Methods and systems for predicting surface failure of a surface, for example a method comprising the steps of: obtaining a group of measured datasets, each including: a measurement value of at least a first type for each of a plurality of grid elements, each grid element associated with a location on the surface; and a time value, such that the group of datasets includes datasets associated with a plurality of unique time values, identifying an interface set of grid elements for each measured dataset, each interface set comprising grid elements of the associated measured dataset meeting a connection threshold according to a connection rule in dependence on the measurement values of the grid elements, determining a risk of surface failure in accordance with identification of a pattern of grid elements of the interface set which has a persistent location with respect to the surface of interface sets over a plurality of measured datasets.

Methods and systems for predicting surface failure of a surface, for example a method comprising the steps of: obtaining a group of measured datasets, each including: a measurement value of at least a first type for each of a plurality of grid elements, each grid element associated with a location on the surface; and a time value, such that the group of datasets includes datasets associated with a plurality of unique time values, identifying an interface set of grid elements for each measured dataset, each interface set comprising grid elements of the associated measured dataset meeting a connection threshold according to a connection rule in dependence on the measurement values of the grid elements, determining a risk of surface failure in accordance with identification of a pattern of grid elements of the interface set which has a persistent location with respect to the surface of interface sets over a plurality of measured datasets.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for finding lost objects. In some implementations, a request for a location of an item is obtained. Current video data from one or more cameras is obtained. It is determined that the item is not shown in the current video data. Sensor data corresponding to historical video data is obtained. Events that likely occurred with the item and corresponding likelihoods for each of the events are determined. A likely location for the item is determined based on the likelihoods determined for the events. An indication of the likely location of the item is provided.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for finding lost objects. In some implementations, a request for a location of an item is obtained. Current video data from one or more cameras is obtained. It is determined that the item is not shown in the current video data. Sensor data corresponding to historical video data is obtained. Events that likely occurred with the item and corresponding likelihoods for each of the events are determined. A likely location for the item is determined based on the likelihoods determined for the events. An indication of the likely location of the item is provided.

In a bio-threat alert infrastructure system and method, an analyzing processor applies statistical algorithms to the collected quantitative data to precisely estimate event data, including time and position data, associated the development of a bio-threat. An encoding processor encodes the event data into a bio-threat alert signal. A transmitting element transmits the signal for reception by a bio-threat alert device. In the bio-threat alert device, and an associated method, a receiving element receives the signal. A decoding processor decodes the signal into the event data. A presentation element presents the event data to a user of the device.

In a bio-threat alert infrastructure system and method, an analyzing processor applies statistical algorithms to the collected quantitative data to precisely estimate event data, including time and position data, associated the development of a bio-threat. An encoding processor encodes the event data into a bio-threat alert signal. A transmitting element transmits the signal for reception by a bio-threat alert device. In the bio-threat alert device, and an associated method, a receiving element receives the signal. A decoding processor decodes the signal into the event data. A presentation element presents the event data to a user of the device.

Systems and methods for detecting potential theft and identifying individuals having a history of committing theft use an electromagnetic emission associated with a personal electronic device associated with an individual is received from at least one of a sensor that is coupled to at least one of a traffic camera or an aerial drone camera. One or more signal properties of the electromagnetic emission are analyzed to determine an emission signature. Video data and video analytics are correlated with the emission signature to identify the individual having possession of the item. The emission signature and video data are stored for later use during a checkout procedure. If an emission signature detected at a checkout station matches that of the individual having possession of the item, and the item is not processed through the checkout station, an alert is issued and the individual is flagged as a potential shoplifter.

Systems and methods for detecting potential theft and identifying individuals having a history of committing theft use an electromagnetic emission associated with a personal electronic device associated with an individual is received from at least one of a sensor that is coupled to at least one of a traffic camera or an aerial drone camera. One or more signal properties of the electromagnetic emission are analyzed to determine an emission signature. Video data and video analytics are correlated with the emission signature to identify the individual having possession of the item. The emission signature and video data are stored for later use during a checkout procedure. If an emission signature detected at a checkout station matches that of the individual having possession of the item, and the item is not processed through the checkout station, an alert is issued and the individual is flagged as a potential shoplifter.

The present disclosure relates to system(s) and method(s) for alerting one or more service providers based on analysis of real-time sensor data. The system is configured to receive real-time sensor data and historical sensor data captured by one or more agent devices. Further, the system is configured to determine an anomaly corresponding to a target agent device from the one or more agent devices, based on comparison of the real-time sensor data and one or more predefined threshold parameters. The system is further configured to generate an alert corresponding to the anomaly and identify one or more service providers, affected by the anomaly, based on analysis of the historical sensor data and the anomaly. Further, the system is configured to transmit the alert to the one or more service providers, thereby alerting the one or more service providers.

The present disclosure relates to system(s) and method(s) for alerting one or more service providers based on analysis of real-time sensor data. The system is configured to receive real-time sensor data and historical sensor data captured by one or more agent devices. Further, the system is configured to determine an anomaly corresponding to a target agent device from the one or more agent devices, based on comparison of the real-time sensor data and one or more predefined threshold parameters. The system is further configured to generate an alert corresponding to the anomaly and identify one or more service providers, affected by the anomaly, based on analysis of the historical sensor data and the anomaly. Further, the system is configured to transmit the alert to the one or more service providers, thereby alerting the one or more service providers.