart returns and smart vents), LIDAR 502b (described in more detail below), and other hardware units 502c that are placed in the room and connected to the system. The SmartHub 501 is also directly connected to the HVAC system's main controller units 503a, secondary monitoring systems 503b, controllers 503c, and/or other web based interfaces 503d.

The SmartHub 501 includes a commercial board available off the shelf that has different types of connectors, joiners and interfaces, which make the SmartHub 501 as versatile as possible when it comes to connecting it to the different types of commercially available HVAC units. The SmartHub 501 also has the capability to communicate directly with smart thermostats that have internet based API's and control all aspects of the HVAC system, not only the on or off properties of the HVAC unit itself. The SmartHub 501 communicates with the other components of the system, triggers events, and updates different components of the systems as needed. In some cases, the SmartHub is the only hardware that communicates with the cloud system 504, stores permanent data, and runs the machine learning and deep learning algorithms on the data received.

Referring now to FIG. 6, layers of the SmartHub unit's procedural flows are shown. The SmartHub provides a secure methodology for inputs and outputs using SSL/HTTPS protocols 601 or any other third party protocol required by future 3rd party hardware on information received. Once input data securely reaches the SmartHub, it is classified in one of the available categories and handled appropriately. A device initiation workflow 602 causes new devices to be added 602a, reset 602b, updated 602c, or removed 602d from the system. Input data categorized as raw sensor data is handled by the data collection workflow in accordance with the other processes discussed herein.

When a software update is available for the SmartCore or SmartHub, the software workflow 604 is responsible for pushing the updates to the necessary endpoints, after saving the latest stable version 604a, the latest software version installed 604b, workflows, and configurations. If the SmartCore or the SmartHub are unstable after the update, the SmartHub software workflow 604 initiates a quick recovery process to stabilize the corresponding units.

The instructions table workflow 605 is responsible for managing the actions rulesets 605a and data exchange interfaces for the modulators, thermostats, or other third party devices 605b. The rulesets 605a include the algorithms, formulas, and/or coefficients which are part of various components of the system and improved through machine and deep learning, as discussed above. These interfaces are kept up to date based on hardware and vendor requirements.

The logging workflow 606 keeps track of all data received by the SmartHub, classifying and organizing it according to an internal computational table. This data is regularly sent, through a security layer 608, to the cloud infrastructure 609 for storing and usage in the process of training the machine learning 609e and deep learning 609f algorithms, and also for analytics 609k.

The web panel workflow 607 manages the web dashboards for the three predefined types of users of the system. The building owner portal 607a gives an owner of the space in which the system is being implemented an overall look on the system's performance in the space (e.g. within the building). The owner can create new user groups such as third party portals 607b which represent people, such as renters, who occupy parts of the space. The third party portals 607b allow people within the space to view their consumption patterns, the flow of people within the space, or other relevant data. The service company portal 607c allows the HVAC system servicing company to monitor all errors, warnings and logs for all devices within the HVAC setup.

The cloud infrastructure 609 provides a large set of services that includes data storage 609a, services 609b, workflows/steps 609c, standards/defaults 609d, machine learning service 609e, deep learning 609f, IoT services 609g, updating functions 609h, generators 609i, third party device interface libraries 609j, and other services as needed. All these layers work together and they represent the software foundation of the system of the subject technology.

Referring now to FIGS. 7a-7b, simplified representations of the flow control principle for air through a vent during states of an HVAC system in accordance with the subject technology are shown. These representations show the ways in which the vents can control both the volume and direction of air flow from a ventilation duct into a zone within a space (e.g. a room). FIG. 7a shows a heating system while FIG. 7b shows a cooling system. The graphs show exemplary air flow coming through vents within the system depending on the current positioning of the gates 703 and flaps 704. In general, the volume of air flow into the vent is controlled by a gate 703 while properties of the air flow out of the vent, such as speed and direction, are controlled by a flap 704. The positioning of the gate 703 and flap 704 can be changed depending on the desired air flow through the vent.

The vents include gates 703 fixed between a vent body 701 and a gate back shield 702. The gates 703 can be actuated to open, allowing airflow through the vent, or actuated to a closed position to prevent airflow from the duct through the vent. In this way, the position of the gate 703 controls the volume of air allowed through the vent terminal. Graphs 705 and 708 show the gate 703 in a fully closed position, blocking all air flow through the vent. Graphs 706 and 709 show the gate 703 in a partially opened position, allowing some air flow through the vent while blocking some air flow. Finally, graphs 707 and 710 show the gate 703 in a fully opened position allowing full air flow through the vent.

