Honeywell International Inc.

Ademco Inc.

Ramprasad Yelchuru

Pradyumna Sampath

Shreyan Chowdhury

Gudi Ravindra

Srikanth Ryali

Shailesh Rajnikant Patel

Pradeep Shetty

Ravi Bharathi Krishnan

Purnaprajna Raghavendra Mangsuli

Aaron J Klein

Cameron Kip Vreeland

Vivek Ramachandran

Suresh Vemuri

Huanmin Bao

A control system for controlling operation of a plurality of building control devices includes a pool of virtual controllers that are hosted on one or more computing device and are configured to provide control commands for controlling one or more associate building control devices of the plurality of building control devices. Each of a plurality of edge controllers are associated with at least one building control device and are configured to receive and execute control commands from one or more of the virtual controllers to control the associated one or more building control devices. An orchestrator is configured to monitor one or more operational characteristics of each of the virtual controllers and to modify one or more aspects of the pool of virtual controllers when one or more of the operational characteristics of one or more of the virtual controllers meets predetermined characteristics.

Method and system for managing virtual controllers in a building management system

Systems, methods, and devices for monitoring industrial equipment using audio are described herein. One system includes two computing devices. The first computing device can receive, from an audio sensor, audio sensed during operation of industrial equipment, extract a plurality of features from the audio, determine whether any portion of the audio is anomalous, and send, upon determining a portion of the audio is anomalous, the anomalous portion of the audio to the second, remotely located, computing device. The second computing device can provide the anomalous portion of the audio to a user to determine whether the anomalous portion of the audio corresponds to a fault occurring in the equipment, and receive, from the user upon determining the anomalous portion of the audio corresponds to a fault occurring in the equipment, input indicating the anomalous portion of the audio corresponds to the fault to learn fault patterns in the equipment.

Monitoring industrial equipment using audio

A wireless controller to set a programmable setpoint of a remote HVAC unit that thermostatically controls a temperature in a space using the temperature sensed and a programmable setpoint. The wireless controller may include a transmitter, a memory, a temperature sensor, and a controller. The wireless controller may transmit commands to set the programmable setpoint of the remote HVAC unit, wait until the temperature sensed by the temperature sensor of the wireless controller stabilizes, determine a difference between the desired setpoint temperature and the stabilized temperature, and if the offset temperature is greater than or equal to a threshold offset, determine an updated control setpoint temperature and transmit commands to set the programmable setpoint of the remote HVAC unit to an updated control setpoint temperature.

Method and system for controlling a mini-split HVAC unit from a remote location

Systems and methods for training a control panel to recognize user defined and preprogrammed sound patterns are provided. Such systems and methods can include the control panel operating in a learning mode, receiving initial ambient audio from a region, and saving the initial ambient audio as an audio pattern in a memory device of the control panel. Such systems and methods can also include the control panel operating in an active mode, receiving subsequent ambient audio from the region, using an audio classification model to make an initial determination as to whether the subsequent ambient audio matches or is otherwise consistent with the audio pattern, determining whether the initial determination is correct, and when the control panel determines that the initial determination is incorrect, modifying or updating the audio classification model for improving the accuracy in detecting future consistency with the audio pattern.

Systems and methods for training devices to recognize sound patterns

Systems and methods () for offline/online performance monitoring of batch processes (BPs) involving obtaining archived data (AD) obtained during runs of BP and including information defining a batch quality attribute for each run. The method also involves forming clusters by classifying AD for the runs into classes based on the batch quality attribute(s) and building a first multivariate statistical model (MSM) using AD. The method can further involve building a wavelet analysis based feature matrix (FM) using AD, forming a first projection () by projecting FM onto a first MSM, building a second MSM () using information obtained from the first projection, and computing centroids (C, . . . , C) and boundary profiles for the clusters (). The method can involve performing an online/offline performance monitoring () using an integrated version of the first and second MSM, a classification algorithm, centroids, and boundary profiles.

Systems and methods for real time classification and performance monitoring of batch processes

A method () for offline/online monitoring of batch processes. The method involves () decomposing a time domain of a batch process run (BPR) into several blocks and () building multivariate statistical models (MSMs) for each of them using archived data for a batch process (ABPD). ABPD comprises stored data obtained during BPRs. The method also involves () retrieving recently stored data (RSD) for a recent fully performed BPR run (FPR) or current BPR run. The method further involves () building a feature vector matrix (FVM) using RSD. FVM contains feature vectors representing statistical measures of wavelet coefficients determined for variables (v, . . . , v). A projection () is formed by projecting feature vectors onto at least one MSM or a combined multivariate statistical model (CMSM). CMSM is a weighted average of at least two MSMs. Subsequently, at least one estimate is generated for FPRor current BPR run using information provided by the projection ().

Growing community of inventors

Bengaluru, India

Ramprasad Yelchuru