Abstract: A method can include training a machine learning algorithm to determine a duration of a new work order, based on (a) historical input data for the machine learning algorithm and (b) historical output data for the machine learning algorithm. The method can also include determining one or more work orders for a service provider comprising: determining, by the machine learning algorithm, as trained, one or more durations of the one or more work orders; and determining an optimized service route for the one or more work orders. The method can further include updating a work schedule for the service provider based on the optimized service route. Other embodiments are also provided.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform: determining one or more work orders for a service provider; determining an optimal service route for the one or more work orders; updating an available time slot in a work schedule of the service provider; and transmitting the work schedule updated with the optimal service route to be displayed on a user interface executed on a device of the service provider. Other embodiments are also provided.

Abstract: Systems, methods, and other embodiments described herein relate to improving crash prediction through correlating an observed response and a predicted response of a vehicle. In one embodiment, a method includes generating the predicted response for the vehicle as a function of a response model and according to current vehicle inputs that are control inputs associated with steering, braking, and accelerating the vehicle. The response model is a learning model that predicts behaviors of the vehicle. The method includes computing a residual indicating an extent of correlation between the predicted response and the observed response. The method includes, in response to determining the residual satisfies a crash threshold that indicates an anomaly between the predicted response and the observed response, providing an alert indicating the vehicle has likely crashed.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: estimating, using a machine learning model, a respective budget for expenditures based on respective parameters of each of one or more project initiatives associated with physical stores; determining, using a mixed integer linear programming formulation, a time window to execute the each of the one or more project initiatives; generating one or more respective recommendations for the each of the one or more project initiatives for a predetermined time period; and sending instructions to display the one or more respective recommendations on a graphical user interface, wherein the graphical user interface displays a respective status of each of the one or more respective recommendations. Other embodiments are disclosed.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform: determining one or more work orders for a service provider; determining an optimal service route for the one or more work orders; updating an available time slot in a work schedule of the service provider; and transmitting the work schedule updated with the optimal service route to be displayed on a user interface executed on a device of the service provider. Other embodiments are also provided.

Abstract: System, methods, and other embodiments described herein relate to improving crash prediction through correlating an observed response and a predicted response of a vehicle. In one embodiment, a method includes generating the predicted response for the vehicle as a function of a response model and according to current vehicle inputs that are control inputs associated with steering, braking, and accelerating the vehicle. The response model is a learning model that predicts behaviors of the vehicle. The method includes computing a residual indicating an extent of correlation between the predicted response and the observed response. The method includes, in response to determining the residual satisfies a crash threshold that indicates an anomaly between the predicted response and the observed response, providing an alert indicating the vehicle has likely crashed.

Abstract: System, methods, and other embodiments described herein relate to determining a location of a vehicle within a structure. In one embodiment, a method includes collecting, from at least one sensor in the vehicle, sensor data that indicates information associated with control of the vehicle in the structure. The method includes classifying gradients along a path of the vehicle through the structure according to the sensor data. The method includes identifying traversed levels of the structure along the path according to the gradients. The method includes providing the location including at least an indicator of the traversed levels as an electronic output.

Abstract: In an embodiment, a driver-scoring device detects harsh events performed by an operator of a vehicle driven a number of distance units by the operator during a first period of time. Each of the detected harsh events has a respective g-force exceeding a threshold g-force. The driver-scoring device determines a penalty score including a ratio of a harsh-event score added to a sum of respective event-penalty scores for each of the detected harsh events to a metric score parameter. The harsh-event score includes a ratio of a number of the detected harsh events to the number of distance units driven by the operator during the first period of time. The respective event-penalty score for each of the detected harsh events includes a respective ratio of a penalty factor associated with the detected harsh event to the number of distance units driven by the operator during the first period of time.

Abstract: System, methods, and other embodiments described herein relate to determining a location of a vehicle within a structure. In one embodiment, a method includes collecting, from at least one sensor in the vehicle, sensor data that indicates information associated with control of the vehicle in the structure. The method includes classifying gradients along a path of the vehicle through the structure according to the sensor data. The method includes identifying traversed levels of the structure along the path according to the gradients. The method includes providing the location including at least an indicator of the traversed levels as an electronic output.

Abstract: A multiphase current interrupter is provided for interrupting a phase current between two contacts in an electrical phase. The current interrupter includes a first ablative chamber disposed around contacts for a first electrical phase. The first chamber has an ablative material thereon that causes a shock wave when an electrical arc is generated in an arc zone for the first electrical phase during a separation of the contacts therein. The current interrupter further includes at least a second ablative chamber disposed around contacts for at least a second electrical phase. The second chamber has an ablative material thereon that causes a shock wave when an electrical arc is generated in an arc zone for the second electrical phase during a separation of the contacts therein. An interconnecting structure provides fluid communication between the first ablative chamber and the second ablative chamber. The interconnecting structure is adapted to dissipate a shock wave generated in any of the ablative chambers.

Abstract: A multiphase current interrupter is provided for interrupting a phase current between two contacts in an electrical phase. The current interrupter includes a first ablative chamber disposed around contacts for a first electrical phase. The first chamber has an ablative material thereon that causes a shock wave when an electrical arc is generated in an arc zone for the first electrical phase during a separation of the contacts therein. The current interrupter further includes at least a second ablative chamber disposed around contacts for at least a second electrical phase. The second chamber has an ablative material thereon that causes a shock wave when an electrical arc is generated in an arc zone for the second electrical phase during a separation of the contacts therein. An interconnecting structure provides fluid communication between the first ablative chamber and the second ablative chamber. The interconnecting structure is adapted to dissipate a shock wave generated in any of the ablative chambers.

Abstract: Apparatus for interrupting an electrical current between two contacts, such as a first contact and a second contact, is provided. The first and second contacts are separable away from one another to interrupt electrical current flowing between the contacts. An ablative chamber is disposed around the contacts. The chamber includes an ablative material that discharges a vapor when an electrical arc is generated in an arc zone during a separation of the contacts. A venting arrangement is provided in the ablative chamber. The venting arrangement is distributed along the arc zone to influence at least one parameter in the ablative chamber during an arc quenching event. The parameter is selected to affect at least one arcing characteristic.