The air flaps 704 can be actuated independently of the gates 703 to control air flow, direction, and/or speed. In most cases, in the heating state, there is less of a need to adjust the air flow direction, and increase the air speed by using the flaps 704, because of the hot air properties. If hot air is pushed into a cool room, the hot air slowly descends as it cools down, heating up the air in the room. If hot air is pushed into a warm room, the hot air travels further away in the room. However, there can be a significant need to affect the way air is moved from the vent into the space during a cooling application, as in FIG. 7b. Cold air has the tendency to descend faster in a warm environment. The flaps 704 are typically curved such as in an arcuate shape, or at least include a curved portion, and can be in a somewhat semi-circular or semi-cylindrical shape, to direct air flow from the vent into the space. As the flaps 704 are actuated, the curved flaps 704 rotate to direct air in a different direction. For example, in some cases, the flaps 704 can be curved such that the further they are actuated, the more they direct air in the direction of a plane parallel to the vent (e.g. parallel to the ceiling). This can cause the air to be spread across the space more effectively. Similarly, if the flaps 704 are rotated the other way, the curved flaps 704 rotate back into the opening and direct the air in a direction more perpendicular to the plane (e.g. down into the room rather than parallel to the ceiling). In this way, controlling the flaps 704 can control the extent to which air is spread throughout the space, or directed more locally to the vent but further down into the room. Graphs 705-707, show the flaps 704 in a semi-retracted state while graphs 708-710 show the flaps 704 rotated to extend from the vent, directing air across the ceiling of the space (assuming the vent is fixed to the ceiling). In general, air is kept within a distance of about two feet from the ceiling to minimize any draft felt by the occupants of the room and to maximize comfort.

Additionally, or alternatively, during both heating and cooling, the air flow can be directed in angle to flow as parallel to the ceiling as possible, with the flaps 704 being used to regulate the speed of the air flow through the vent. To that end, the flaps 704 can include an extension 720, which in this case is a wide central section of the flap 704. While the flap 704 typically forms a channel through the vent, the extension 720 narrows this channels at one cross section, that cross section being defined entirely between the extension 720 and the vent body 701. As the flaps 704 are then actuated to extend further out from the vent, the extension 720 moves closer to the vent body 701, narrowing the air passage between them even further at that cross section. This causes the air flowing between the flap 704 and the vent body 701 to move more quickly and travel further from the vent. Since cold air descends faster, the flaps 704 can be actuated further in a cooling application such that air travels through the vent at a higher speed, allowing it to travel further from the vent as needed. Therefore in some cases, the flaps 704 can include an extension 720 in lieu of having a curved portion, and speed of air through the vent can be regulated rather than the angle of the air. In other cases, both can be regulated by a curved flap 704 which also includes an extension 720.

Referring now to FIG. 7c, a cross sectional view of an exemplary vent is shown. FIG. 7c shows how the gates 703 and flaps 704 for a particular vent 712, 713 are actuated. Each vent 712, 713 has multiple gates 703 and flaps 704 which can be used to send air out at multiple locations on the vent 712, 713 and in different areas or directions. Vent 712 has gates 703 in a completely closed position with flaps 704 completely receded into the vent 712. Vent 713 has all gates 703 in a semi-open position to allow roughly 50% air flow through the vent 713. Each flap 704 is pivotally attached to a lever arm 711. The lever arm 711 can be actuated downward, forcing the curved flaps 704a, 704b (generally 704) into contact with curved sections 714. In the example of the vent 713, some flaps 704a remain retracted into the vent 713, while other flaps 704b have been actuated downward. In this configuration, the flaps 704b direct air in a direction more parallel to the opening of the vent 713 (e.g. close to the ceiling).

