Abstract: Systems and methods in accordance with the present disclosure include techniques for predicting an accident, comprising: receiving monitoring data from a user device associated with a user, the monitoring data indicative of movement of the user; determining a user action based on the monitoring data using a first artificial intelligence model; and determining a probability of occurrence of one or more potential accidents based on the determined user action and the monitoring data using a second artificial intelligence model.

Abstract: Systems and methods in accordance with the present disclosure include techniques for predicting an accident, comprising: receiving monitoring data from a user device associated with a user, the monitoring data indicative of movement of the user; determining a user action based on the monitoring data using a first artificial intelligence model; and determining a probability of occurrence of one or more potential accidents based on the determined user action and the monitoring data using a second artificial intelligence model.

Abstract: Systems and methods in accordance with the present disclosure include techniques for predicting an accident, comprising: receiving monitoring data from a user device associated with a user, the monitoring data indicative of movement of the user; determining a user action based on the monitoring data using a first artificial intelligence model; and determining a probability of occurrence of one or more potential accidents based on the determined user action and the monitoring data using a second artificial intelligence model.

Abstract: A computer system generates a tactile force model for a tactile force sensor by performing a number of calibration tasks. In various embodiments, the calibration tasks include pressing the tactile force sensor while the tactile force sensor is attached to a pressure gauge, interacting with a ball, and pushing an object along a planar surface. Data collected from these calibration tasks is used to train a neural network. The resulting tactile force model allows the computer system to convert signals received from the tactile force sensor into a force magnitude and direction with greater accuracy than conventional methods. In an embodiment, force on the tactile force sensor is inferred by interacting with an object, determining the motion of the object, and estimating the forces on the object based on a physical model of the object.