Methods, systems, and computer programs are presented for tools for fire monitoring. One method includes an operation for receiving, by a fire forecasting program, fire-related inputs including vegetation data, topography data, weather data, and fire-monitoring information. The fire-monitoring information includes the shape of fire burning in a region. Additionally, the method includes an operation for generating a fire forecast for the region based on the fire-related inputs. The fire forecast describes a state of the fire in the region at multiple times in the future, the state of the fire comprising a fire perimeter, a fire line intensity, and a flame height. Additionally, the method includes operations for receiving updated fire-monitoring information regarding a current state of the fire in the region, for modifying the fire forecast based on the updated fire-monitoring information, and for causing presentation of the fire forecast in a user interface.

A safety system for residential and commercial use includes a plurality of sensor modules that may be distributed about the environment, and that are in communication with a remote server environment and with other devices over a wireless communication network (e.g., cellular, Wi-Fi). Each sensor module includes a plurality of sensors that are capable of measuring or detecting characteristics of the environment such as smoke, small particulate, large particulate, chemicals, gasses, temperature, humidity, pressure, geolocation, and other characteristics. Analysis of sensor data is performed locally on the sensor module, as well as remotely on a server, in order to fuse and consider multiple sensor data points to identify emergency and non-emergency scenarios. By fusing and analyzing sensor data emergencies can be detected more quickly, and false alarms can be filtered out and avoided.

A method of transmitting a stale notification using one or more processors, comprising: receiving data about an interaction involving a user device, the data including a predefined period of time based on a complexity of the interaction; detecting no user inputs for the predefined period of time; and transmitting a notification to the user device indicating that the interaction is stale.

A method of transmitting a stale notification using one or more processors, comprising: receiving data about an interaction involving a user device, the data including a predefined period of time based on a complexity of the interaction; detecting no user inputs for the predefined period of time; and transmitting a notification to the user device indicating that the interaction is stale.

Presented are intelligent electronic footwear and apparel with controller-automated features, methods for making/operating such footwear and apparel, and control systems for executing automated features of such footwear and apparel. A method for automating a collaborative operation between an intelligent electronic shoe (IES) and an intelligent transportation management (ITM) system includes receiving, via a detection tag attached to the IES shoe structure, a prompt signal from a transmitter-detector module communicatively connected to a traffic system controller of the ITM system. In reaction to the received prompt signal, the detection tag transmits a response signal to the transmitter-detector module. The traffic system controller uses the response signal to determine a location of the IES's user, and the current operating state of a traffic signal proximate the user's location. The traffic system controller transmits a command signal to the traffic signal to switch from the current operating state to a new operating state.

A diagnostics and prediction system including a cloud system that continuously collects operating parameters from each of a number of environmental sensors and provides access to this data by a plurality of processing applications including (1) a predictive modeling system including (a) a health prediction system, (b) a sensor false alarm prediction system, (c) a zone false alarm prediction system and (d) a reporting system, (2) a system that diagnoses and predicts environmental hazardous areas and clusters areas based upon concentrations of CO in the site or building; and (3) a battery prediction system that predicts a battery life for the sensor.

A diagnostics and prediction system including a cloud system that continuously collects operating parameters from each of a number of environmental sensors and provides access to this data by a plurality of processing applications including (1) a predictive modeling system including (a) a health prediction system, (b) a sensor false alarm prediction system, (c) a zone false alarm prediction system and (d) a reporting system, (2) a system that diagnoses and predicts environmental hazardous areas and clusters areas based upon concentrations of CO in the site or building; and (3) a battery prediction system that predicts a battery life for the sensor.

A disaster preparation system may include a system controller. The system controller may include a device processor; and a non-transitory computer readable medium including instructions executable by the device processor to perform the following steps: receiving location data from a personal electronic device of a user; receiving forecast data regarding a predicted disaster; making a determination of a preparatory action to be executed on behalf of the user, based on the location data and the forecast data; and executing the preparatory action at a predetermined time relative to the predicted time of occurrence of the predicted disaster.

The present invention relates to methods and apparatus for detection of fire states in the presence of welding activities. In some examples, the welding detection system may algorithmically calculate a risk of a fire state developing. In some embodiments, the welding fire detection and prevention system may communicate warning states to users, supervisors, equipment and/or building monitoring systems.

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.