Referring now to FIGS. 8a-8c, an exemplary vent 800 is shown in various stages of installation. In FIG. 8a, the vent body 801 is inserted into a duct opening of the HVAC system. A wall level plate 802 is attached between the vent body 801 and the ceiling or wall to hide any gaps between the vent and the opening. In FIG. 8b, a vent assembly frame 803 is installed. As can be seen in FIG. 8c, the vent assembly frame 803 includes an opening 805. The opening 805 allows for insertion and attachment of the SmartCore 804. Within the opening, the SmartCore 804 connects to other devices (not distinctly shown) included as part of the vent 800, including harnesses (duct air sensors, gate and flap control motors). The vent 800 is configured such that after insertion of the SmartCore 804 into the opening 805, a push-and-lock mechanism allows the SmartCore 804 to be locked in place within the vent 800. Once the SmartCore 804 is attached within vent 800, the vent 800 can be booted up and the setup of the entire vent 800 can be initiated.

Referring now to FIGS. 9a and 9b, perspective views of a fully installed vent 900 in accordance with the subject technology are shown. Even though the completely installed vent 900 is fully functional and visually appealing, it can further be customized to blend in with the architectural elements of the building of which the system is a part of. The vent 900 includes functional side plates 901 and an ornamental front face plate 902. The functional side plates 901 cover mounting screws of the vent while the cover plates 902 are ornamental only. The side plates 901 and front face plate 902 can contain snap-on multipoint magnetic couplers which can attach to corresponding magnetic couplers in the vent front face. The custom designed face plates 902 can be custom colored so they can show different design patterns or shapes and can bare different branding as needed. This allows the vent 900 to be easily adapted to fit in with the appearance of any environment.

Referring now to FIG. 10, an exploded view of the various parts of a vent 1000, in accordance with the subject technology is shown. FIG. 10 shows some of the major internal sub-assembly and components of the vent 1000. These include a uni-body 1001, a control subassembly 1002, a gate cover 1003, and a front flap support cover 1004. The uni-body 1001 is the main frame of the vent 1000 assembly and encases the gate control mechanism. The gate cover 1003 works to protect the control subassembly 1002 and support the connection of the control subassembly 1002 to sensors mounted inside an adjacent HVAC duct. The front flap support cover 1004 supports and guides the air flow control flaps while also hiding and protecting a gate mechanism actuator 1002a and the connection for the SmartCore. The gate actuator 1002a was designed to be part of the vent flaps and gate control subassembly 1002 in order to minimize and simplify the assembly process. As such, subassembly 1002 includes two rotational actuators, each equipped with its own driving gear. The 1002a gate mechanism actuator engages the driven large gear when the subassembly 1002 is assembled inside the uni-body 1001.

Referring now to FIG. 11, an exploded view of the major components of the uni-body 1001 subassembly that houses the gate control mechanism is shown. The uni-body 1001 includes a cam type mechanism designed to use four gate blades 1103, a guiding central housing plate 1102 and a cam-gear 1104. While four gate blades 1103 are shown in the given example, other numbers of gate blades are used in different embodiments and the uni-body 1001 need not use exactly four gate blades. The electric actuator 1002a (e.g. from FIG. 10) passes through one of the openings of the housing plate 1102 and engages the cam-gear 1104 which transforms rotational movement into linear motion of the gate blades 1103. Different types of vent terminals and vent returns can have different configuration of these gate blades 1103 and actuators 1002a depending entirely on the application and specific design standard.

Referring now to FIG. 12, an exploded view of the major components of the control subassembly 1002 is shown. The control subassembly 1002 controls both the gate opening and the air deflector flap mechanisms. This control subassembly 1002 uses two actuators 1002a and 1203b (1002a being shown in FIG. 10), that turn the cam-gears 1104 (FIG. 11) and 1203d by engaging the common design driving gear 1203c. While the gate opening actuator 1002a is installed directly on the control guiding housing frame 1201, the second actuator 1203b that controls the position of the air flow deflector flaps uses a support bracket 1203a to ensure a proper alignment of the gear set 1203c and 1203d. The cam-gear 1203d transforms the rotational movement in a precise linear motion through the guiding plates 1202c and the support link 1202b, resulting in the desired positioning of the flaps 1202a. The assembling process is simple as it uses self-tapping screws and self-aligning plastic components, like the holding rollers designed specifically for the cam-gear 1203d, to allow minimal friction, and to eliminate noise and wearing. Different types of vent terminals and vent returns can have different configurations and/or shapes of air deflector flaps; they can also have different numbers of actuators, depending on the HVAC application and building specific design standards.

