Abstract: A development management system is described herein that may provide a unified portal that depicts an interactive user interface accessible to a developer and various stakeholders in a region at which a development is planned. Within the unified portal, the developer can provide and/or access certain sets of data. In addition, other stakeholders in the region at which a development is planned can access the unified portal and provide access-controlled data that may otherwise be unavailable to the developer. The unified portal may allow the developer and/or the stakeholders to monitor the progress of a development, provide input as to various design elements that may comprise the development, to provide or request additional information as needed, to select a location at which the development will occur with the aid of artificial intelligence, and to review and revise a layout of the proposed development graphically depicted via the user interface.

Abstract: A system, apparatus, computer program product, and method use a convolutional neural network to auto-determine a first floor height (FFH) and a FFH elevation (FFE) of a building. The FFH, and FFE of the building are determined with respect to the terrain or surface of the parcel of land on which the building is located. In turn, by knowing the FFH and/or FFE of the building on the parcel, it is possible to use that information while performing a flood risk assessment to a property without requiring a personal inspection of the parcel by a human.

Abstract: A flood footprint estimation system that can generate a requested flood footprint is described herein. For example, the flood footprint estimation system can estimate water surface elevations at various points along a stream or river. The flood footprint estimation system can then perform a smoothing operation on the estimated water surface elevations to generate a trend line or curve of the estimated water surface elevations in which each point of the trend line or curve corresponds to a water surface elevation value that is no greater than any of the water surface elevation values of the previous points of the trend line or curve. The flood footprint estimation system can use the trend line or curve to perform an iterative water expansion to determine which geographic locations may flood. Results of the iterative water expansion can be provided to a user device in the form of a user interface.

Abstract: An improved living area estimation system is described herein that can control and/or use data obtained by a residential robotic device that operates within a structure to estimate the living area. In particular, a residential robotic device may navigate along a predetermined or dynamically-determined route on one floor of the structure. As the residential robotic device travels along the route, the residential robotic device can use one or more sensors to track the area covered. The living area estimation system can obtain a traversed area map directly or indirectly from the residential robotic device, use image processing techniques to enhance the traversed area map, and estimate a living area of a floor on which the residential robotic device operated using the enhanced traversed area map. The living area estimation system can then use artificial intelligence and the estimated floor living area to estimate the living area of a structure.

Abstract: A system, apparatus, computer program product, and method use a convolutional neural network to auto-determine a first floor height (FFH) and a FFH elevation (FFE) of a building. The FFH, and FFE of the building are determined with respect to the terrain or surface of the parcel of land on which the building is located. In turn, by knowing the FFH and/or FFE of the building on the parcel, it is possible to use that information while performing a flood risk assessment to a property without requiring a personal inspection of the parcel by a human.

Abstract: Systems and methods are disclosed for the generation and interactive display of three-dimensional (3D) models that accurately represent buildings and other large, complex objects possessing both internal and external features. More specifically, an exterior mesh can be generated that captures all the external features of the building. An interior mesh can also be generated that captures all the internal features of the building. The exterior mesh and the interior mesh may be layered and combined using geographical coordinates (e.g., global positioning system (GPS) data) in order to create a combined mesh that can be used to render a 3D model of the object. Any images taken of external or internal features may also be appended to the 3D model or even overlaid on the 3D model (like textures), based on the location and directional view associated with those images.

Abstract: Systems and methods for property valuation using automated valuation models are described herein, which involve a complex series of workflows for data processing, automated valuation modeling, and error detection—each of which are capable of leveraging machine learning algorithms/techniques and can be combined and operated together in a specific manner in order to improve data availability and data quality, improve the accuracy of generated property value estimates, improve the performance of the models over time, and allow the property value estimation to be adapted to various use cases. Estimation of property value may involve an ensemble model which reconciles the outputs of different sub-models based on a use case, with the sub-models using different approaches that have their own strengths and weaknesses.

Abstract: Systems and methods are disclosed for the generation and interactive display of three-dimensional (3D) building models, for the determination and simulation of risk associated with the underlying buildings, for the prediction of changes to the underlying buildings associated with the risk, for the generation and display of updated 3D building models factoring in the risk or predicted changes, and for the collection and display of relevant contextual information associated with the underlying building while presenting a 3D building model. The 3D building model can be displayed in an augmented reality (AR) view, and a user can interact with the 3D building model via controls present in the AR view and/or by moving within the real-world location in which the user is present.

Abstract: A hazard visualization system that can use artificial intelligence to identify locations at which hazards have occurred and a cause therein and to predict locations at which hazards may occur in the future is described herein. As a result, the hazard visualization system may reduce the likelihood of structural damage and/or loss of life that could otherwise occur due to natural disasters or other hazards. For example, the hazard visualization system can train an artificial intelligence model to predict the date, time, type, severity, path, and/or other conditions of a hazard that may occur at a geographic location. As another example, the hazard visualization system can train an artificial intelligence model to identify equipment or other infrastructure depicted in geographic images.

Abstract: A system is disclosed that implements features for generating a user-specific content page. In one embodiment, the system includes an identity lifecycle management (ILM) system a platform as a service (PaaS) system, and an application system. The ILM system can store associations of a user with personas, and a list of features of applications, run the application system, associated with each persona. The PaaS system may retrieve data values of the features of the applications associated with the personas of the user from the application system to generate a user-specific content page for the user.

