Abstract: Embodiments include techniques for developing a model framework for remote unit monitoring condition-based maintenance. The techniques include collecting data associated with unplanned service requests, and generating one or more models from the collected data. The techniques also include predicting unplanned service requests based at least in part on the one or more models, and transmitting an output of the prediction of the unplanned service request.

Abstract: A monitoring system includes one or more detection devices, a communication device, and an analytics system. The one or more detection devices generate, at a conveyance system, one or more data streams describing the ride of the conveyance system, where the data streams include at least one of vibration data and audio data. The communication device transmits sensor data based on the one or more data streams. The analytics system receives the sensor data from the communication device and, based on the sensor data, determines a ride quality of the conveyance system.

Abstract: A building management system for a building system includes a building system interface configured to receive building system data; a knowledge base configured to receive the building system data, the knowledge base providing a model of the building system, the model including semantic descriptions of the building system data, the semantic descriptions of the building system data being arranged in an ontology; and a user interface configured to access the knowledge base.

Abstract: An elevator system includes a component adapted to perform a function, a sensor, and a control configuration. The sensor is configured to detect an operating parameter associated with the function. The control configuration is configured to receive a parameter signal from the sensor, and extract a predesignated feature from data associated with the parameter signal. The predesignated feature is then aggregated by the control configuration and machine learning is applied to determine a degradation level of the function associated with the predesignated feature.

Abstract: An elevator vandalism monitoring system is configured to determine if an act of vandalism upon a component of an elevator system has occurred. The vandalism monitoring system includes a sensor, a processor, an electronic storage medium, a model, and a comparison module. The sensor is configured to monitor a detectable parameter associated with the component, and output a detectable parameter signal. The processor is configured to receive the detectable parameter signal. The model is stored in the electronic storage medium, and is associated with an expected parameter. The comparison module is executed by the processor, and is configured to generally compare the model to the detectable parameter signal for determining if a parameter anomaly exists.

Abstract: According to an aspect, an elevator sensor calibration system includes one or more sensors operable to monitor an elevator system, an elevator sensor calibration device, and a computing system. The computing system includes a memory and a processor that collects a plurality of baseline sensor data from the one or more sensors during movement of an elevator component, collects a plurality of disturbance data from the one or more sensors while the elevator component is displaced responsive to contact with the elevator sensor calibration device during movement of the elevator component, and performs analytics model calibration to calibrate a trained model based on one or more response changes between the baseline sensor data and the disturbance data.

Abstract: According to an aspect, a method of elevator sensor system calibration includes collecting, by a computing system, a plurality of data from one or more sensors of an elevator sensor system while a calibration device applies a known excitation. The computing system compares an actual response to an expected response to the known excitation using a trained model. The computing system performs analytics model calibration to calibrate the trained model based on one or more response changes between the actual response and the expected response.

Abstract: A method of examining an electrical safety chain of an elevator system including: emitting an electric pulse from a time-domain reflectometer into an electrical safety chain of an elevator system; detecting a reflected electric pulse reflected within the electrical safety chain using the time-domain reflectometer; comparing the reflected electric pulse to a baseline reflected electric pulse; and determining a degradation level in response to the reflected electric pulse and the baseline reflected electric pulse.

Abstract: A monitoring system includes one or more detection devices, a communication device, and an analytics system. The one or more detection devices generate, at a conveyance system, one or more data streams describing the ride of the conveyance system, where the data streams include at least one of vibration data and audio data. The communication device transmits sensor data based on the one or more data streams. The analytics system receives the sensor data from the communication device and, based on the sensor data, determines a ride quality of the conveyance system.

Abstract: A method of examining an electrical safety chain of an elevator system including: emitting an electric pulse from a time-domain reflectometer into an electrical safety chain of an elevator system; detecting a reflected electric pulse reflected within the electrical safety chain using the time-domain reflectometer; comparing the reflected electric pulse to a baseline reflected electric pulse; and determining a degradation level in response to the reflected electric pulse and the baseline reflected electric pulse.

Abstract: Embodiments include techniques for developing a model framework for remote unit monitoring condition-based maintenance. The techniques include collecting data associated with unplanned service requests, and generating one or more models from the collected data. The techniques also include predicting unplanned service requests based at least in part on the one or more models, and transmitting an output of the prediction of the unplanned service request.

