Disclosed herein are systems and methods for identifying issues in a building. In one aspect, a method includes receiving information describing an issue with a building, accessing data that identifies (i) a plurality of components that are included in the building and (ii) features of the plurality of components, identifying one or more candidate components that have at least a threshold likelihood of being a cause of the issue, and performing some action in response to remedy the issue. For example, the method can include selecting a candidate service provider from among a plurality of service providers based on a comparison of (i) the one or more candidate components and (ii) information identifying technical qualifications for the plurality of service providers, transmitting a service request for the issue to the candidate service provider, receiving a response from the candidate service provider, and scheduling, based on the response, a service appointment.

A method for estimating warranty costs for an individual machine can include training a warranty cost model. The method can also include receiving telematics data from a plurality of sensors on an individual machine and determining one or more activity types for the individual machine based on the associated telematics data. A mean activity time can be calculated for each activity type. The mean activity time for each activity type can be fed into the trained warranty cost model to provide a predicted warranty cost for the individual machine and a corresponding probability of the predicted warranty cost from the trained warranty cost model.

A cloud diagnostic system and a method of operating the same to diagnose or predict potential fault conditions in an appliance includes obtaining, at a remote server, a first data stream from the appliance through the external communication network at a first data density (e.g., in megabytes/sec). The method further includes analyzing the first data stream to determine a data anomaly or potential issue exists. The remote server may request that the appliance transmit a second data stream at a second data density that is greater than the first data density and may analyze the second data stream using complex, higher resolution machine learning models to diagnose a potential fault condition for the appliance.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user's voice, storing the user's voice in a memory of an earpiece device, or storing the user's voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user's voice, storing the user's voice in a memory of an earpiece device, or storing the user's voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

Methods and apparatus are provided herein. For example, a method for maintaining a power conversion system can include transmitting, to a computing apparatus in operable communication with the power conversion system, an alert message indicating non-working microinverters and which of the non-working microinverters are under warranty and eligible for replacement; receiving, from the computing apparatus, a request for replacement for the non-working microinverters; and transmitting, to the computing apparatus, an acknowledgment message indicating that the request has been successfully received and replacements for the non-working microinverters are being shipped.

Methods and apparatus are provided herein. For example, a method for maintaining a power conversion system can include transmitting, to a computing apparatus in operable communication with the power conversion system, an alert message indicating non-working microinverters and which of the non-working microinverters are under warranty and eligible for replacement; receiving, from the computing apparatus, a request for replacement for the non-working microinverters; and transmitting, to the computing apparatus, an acknowledgment message indicating that the request has been successfully received and replacements for the non-working microinverters are being shipped.

A digital content communications system for providing customer or product support using predictive analytics is provided. The system may include an analytics subsystem that communicates with one or more servers and one or more data stores in a network. The analytics subsystem may include a data access interface to receive a first set of data associated with a plurality of users or user accounts from a first data source, and to receive a second set of data associated with a plurality of users or user accounts from a second data source. The analytics subsystem may include processor to: prepare the first set of data; train a model using the first set of prepared data, wherein the model is at least one of a cancel-defer-go live model, a regular-extended warranty model, or a phase duration forecasting model. The processor may also prepare the second set of data; run the second set of data through the trained model; generate predictions based on running the second set of data that ran through the trained model; and provide at least one multimodal output based on the generated predictions.

A method for correlating data from different sensors for product lifecycle management includes receiving sensor information from an additional sensor of a plurality of sensors of an industrial operation. The additional sensor is different from component sensors used for functionality of a component of the industrial operation. Sensor information from the additional sensor monitors conditions of a portion of the industrial operation different from sensor information of the component sensors used for the functionality of the component. The method includes deriving, using the sensor information, a correlation between an operational parameter of the component and sensor information of the additional sensor. The operational parameter is related to a predicted operational lifetime of the component. The method includes identifying an abnormal operating condition of the component based on a comparison between additional sensor information from the additional sensor and the operational parameter, and sending an alert with the abnormal operating condition.

An apparatus for a transaction includes a memory and at least one processor coupled to the memory. The at least one processor is configured to generate a trade-in value with a payoff amount for a first item being traded in for a purchase of a second item. Additionally, the at least one processor is configured to get loan approval for a loan for the second item. The at least one processor is also configured to calculate payments for the loan for the second item. The at least one processor is also configured to present a contract for signing for a purchase of the second item. The at least one processor is also configured to accept a payment for the second item and send a communication to a consumer from a dealer of the second item.