Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: A method for detecting tooth wear using digital 3D models of teeth taken at different times. The digital 3D models of teeth are segmented to identify individual teeth within the digital 3D model. The segmentation includes performing a first segmentation method that over segments at least some of the teeth within the model and a second segmentation method that classifies points within the model as being either on an interior of a tooth or on a boundary between teeth. The results of the first and second segmentation methods are combined to generate segmented digital 3D models. The segmented digital 3D models of teeth are compared to detect tooth wear by determining differences between the segmented models, where the differences relate to the same tooth to detect wear on the tooth over time.

Abstract: Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Abstract: A method for detecting tooth wear using digital 3D models of teeth taken at different times. The digital 3D models of teeth are segmented to identify individual teeth within the digital 3D model. The segmentation includes performing a first segmentation method that over segments at least some of the teeth within the model and a second segmentation method that classifies points within the model as being either on an interior of a tooth or on a boundary between teeth. The results of the first and second segmentation methods are combined to generate segmented digital 3D models. The segmented digital 3D models of teeth are compared to detect tooth wear by determining differences between the segmented models, where the differences relate to the same tooth to detect wear on the tooth over time.

Abstract: A method for detecting tooth wear using digital 3D models of teeth taken at different times. The digital 3D models of teeth are segmented to identify individual teeth within the digital 3D model. The segmentation includes performing a first segmentation method that over segments at least some of the teeth within the model and a second segmentation method that classifies points within the model as being either on an interior of a tooth or on a boundary between teeth. The results of the first and second segmentation methods are combined to generate segmented digital 3D models. The segmented digital 3D models of teeth are compared to detect tooth wear by determining differences between the segmented models, where the differences relate to the same tooth to detect wear on the tooth over time.

Abstract: A method for detecting tooth wear using digital 3D models of teeth taken at different times. The digital 3D models of teeth are segmented to identify individual teeth within the digital 3D model. The segmentation includes performing a first segmentation method that over segments at least some of the teeth within the model and a second segmentation method that classifies points within the model as being either on an interior of a tooth or on a boundary between teeth. The results of the first and second segmentation methods are combined to generate segmented digital 3D models. The segmented digital 3D models of teeth are compared to detect tooth wear by determining differences between the segmented models, where the differences relate to the same tooth to detect wear on the tooth over time.

Abstract: Computer-based techniques are described that use orthodontic prescription templates to assist an orthodontic practitioner in creating a patient-specific orthodontic prescription. In particular, an orthodontic practitioner may retrieve a stored electronic orthodontic prescription template. The practitioner may then generate an orthodontic prescription that is specific to a patient's teeth by modifying one or more bracket attributes of the template within orthodontic modeling software. Subsequently, the practitioner may communicate the patient-specific orthodontic prescription to a manufacturing facility that constructs an indirect bonding tray for use in physically placing brackets on the patient's teeth.

Abstract: Computer-based techniques are described that use orthodontic prescription templates to assist an orthodontic practitioner in creating a patient-specific orthodontic prescription. In particular, an orthodontic practitioner may retrieve a stored electronic orthodontic prescription template. The practitioner may then generate an orthodontic prescription that is specific to a patient's teeth by modifying one or more bracket attributes of the template within orthodontic modeling software. Subsequently, the practitioner may communicate the patient-specific orthodontic prescription to a manufacturing facility that constructs an indirect bonding tray for use in physically placing brackets on the patient's teeth.