Eventually, the vent is encased and locked within an HVAC duct. To that end, referring now to FIG. 13, the uni-body 1001 sub-assembly can include a uni-body support frame 1301 and a gate shield 1302 that guides and protects the gate blades 1103.

All the manufactured components presented in FIGS. 8-13 are built of multiple injection molded pieces using very durable recycled or organic plastic, the composition being selected based on the characteristics and the functionality of the component. These parts are environmental friendly (recyclable at end of life) and treated with non-toxic flame retardant additives to ensure that they are fire safe when used in enclosed spaces and tower buildings. To minimize the time and tools required for assembly, some of these components of the vent are assembled by using either self-tapping screws (e.g. for the gate shield 1302), or plastic or metal pins (e.g. support bracket 1203a, second actuator 1203b, driving gear 1203c) locked in place based on press fit tolerance.

The subject technology includes a variety of configurations of systems having smart vents, returns, and/or air exchangers connected to a central processing hub. Referring now to FIG. 14, an HVAC setup in accordance with the subject technology is shown generally at 1400. The system 1400 is one of the simplest configurations of the subject technology and is used in conjunction with a residential HVAC system. The system 1400 includes a ceiling mounted multi directional vent 1401 and a return 1402. Both the vent 1401 and return 1402 are “smart” and include SmartCore units. In some cases, a simpler SmartCore unit can be included in the return 1402, as the return 1402 requires a smaller collection of parameters of the air removed from the indoor space than the vent 1401.

In this case the vent 1401 uses two sets of sensors; one set of internal sensors placed inside the SmartCore and another set externally connected to the SmartCore. The set of external sensors collects the characteristics of the air coming through the HVAC duct, while the internal sensors collect data about the air in front of the vent and surrounding space. Through the sensors, the SmartCore of the vent 1401 collects data on the air temperature, air quality, air humidity, barometric pressure, air flow noise (vibration), air speed and other variables. Information can be collected from sensors at numerous locations, including within the HVAC duct, near the vent, on the ceiling (e.g.b y motion detector 1401b), or even at floor level (e.g. at 1401a via information from an IR sensor). Based on the information received the corresponding vent is able, via the SmartCore, to control the air flow volume and direction within the space. Likewise, the SmartCore of the return 1402 senses air temperature, air quality, air humidity and air flow noise (vibration). The SmartCores of the vent 1401 and return 1402 exchange data regularly in order to control the air flow volume dispersed into the space versus the air volume removed from the space. This results in a faster and more efficient change in air characteristics.

Referring now to FIG. 15 another HVAC setup in accordance with the subject technology is shown generally at 1500. The setup 1500 presents a case with multiple vents 1501, 1502 and one return 1503 in a space. Each of the vents 1501, 1502 can control its own surrounding space. The vents 1501, 1502 are also configured to closely collaborate and can identify the closest vent 1501, 1502 to the return 1503 and adjust the air volume given off by each vent 1501, 1502 in such a way that it will not impact the overall air distribution in the space. In particular, the vents 1501, 1502 can adjust their air dispersion (e.g. by manipulating the gates and flaps as discussed above) to avoid sending freshly dispersed air from a vent 1501, 1502 directly into the return 1503. Doing so can create a false positive for the overall temperature distribution in the space, and can result in poor air circulation throughout the space.

Referring now to FIGS. 16 and 17, simple setups of systems 1600, 1700 in accordance with the subject technology are shown. The setup 1600 includes a wall mounted vent 1601 while the system 1700 includes a ceiling mounted vent 1701. Each vent 1601, 1701 communicates with a wall mounted return 1602, 1703. The system 1700 additionally includes a ceiling mounted vent 1701 which communicates with the return 1703. The vents 1601, 1701 control the airflow in both the vertical direction (i.e. parallel to the vent 1601, perpendicular to vent 1701) and in the horizontal direction (i.e. perpendicular to the vent 1601, parallel to vent 1701). The internal directional flaps allow airflow adjustment along the length of each vent 1601, 1701, 1702. The vents 1601, 1701, 1702 function similarly to the multi-directional vents 1401, 1501, 1502, the main difference being that the multidirectional vents 1401, 1501, 1502 control air flow in all four directions as shown, while the vents 1601, 1701, 1702 control the air flow in only one or two directions. As explained below, a SmartHub can be utilized to ensure that all vents are collecting information from other vents (and other components) within a given system, rather than just local air characteristics detected around the vents themselves.

