Systems and apparatus are provided for monitoring and/or collecting data regarding environmental conditions and optionally personal health information, and generating warnings for a wearer based on acceptable limits for hazards. Using the collected data, the systems and apparatus communicate recommendations to the wearer to improve or maintain personal safety in the detected environment. Methods for monitoring environmental risks and generating warnings based on acceptable limits for hazards are also provided.

In some implementations, a system can transmit communications indicating an occurrence of a particular type of safety incident experienced by a user. Registration information that indicates that a plurality of safety devices of different types are to be registered with the user is initially obtained. Sensor data from the plurality of safety devices of different types are obtained. An occurrence of a particular type of safety incident experienced by the user is then selected from among a plurality of types of safety incidents. The selection may be based at least on the obtained sensor data and the obtained registration information. A communication is then provided to another user to indicate the occurrence of the particular type of safety incident experienced by the user in response to selecting the occurrence of the particular type of safety incident.

A system and method for investigating crimes occurring at locations that are communicatively connected by a central server is disclosed. The investigation is highly automated and obtains evidence using computer aided searches of historic surveillance data gathered at locations within a computer search area. The investigation also utilizes active searches of real-time surveillance data gathered at the locations in response to a be-on-the-look-out (BOLO) alert sent to the locations from the central server. Based on evidence obtained from these searches, the search area may be updated and the searches may be repeated to follow a moving crime pattern/route. In addition, the information provided from the searches may facilitate the prediction of a location that is likely to experience a crime in the future. Accordingly, the central server may transmit a high alert to the predicted location.

Optimizing and/or personalizing activities to a user through artificial intelligence and/or virtual reality.

Optimizing and/or personalizing activities to a user through artificial intelligence and/or virtual reality.

A flame detector configured for radiant energy monitoring, quantification, and information transmission. The system has at least one optical sensor channel, each including an optical sensor configured to receive optical energy from a surveilled scene within a field of view, the channel producing a signal providing a quantitative indication of the optical radiation energy received by the optical sensor within a sensor spectral bandwidth. A processor is responsive to the signal from the at least one optical sensor channel to provide a flame present indication of the presence of a flame, and a quantitative indication representing a magnitude of the optical radiation energy from the surveilled scene. An Artificial Neural Network may be used to provide an output corresponding to a flame condition.

A flame detector configured for radiant energy monitoring, quantification, and information transmission. The system has at least one optical sensor channel, each including an optical sensor configured to receive optical energy from a surveilled scene within a field of view, the channel producing a signal providing a quantitative indication of the optical radiation energy received by the optical sensor within a sensor spectral bandwidth. A processor is responsive to the signal from the at least one optical sensor channel to provide a flame present indication of the presence of a flame, and a quantitative indication representing a magnitude of the optical radiation energy from the surveilled scene. An Artificial Neural Network may be used to provide an output corresponding to a flame condition.

A state detection method includes: storing first information obtained from a first sensor and second information obtained from a second sensor in a predetermined segment in a storage, by a processor; specifying a behavior segment indicating a segment in which a subject performs a specific behavior and a non-behavior segment indicating a segment in which the subject does not perform the specific behavior using the second information stored in the storage, by the processor; determining a feature amount to be used for detecting a specific state of the subject using respective values of a plurality of feature amounts included in the first information stored in the storage in each of the behavior segment and the non-behavior segment and determining a threshold value for the determined feature amount, by the processor; and detecting the specific state of the subject from the information obtained from the first sensor, by the processor.

Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

The present invention relates to a two-wheeled vehicle accident reporting device having a retro-reflective cover, a deep learning recognition-based two-wheeled vehicle accident severity prediction server, and a two-wheeled vehicle accident severity prediction system including the same. The above reporting device includes: a body mounted on a two-wheeled vehicle; a retro-reflective cover having one end fixed to a lower end of the body, which is configured to be folded and unfolded in a scallop shape and reflects light; and a control board which is mounted on one side of the body, measures the speed and position of the two-wheeled vehicle using a plurality of sensors, and transmits accident occurrence information including speed information, impact amount information, location information and time information along with driver identification information through a wireless communication network to a two-wheeled vehicle accident severity prediction server when an accident occurs.