Abstract: Embodiments include a system and method for scheduling maintenance based on remote monitoring data and service data analytics. The embodiments include a controller configured monitor performance of one or more units, a remote system configured to store service data associated with the one or more units, and a processor operably coupled to the controller and the remote system. The processor is configured to receive monitoring data from the controller for the one or more units, and receive service data for the one or more units. The remote system is also configured to generate a health score based at least in part on the monitoring data and the service data. The processor is further configured to predict a failure based at least in part on the health score, and execute an action based at least in part on the generated health score.

Abstract: A system for providing route recommendations for field service technicians is provided. The system includes a processor for performing operations that include identifying a current geographic location of a service technician and receiving a list of tasks for the service technician. A plurality of route options are generated for the service technician based at least in part on the list of tasks and the current geographic location of the service technician. Each of the plurality of route options includes a geographic location of at least one of the tasks in the list of tasks. The route options are output.

Abstract: According to one or more embodiments, a system and method for authorizing a user securing an elevator call in a building is provided. For example, the method includes receiving, at a mobile device, a secure authorization token that includes an expiration time, connecting the mobile device to a backend system using the secure authorization token from the mobile device, verifying, using the backend system, an authenticity of the secure authorization token from the mobile device based on at least the expiration time, generating, at the backend system, a secure access token and a random number in response to the authenticity of the secure authorization token being verified, and receiving, at the mobile device, the secure access token and the random number for use making elevator call requests.

Abstract: A method of managing structure resources of a cyber-physical structure includes identifying the structure resources of the cyber-physical structure, the structure resources including dynamic resources configured to provide dynamic structure data over time based on monitoring the cyber-physical structure over time; identifying, by a structure management computer system, applicable structure-management templates which include one or more operation algorithms for managing the structure resources and one or more required-resource descriptions defining structure resources required by the one or more operation algorithms, the applicable structure management templates identified based on matching identified structure resources to the required-resource descriptions of the structure-management templates; and applying, by the structure management computer system, one or more of the applicable structure-management templates as structure management systems to manage operation of the cyber-physical structure by implementi

Abstract: According to an aspect, a method of elevator sensor system calibration includes collecting, by a computing system, a plurality of data from one or more sensors of an elevator sensor system while a calibration device applies a known excitation. The computing system compares an actual response to an expected response to the known excitation using a trained model. The computing system performs analytics model calibration to calibrate the trained model based on one or more response changes between the actual response and the expected response.

Abstract: According to an aspect, an elevator sensor calibration system includes one or more sensors operable to monitor an elevator system, an elevator sensor calibration device, and a computing system. The computing system includes a memory and a processor that collects a plurality of baseline sensor data from the one or more sensors during movement of an elevator component, collects a plurality of disturbance data from the one or more sensors while the elevator component is displaced responsive to contact with the elevator sensor calibration device during movement of the elevator component, and performs analytics model calibration to calibrate a trained model based on one or more response changes between the baseline sensor data and the disturbance data.

Abstract: According to an aspect, a method of elevator sensor system calibration includes collecting, by a computing system, a plurality of baseline sensor data from one or more sensors of an elevator sensor system as a field-site baseline response. The computing system compares the field-site baseline response to an experiment-site baseline response. The computing system performs analytics model calibration to produce a calibrated trained model for fault diagnostics and/or prognostics based on one or more response changes between the field-site baseline response and the experiment-site baseline response.

Abstract: An elevator system includes a component adapted to perform a function, a sensor, and a control configuration. The sensor is configured to detect an operating parameter associated with the function. The control configuration is configured to receive a parameter signal from the sensor, and extract a predesignated feature from data associated with the parameter signal. The predesignated feature is then aggregated by the control configuration and machine learning is applied to determine a degradation level of the function associated with the predesignated feature.

Abstract: An elevator vandalism monitoring system is configured to determine if an act of vandalism upon a component of an elevator system has occurred. The vandalism monitoring system includes a sensor, a processor, an electronic storage medium, a model, and a comparison module. The sensor is configured to monitor a detectable parameter associated with the component, and output a detectable parameter signal. The processor is configured to receive the detectable parameter signal. The model is stored in the electronic storage medium, and is associated with an expected parameter. The comparison module is executed by the processor, and is configured to generally compare the model to the detectable parameter signal for determining if a parameter anomaly exists.