The system 1700 also includes an exchanger 1702, which, like the vents and returns of the subject technology, is also “smart” and includes a processor, memory, and programming to carry out desired functions. The exchanger 1702 functions similarly to the return 1703 but plays a different role in the system 1700 in that it allows air exchange between two adjacent rooms or spaces. The exchanger 1702 has a simple processing core which can be used for communication with other components of the system 1700 as well as basic data collection.

The components of the systems can also include additional sensors, connected to (and/or electrically communicating with) the vents 1601, 1701, returns 1602, 1703, and exchanger 1702. In the example given the vent 1601 includes a motion detector 1601b. The motion detector 1601b detects movement to determine which specific zones within the space need attention due to activity. Further, in the example systems 1600, 1700, the vents 1601, 1701 and exchanger 1702 also include IR temperature sensors 1601a, 1701a, 1702a which measure temperature at fixed areas within the space.

Referring now to FIG. 18, another example setup of a system 1800 in accordance with the subject technology is shown. The system 1800 is more complex, having more components throughout the space than the systems 1600, 1700 described above. The system 1800 includes two multi-directional vents 1801, 1802, two unidirectional vents 1803, 1804, a return 1807, a LIDAR 1805, and a SmartHub 1806. Notably, the number of each component of the system 1800 is exemplary only and it should be understood that more or fewer of each component may be included in different embodiments. The system 1800 can also include other sensors, such as any of the sensors described herein, either as a part of the other components (e.g. the vents 1801, 1802) or as separate components within the system 1800.

Data collected by the system 1800 is analyzed by deep learning and machine learning algorithms, allowing the most efficient heating and cooling adjustments controlled by vents 1801, 1802, 1803, 1804, and the return 1807. The LIDAR 1805 is configured to read obstacles within the space where it is installed and is equipped to read the temperature levels within a larger space. The SmartHub 1806 is configured to manage all the other devices of the system by collecting and processing all the information received from all the SmartCores of the vents 1801, 1802, 1803, 1804, return 1807, and the LIDAR 1805. The SmartHub 1806 takes the data from the other units, communicates between units of the HVAC system 1800, sends the data to a main server, and communicates the decisions to all the smart equipment linked to it. The SmartHub 1806 can also be installed in areas outside the SmartCores' reach. In other words, the SmartHub 1806 can be located where there is no vent, return, or the like to gather data. Thus, in that location, the SmartHub 1806 itself can collect data in lieu of a SmartCore. Alternatively, just a SmartCore could be placed in such a location to collect data, without a corresponding HVAC component, such as a vent. The additional collected data (like temperature humidity and human presence) can then be relied upon to improve the heating or cooling adjustments regarding that isolated area.

Referring now to FIG. 19, a block diagram of internal components of a SmartCore, as well as external components attached to a SmartCore, is shown. As discussed above, the SmartCore can be included as a part of the smart vents, returns, and exchangers which are part of the systems configured in accordance with the subject technology. The SmartCore unit is responsible for all electronic processing including: sensor data gathering; communication using different protocols and technologies/standards; actuating the motors; and serving as a first interface between the user and the vents, returns, and exchangers.

Block 1950 represents internal components which can be included in various embodiments of SmartCores in accordance with the subject technology. The internal components include a CPU 1901 which represents the main processing unit responsible for managing all inputs and outputs for the entire SmartCore unit. Volatile memory 1902 is used for storing temporary data such as sensor data, current motor position, connection attributes, and the like. The non-volatile memory 1903 will be used to permanently store data such as configuration data, authorization data, software snapshots, formulas, flows, and the like. The SmartCore includes a custom PCB board which can include features such as Bluetooth 1904, Wi-Fi 1905, and Z-wave 1906. Using these components, the vents, returns, and exchangers can connect to the internet and/or communicate with other devices using custom or standard protocols.

The PCB of the SmartCore also includes a series of sensors and sensor connection ports. To that end, the SmartCore can include temperature sensors 1908, humidity sensors 1909 and barometric pressure sensors 1910 responsible for reading the air characteristics at multiple locations. These sensors can be located in the ceiling, floor, or wall level (inside of the SmartCore) and also in the duct system, behind a vent or return.

