Abstract: Systems and methods for providing contextual interaction with connected devices are described. A mobile device having a display that presents a user interface enabling access to functionalities provided by connected devices. The user interface may be updated as various contextually-related data is received. For example, data representing a current position of the mobile device, such as Bluetooth low energy beacon signals, WiFi signals, and the like, may be monitored. In response to determining that the current position is within a threshold proximity of a first location, the user interface may be updated to emphasize a first location interface corresponding to the first location over interfaces corresponding to other locations.

Abstract: A delivery system for an occlusive implant may include a delivery sheath having a delivery lumen extending proximally from a distal end of the delivery sheath, the delivery sheath being formed from a polymeric material, and a core wire slidably disposed within the delivery lumen. The core wire may be configured to releasably engage the occlusive implant. The delivery sheath may include a circumferential ring monolithically formed therewith at the distal end of the delivery sheath and a plurality of longitudinal slots disposed proximal of the circumferential ring. An occlusive implant system may include an occlusive implant configured to shift between a delivery configuration and a deployed configuration, and the delivery system for the occlusive implant. The occlusive implant may be disposed within a distal portion of the delivery lumen in the delivery configuration.

Abstract: Systems and methods for providing contextual interaction with connected devices are described. A mobile device having a display that presents a user interface enabling access to functionalities provided by connected devices. The user interface may be updated as various contextually-related data is received. For example, data representing a current position of the mobile device, such as Bluetooth low energy beacon signals, WiFi signals, and the like, may be monitored. In response to determining that the current position is within a threshold proximity of a first location, the user interface may be updated to emphasize a first location interface corresponding to the first location over interfaces corresponding to other locations.

Abstract: Systems, devices, and methods for intradermal or subdermal fluid delivery via a microneedle are provided. A delivery system can include an injector, fluid-filled cartridge or syringe, and a needle. A cartridge or syringe can be compatibly coupled with an injector device such that the injector device is capable of ejecting fluid out of the cartridge and though the needle. Fluid delivery systems can be utilized in a number of applications, including medications and supplements for the skin.

Abstract: Systems and methods are described for evaluating and gamifying maintenance for a property by a user. The method may include: (1) retrieving first home data for a first property and second home data for a second property, wherein a user is associated with the first property; (2) calculating, using a trained machine learning evaluation model, one or more second home score factors based upon the second home data; (3) detecting that the user is to be associated with the second property; (4) detecting, based upon the first home data and the second home data, one or more local environmental differences between the first property and the second property; and (5) generating a learning module for the user for improving or maintaining the one or more second home score factors based upon the one or more local environmental differences.

Abstract: Systems and methods are described for evaluating and gamifying maintenance for a property by a user. The method may include: (1) retrieving training data captured by one or more sensors associated with one or more properties or one or more users; (2) retrieving at least one of home data for a property or user data for a user; (3) determining, using a machine learning model, home score factors based upon at least one of the home data or the user data, wherein the machine learning model is trained with the training data; (4) generating, based upon the home score factors, a home score for the property; (5) determining, based upon at least one of the home data or the user data, difference factors between the property and a previous property associated with the user; and (6) causing a user device to display the home score and difference factors.

Abstract: An asset management system is disclosed where a plurality of financial databases may connect with and be in communication with an asset management tool. The asset management tool is able to create an individual spending plan (scheduled distributions) and matching fixed income investment portfolio for a user based on inputted parameters with automatic distributions from the portfolio consistent with the individual spending plan occurring with a high degree of certainty. The asset management tool may communicate with the plurality of financial databases to put the individual spending plan and matching portfolio into action and is able to calculate and communicate an optimized surplus investment as a means of self-insuring so that the predefined schedule of distributions is met with the effective certainty one would expect from an insured/guaranteed income product.

Abstract: Embodiments include systems and methods that may include receiving situational information triggering a need to alert the driver and in response to the need to alert the driver presenting an alert to the driver based on driver state information selected based on a likelihood the driver will be more receptive to the alert modality than others of the plurality of alert modalities. The likelihood the driver will be receptive to the alert modality may be based on the received situational information, the received driver state information, and a historical behaviour record. The historical behaviour record may correlate the driver's reaction or the reaction of other drivers to previous alerts presented to the driver or other drivers with similar driver state information and similar situational information triggering presentation of previous alerts. The system may learn from the reaction of the driver and/or other drivers to better select suitable alert modalities.

Abstract: An asset management system is disclosed where a plurality of financial databases may connect with and be in communication with an asset management tool. The asset management tool is able to create an individual spending plan (scheduled distributions) and matching fixed income investment portfolio for a user based on inputted parameters with automatic distributions from the portfolio consistent with the individual spending plan occurring with a high degree of certainty. The asset management tool may communicate with the plurality of financial databases to put the individual spending plan and matching portfolio into action and is able to calculate and communicate an optimized surplus investment as a means of self-insuring so that the predefined schedule of distributions is met with the effective certainty one would expect from an insured/guaranteed income product.

Abstract: An editing system may dynamically and intelligently determine which data points to remove, replace, and/or modify from a point cloud space so that more features, color information, and/or detail of the point cloud are preserved after decimation. The system may receive data points that are distributed in space, and may select one or more elements of the data points on which to base the decimation. For instance, the system may decimate a first subset of the data points by a first amount based on a first difference in values defined for the one or more elements of the first subset of data points, and may decimate a different second subset of the data points by a different second amount based on a second difference in values defined for the one or more elements of the second subset of data points.

