Abstract: Driving skill data is gathered with one or more accelerometers during a driving session of a first student driver, including one or more of acceleration data, braking data, or steering data and wherein the driving skill data includes one or more of a timestamp or location stamp. A driving session report is generated with a computer processor. The driving session report includes a calculation of one or more of a student driver acceleration skill score based on the acceleration data, a student driver braking skill score based on the braking data, or a student driver steering skill score based on the steering data and storing the one or more scores on a computer-readable medium. The driving session report is displayed. Driving skill data may be gathered and driving session reports may be generated for subsequent student drivers.

Abstract: A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage.

Abstract: A damage assessment module operating on a computer system generating a model undamaged roof shingle includes using a method based on the average nearest-neighbor distance. The damage assessment module identifies a set of points comprising a first point cloud representing a first shingle and a set of points from a second point cloud representing a second shingle. The damage assessment module then calculates an average nearest-neighbor distance for the set of points. Based on the average, the damage assessment module calculates a threshold distance. The damage assessment module then stores the set of points to memory as a point cloud representing a model roof shingle that can be later retrieved and compared to point clouds of individual shingles. The damage assessment module improves the consistency and accuracy associated with assessment of the roof and eliminates the need for the estimator to use subjective assessment results, which can be inadequate.

Abstract: A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage. The report may be used to determine the financial cost of the damage and/or determine whether the roof should be replaced or repaired. In addition to eliminating the need for an estimator to physically climb onto a roof for evaluation purposes, the damage assessment module improves the consistency and accuracy associated with estimating damage to a roof.

Abstract: A damage assessment module operating on a computer system automatically evaluates a property, estimating damage to the property by analyzing a point cloud of a property. The damage assessment module identifies individual point clusters or segments from the point cloud and detects potentially damaged areas of the property surface by identifying outlier points in the point clusters. The damage assessment module may be used to determine the financial cost of the damage and/or determine whether the property should be replaced or repaired. In addition to eliminating the need for an estimator to visit the property in person, the damage assessment module improves the consistency and accuracy associated with estimating damage to a property.

Abstract: Driving skill data is gathered with one or more accelerometers during a driving session of a first student driver, including one or more of acceleration data, braking data, or steering data and wherein the driving skill data includes one or more of a timestamp or location stamp. A driving session report is generated with a computer processor. The driving session report includes a calculation of one or more of a student driver acceleration skill score based on the acceleration data, a student driver braking skill score based on the braking data, or a student driver steering skill score based on the steering data and storing the one or more scores on a computer-readable medium. The driving session report is displayed. Driving skill data may be gathered and driving session reports may be generated for subsequent student drivers.

Abstract: A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage. The report may be used to determine the financial cost of the damage and/or determine whether the roof should be replaced or repaired. In addition to eliminating the need for an estimator to physically climb onto a roof for evaluation purposes, the damage assessment module improves the consistency and accuracy associated with estimating damage to a roof.

Abstract: The method, system, and computer-readable medium facilitates monitoring one or more eyes of a vehicle operator during a driving session to generate a plurality of gaze location logs with gaze location values and timestamps. The gaze location value may be generated by determining a focal point of the vehicle operator's gaze, determining which of a plurality of areas of the vehicle is associated with the focal point, and assigning the gaze location value based on the area of the vehicle associated with the focal point. The gaze location logs may be analyzed to determine the duration of the vehicle operator's gaze at each area of the vehicle. Based on the duration of the vehicle operators gaze, recommendations to improve vehicle operator performance may be determined and communicated to the vehicle operator.

Abstract: A damage assessment module operating on a computer system automatically evaluates a property, estimating damage to the property by analyzing a point cloud of a property. The damage assessment module identifies individual point clusters or segments from the point cloud and detects potentially damaged areas of the property surface by identifying outlier points in the point clusters. The damage assessment module may be used to determine the financial cost of the damage and/or determine whether the property should be replaced or repaired. In addition to eliminating the need for an estimator to visit the property in person, the damage assessment module improves the consistency and accuracy associated with estimating damage to a property.