An infrared temperature sensor 1911 picks up the temperature at a location within the space across from the SmartCore. For example, if a vent is installed in the ceiling, the infrared temperature sensor 1911 of the corresponding SmartCore picks up the temperature at the floor surface. If a return is installed on a wall or floor, the sensor 1911 of the corresponding SmartCore likewise reads the temperature from the opposite surface (i.e. the opposite wall or ceiling).

A motion sensor 1912 is responsible for detecting any movement in different areas of the space where the vents and returns are installed. Once movement is detected, the air from the HVAC system is directed towards the specific zone that needs attention due to activity.

An ambient light sensor 1913 provides information regarding light in the space. The information gathered by the ambient light sensor 1913 can be processed by the system to figure out what factors may impact the temperature in a room. For example, based on the information received, the system may determine the extent to which outside light or warm office lights impact the temperature of the room. The system can also learn the difference between artificial and natural light in a particular space based on the information provided by the ambient light sensor 1913, the system then incorporating whether the sensed light is artificial or natural into the adjustments made to air distribution throughout the system.

A proximity sensor 1914 detects any obstacles that could potentially impact the airflow, and helps the corresponding vent or return compensate and adjust to maximize efficiency of the system's operation.

The custom PCB board of the SmartCore can also include input/output devices and connections. In the example shown, RGB LED lights 1921 are included which serve as feedback for the user. The LED lights 1921 can be coded for different messages that help the user easily understand the state of the unit. A micro switch 1922 (or buttons) can be configured to reset, reboot or confirm actions in case of specific processes. Rechargeable batteries, or another type of power source, can be connected to the PCB Board of the SmartCore through a battery connect 1923 to power the SmartCore. When a low voltage power line is available, the SmartCore can also be connected to power through a voltage line-in connector 1924, allowing the batteries to recharge after a temporary power loss. When the SmartCore runs on external power source, it does not need to preserve energy and can collect data from sensors more often. To update, debug, or test the PCB board, the SmartCore can be connected to a computer via a USB Port 1925. The SmartCore can also include multi-pin connectors 1926 which can be used to connect the motors, outside sensors, and other third party devices that can feed data into the system.

Exemplary external devices which can be connected to the SmartCore are depicted in box 1952 and discussed in more detail below. A vibration sensor 1915 picks up vibrations created due to obstructions in the air deflection or air retrieval process. Data from the vibration sensor 1915 can be used to calibrate the corresponding vent or return so they operate within a range where vibrations are eliminated or kept to a minimum. An air speed sensor 1916 senses the amount of air that passes through the unit. Information from the air speed sensor 1916 can be relied upon to determine helping us to better understand where the air is distributed or collected from, and in what load. A particulate sensor 1917 is responsible for analyzing the air quality pushed into and returned from a space. Data from the particular sensor 1917 is used by the system to warn the occupants of the space if the level of particulates is high. If the level is in the admissible range, the system informs the HVAC system to add non-contaminated air. The CO 1918, CO₂ 1919, and gas 1920 sensors are used to detect the presence of any type of harmful gases in the system. The system can rely on that information to selectively trigger an alert, or alert process, informing the occupants of the risk. The alert can be visual, acoustic, or both. In some cases, the information from the sensors can also be used to close down vents in the case where harmful products, such as smoke or allergens, are detected.

The system includes an open API that will give other developers a chance to tap into the capabilities of the platform to either enhance the system even further or to transmit user alerts and or complaints directly to the system manager.

All orientations and arrangements of the components shown herein are used by way of example only. Further, it will be appreciated by those of ordinary skill in the pertinent art that the functions of several elements may, in alternative embodiments, be carried out by fewer elements or a single element. Similarly, in some embodiments, any functional element may perform fewer, or different, operations than those described with respect to the illustrated embodiment. Also, functional elements (e.g. processors, connectors, and the like) shown as distinct for purposes of illustration may be incorporated within other functional elements in various particular implementations.

While the subject technology has been described with respect to preferred embodiments, those skilled in the art will readily appreciate that various changes and/or modifications can be made to the subject technology without departing from the spirit or scope of the subject technology. For example, each claim may depend from any or all claims in a multiple dependent manner even though such has not been originally claimed.