Abstract: A system, apparatus, computer program product, and method use a convolutional neural network to auto-determine a first floor height (FFH) and a FFH elevation (FFE) of a building. The FFH, and FFE of the building are determined with respect to the terrain or surface of the parcel of land on which the building is located. In turn, by knowing the FFH and/or FFE of the building on the parcel, it is possible to use that information while performing a flood risk assessment to a property without requiring a personal inspection of the parcel by a human.

Abstract: A system, and method perform compliance checking of computer records for MLS services. The compliance checking includes detecting multiple-listing-service (MLS) contract compliance with a MLS, gathering MLS-related data regarding an MLS subscriber from at least one database, checking for a non-compliance incident of the MLS-related data with the MLS service requirements, and in response to detection of a non-compliance incident, trigger a computer-based resolution process to resolve the non-compliance incident.

Abstract: A system, and method perform compliance checking of computer records for MLS services. The compliance checking includes detecting multiple-listing-service (MLS) contract compliance with a MLS, gathering MLS-related data regarding an MLS subscriber from at least one database, training an AI engine with input data containing as features MLS service requirements that correspond to contractual obligations of the MLS subscriber under a MLS license, applying the MLS-related data to the AI engine, after the AI engine is trained, and checking for a non-compliance incident of the MLS-related data with the MLS service requirements, and in response to detection of a non-compliance incident, trigger a computer-based resolution process to resolve the non-compliance incident.

Abstract: A method, system and computer program product assess risk of an unauthorized API login and mitigate damage from an unauthorized API login. The method includes collecting in a database license attributes of a user license, user profile attributes, and database content change attributes; receiving an API login request; comparing features of the API login request to at least one of the database license attributes, user profile attributes, and database content change attributes against a predetermined threshold; assessing a risk of the an unauthorized API login request based on a result of the comparison; and based on a level of the assessed risk, implemented protective action to mitigate harm that may result from an unauthorized user from accessing information or services from a computer system by way of an API.

Abstract: A system, apparatus, computer program product, and method use a convolutional neural network to auto-determine a first floor height (FFH) and a FFH elevation (FFE) of a building. The FFH, and FFE of the building are determined with respect to the terrain or surface of the parcel of land on which the building is located. In turn, by knowing the FFH and/or FFE of the building on the parcel, it is possible to use that information while performing a flood risk assessment to a property without requiring a personal inspection of the parcel by a human.

Abstract: A computer system and associated processes are disclosed for grouping similar real estate properties into contiguous neighborhoods, and for generating neighborhood-specific models capable of estimating property values within their respective neighborhoods. A clustering component uses various sources of property-level data to group properties based on measures of property similarity. For example, the clustering component may use features extracted from property images to identify properties with similar characteristics. As another example, the clustering component may measure property similarity based on how frequently specific properties are designated as comparable in appraisal reports. A model generator uses a machine learning process to determine, for specific neighborhoods, correlations between property attributes and values, and uses these correlations to generate the neighborhood specific models.

Abstract: A hazard visualization system that can use artificial intelligence to identify locations at which hazards have occurred and a cause therein and to predict locations at which hazards may occur in the future is described herein. As a result, the hazard visualization system may reduce the likelihood of structural damage and/or loss of life that could otherwise occur due to natural disasters or other hazards. For example, the hazard visualization system can train an artificial intelligence model to predict the date, time, type, severity, path, and/or other conditions of a hazard that may occur at a geographic location. As another example, the hazard visualization system can train an artificial intelligence model to identify equipment or other infrastructure depicted in geographic images.

Abstract: A method, system and computer program product assess risk of an unauthorized API login and mitigate damage from an unauthorized API login. The method includes collecting in a database license attributes of a user license, user profile attributes, and database content change attributes; receiving an API login request; comparing features of the API login request to at least one of the database license attributes, user profile attributes, and database content change attributes against a predetermined threshold; assessing a risk of the an unauthorized API login request based on a result of the comparison; and based on a level of the assessed risk, implemented protective action to mitigate harm that may result from an unauthorized user from accessing information or services from a computer system by way of an API.

Abstract: Systems and methods for determining a boundary from evaluation records for objects are disclosed. In some embodiments, evaluation records for objects (e.g., appraisal records for real estate properties) are accessed. The evaluation records can be used to identify objects with similar characteristics. By representing objects identified as nodes in a graph, edges between nodes representing the identified objects can be established. A network generated from the nodes and edges can be used to identify a boundary comprising objects having similar characteristics.

Abstract: A method, system and computer program product assess risk of an unauthorized API login and mitigate damage from an unauthorized API login. The method includes collecting in a database license attributes of a user license, user profile attributes, and database content change attributes; receiving an API login request; comparing features of the API login request to at least one of the database license attributes, user profile attributes, and database content change attributes against a predetermined threshold; assessing a risk of the an unauthorized API login request based on a result of the comparison; and based on a level of the assessed risk, implemented protective action to mitigate harm that may result from an unauthorized user from accessing information or services from a computer system by way of an API.