Abstract: Disclosed is an imaging system and associated methods for mapping in-focus image data from two-dimensional (“2D”) images of a scene to a three-dimensional (“3D”) model of the scene. The imaging system receives the 2D images and the 3D model, determines the depth of field (“DOF”) and the field of view (“FOV”) for each 2D image, and selects a subset of 3D model constructs that form the FOV and are within the DOF of a particular 2D image. The imaging system determines pixels of the particular 2D image that represent a same set of points in the scene as the subset of 3D model constructs, and maps the visual characteristics from those pixels to non-positional elements of the subset of 3D model constructs.

Abstract: An editing system may dynamically and intelligently determine which data points to remove, replace, and/or modify from a point cloud space so that more features, color information, and/or detail of the point cloud are preserved after decimation. The system may receive data points that are distributed in space, and may select one or more elements of the data points on which to base the decimation. For instance, the system may decimate a first subset of the data points by a first amount based on a first difference in values defined for the one or more elements of the first subset of data points, and may decimate a different second subset of the data points by a different second amount based on a second difference in values defined for the one or more elements of the second subset of data points.

Abstract: Disclosed is a system and associated methods for generating a point-accurate three-dimensional (“3D”) model of a scene with point-accurate color information from a non-cosited capture of the scene. The system may define a first model based on positional measurements obtained from a first device. The system may capture images of the scene with a different set of devices, and may generate a second model from a photogrammetry modeling of the images. The system may align the models in order to determine positioning of the set of devices relative to the first model, and may select a particular device that captures descriptive characteristics from a position in the scene that is represented by the positional elements of a particular data point. The system may define non-positional elements of the particular data point based on the descriptive characteristics captured by the particular device.

Abstract: Disclosed is an imaging system and associated methods for mapping in-focus image data from two-dimensional (“2D”) images of a scene to a three-dimensional (“3D”) model of the scene. The imaging system receives the 2D images and the 3D model, determines the depth of field (“DOF”) and the field of view (“FOV”) for each 2D image, and selects a subset of 3D model constructs that form the FOV and are within the DOF of a particular 2D image. The imaging system determines pixels of the particular 2D image that represent a same set of points in the scene as the subset of 3D model constructs, and maps the visual characteristics from those pixels to non-positional elements of the subset of 3D model constructs.

Abstract: Disclosed is a system and associated methods for generating a point-accurate three-dimensional (“3D”) model of a scene with point-accurate color information from a non-cosited capture of the scene. The system may define a first model based on positional measurements obtained from a first device. The system may capture images of the scene with a different set of devices, and may generate a second model from a photogrammetry modeling of the images. The system may align the models in order to determine positioning of the set of devices relative to the first model, and may select a particular device that captures descriptive characteristics from a position in the scene that is represented by the positional elements of a particular data point. The system may define non-positional elements of the particular data point based on the descriptive characteristics captured by the particular device.

Abstract: A method includes, receiving a biometric identifier from a visitor to the property, determining an arrival time of the visitor based on receiving the biometric identifier, comparing the arrival time of the visitor to an expected arrival time of an expected visitor, based on comparing the arrival time of the visitor to an expected arrival time, transmitting the biometric identifier and data identifying the expected visitor, receiving, by the monitoring system and from the external server, (i) data indicating that the biometric identifier corresponds to the expected visitor and (ii) data indicating that an electronic device of the expected visitor is located at the property, and based on (i) the data indicating that the biometric identifier corresponds to the expected visitor and (ii) the data indicating that the electronic device of the expected visitor is located at the property, granting, by the monitoring system, the visitor access to the property.

Abstract: Systems and methods for providing contextual interaction with connected devices are described. A mobile device having a display that presents a user interface enabling access to functionalities provided by connected devices. The user interface may be updated as various contextually-related data is received. For example, data representing a current position of the mobile device, such as Bluetooth low energy beacon signals, WiFi signals, and the like, may be monitored. In response to determining that the current position is within a threshold proximity of a first location, the user interface may be updated to emphasize a first location interface corresponding to the first location over interfaces corresponding to other locations.

Abstract: An editing system may dynamically and intelligently determine which data points to remove, replace, and/or modify from a point cloud space so that more features, color information, and/or detail of the point cloud are preserved after decimation. The system may receive data points that are distributed in space, and may select one or more elements of the data points on which to base the decimation. For instance, the system may decimate a first subset of the data points by a first amount based on a first difference in values defined for the one or more elements of the first subset of data points, and may decimate a different second subset of the data points by a different second amount based on a second difference in values defined for the one or more elements of the second subset of data points.

Abstract: A method includes, receiving a biometric identifier from a visitor to the property, determining an arrival time of the visitor based on receiving the biometric identifier, comparing the arrival time of the visitor to an expected arrival time of an expected visitor, based on comparing the arrival time of the visitor to an expected arrival time, transmitting the biometric identifier and data identifying the expected visitor, receiving, by the monitoring system and from the external server, (i) data indicating that the biometric identifier corresponds to the expected visitor and (ii) data indicating that an electronic device of the expected visitor is located at the property, and based on (i) the data indicating that the biometric identifier corresponds to the expected visitor and (ii) the data indicating that the electronic device of the expected visitor is located at the property, granting, by the monitoring system, the visitor access to the property.