Claims

1. An adaptive ventilation system for directing air within at least one space in an environment comprising:

at least one vent configured to control a volume and direction of air flow from a ventilation duct and into a zone within one of the spaces, each vent including a processing core and a plurality of flaps configured to be progressively opened by at least one actuator, wherein the flaps are curved to redirect air from said ventilation duct into one of the spaces in the environment at a different angle depending on a degree to which the flaps are progressively opened;

at least one return configured to control a volume of air flow from one of the spaces into a return duct, each return including a processing core; and

a plurality of sensors in electrical communication with the vents and returns,

wherein:

the at least one vent controls the volume and direction of air flow between a ventilation duct and a zone within one of the spaces based on data from the sensors; and

the at least one return controls the volume of air flow from one of the spaces into the return duct based on data from the sensors.

2. The system of claim 1, wherein each vent includes a gate configured to be progressively opened by at least one actuator to control a volume of air from a ventilation duct into said vent.

3. An adaptive ventilation system for directing air within at least one space in an environment comprising:

at least one vent, each vent including a processing core;

at least one return, each return including a processing core; and

a plurality of sensors in electrical communication with the at least one vent and the at least one return,

wherein:

each vent is configured to control a volume and direction of air flow from a ventilation duct and into a zone within one of the spaces; and

each return is configured to control a volume of air flow from one of the spaces into a return duct.

4. The system of claim 3, wherein each vent comprises a plurality of internal sensors and each processing core of each vent communicates with a plurality of external sensors.

5. The system of claim 4, wherein each return comprises a plurality of internal sensors and each processing core of each return communicates with a plurality of external sensors, each return configured to control the volume of air flow from one of the spaces into a return duct based on data received from the internal and external sensors.

6. The system of claim 3, wherein the returns and vents are configured to communicate to set a priority for a plurality of zones in at least one of the spaces for one or more of the following: heating; cooling; and dehumidification.

7. The system of claim 3, wherein the vents and returns are each configured to receive information from at least one of the plurality of sensors and adapt a volume or a direction of air flow therethrough based on a desired setting.

8. The system of claim 7, wherein the vents and returns are further configured to adapt the volume or the direction of air flow therethrough based on past data processed by machine learning and deep learning algorithms.

9. The system of claim 7, wherein the desired settings are based on one or more of the following: user input; or an ASHRAE table of temperature settings for categories of spaces.

10. The system of claim 3, further comprising at least one air exchanger configured to control a volume of air flow between two spaces within the environment.

11. The system of claim 4, wherein:

the internal sensors for at least one vent include: a temperature sensor; a humidity sensor; a barometric pressure sensor; an infrared temperature sensor; a motion sensor; an ambient light sensor; and a proximity sensor; and

the external sensors for at least one vent include: a vibration sensor; an air speed sensor; an air particulate sensor; a CO2 sensor; a CO sensor; a gas sensor; a temperature sensor;

a humidity sensor; and a pressure sensor.

12. The system of claim 3, further comprising a processing hub in electronic communication with the vents and returns, the processing hub configured to manage communications, and provide data between, the vents and returns.

13. The system of claim 12, wherein the processing hub is further in electronic communication with a cloud server.

14. A vent for directing air from a ventilation duct into an environment comprising:

a plurality of flaps configured to be progressively opened by at least one actuator, wherein the flaps are curved to redirect air from the ventilation duct into the environment at a different angle depending on a degree to which the flaps are progressively opened.

15. The vent of claim 14, wherein the flaps are one of: substantially semi-circular shaped; or arcuate shaped.

16. The vent of claim 14, wherein the plurality of flaps includes at least four flaps arranged around a central section of the vent.

17. The vent of claim 16, wherein the central section includes an ASHRAE table of temperature settings for different types or categories of spaces and a removable attached processing core for controlling the vent or a return, the central section and processing core coupling via a push-and-lock mechanism.

18. The vent of claim 13, wherein the flaps are configured to each direct air flow in a different direction from the other flaps.

19. The vent of claim 18, wherein the vent is oriented along an x-y plane and each of the flaps is configured to direct air flow in the direction of the x-y plane at a substantially 90 degree angle.

20. The vent of claim 14, wherein:

each flap forms a channel between said flap and a body of the vent for passing air from the ventilation duct into the environment, at least one cross-section of the channel being defined entirely between a body of the vent and an extension of the flap; and

the flaps are configured such that actuating each flap causes the extension to move closer to the vent body, thereby narrowing the cross-section of the channel defined entirely between the body of the vent and the extension of the flap, thereby increasing a speed of any air passing therethrough.