The present disclosure relates to a vehicle and a method for controlling an emergency call therefor, and more particularly, to a vehicle capable of performing a more stable and reliable emergency call and a method for controlling an emergency call therefor. The method for controlling an emergency call for a vehicle according to an embodiment includes monitoring a sensor signal in an accident determination unit of a control unit; determining whether or not an airbag is deployed based on the sensor signal in the accident determination unit; requesting an automatic emergency call from the accident determination unit to an emergency call unit of the control unit if the airbag is deployed as a result of the determination; and attempting to transmit a call to an emergency rescue center in response to the request from the emergency call unit.

Systems, methods and apparatus for automatic alarm management in a radio-frequency (RF) environment are disclosed. An apparatus calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of FFT data of the RF environment. The apparatus then creates a baseline based on the power distribution by frequency of the RF environment in a period of time, identifies at least one alarm situation based on a multiplicity of alarm triggering conditions by comparing the power distribution in real time or near real time to the baseline of the RF environment, identifies at least one signal based on the first derivative and the second derivative of FFT data in the at least one alarm situation, and sends at least one alarm comprising details of the at least one signal identified in the at least one alarm situation.

An event detection unit (EDU) for detecting an explosive event is provided. The EDU includes different types of sensors for measuring characteristics of an explosive event. The EDU includes an event notification component. The EDU also includes a processor that receives a measurement from the sensors and generates a combined non-event probability and a combined event probability based on that measurement that indicates a likelihood that an explosive event has not occurred or has occurred. The processor determines whether an explosive event has occurred based on the non-event probabilities and event probabilities. When an explosive event has been determined to occur, the processor directs the event notification component to output a notification that an explosive event has occurred.

A patient support apparatus, such as a bed, cot, stretcher, etc., for supporting a patient includes an exit detection system with multiple user-selectable modes of operation that each have different sensitivity levels for triggering an exit alert. The exit detection system also includes one or more non-user selectable modes of operation that are automatically implemented in response to a triggering action. For example, a transition mode may be automatically implemented when the user attempts to switch from a first user-selectable mode to a different user selectable mode, or a motion mode may be automatically implemented when movement of one or more components of the patient support apparatus occurs. In the transition mode, the exit detection system may use a least restrictive sensitivity level. In the motion mode, the exit detection system may inhibit exit alerts and/or change the criteria for issuing the exit alert.

An electronic monitoring bracelet, comprising a ring-shaped body configured so as to be mounted around a limb or an object, and an electronic monitoring system positioned in the body, the electronic monitoring system comprising an integrity detection system and an internal source of energy. The ring-shaped body is in the form of a rigid shell containing a chamber or several chamber sections in which are positioned components of the electronic monitoring system, the ring-shaped body entirely encircling the bracelet.

Embodiments of a central security monitoring device for reducing incidences of false alarms in a security system is disclosed. In one embodiment, a method is described, comprising receiving an alarm signal from an occupancy sensor via a receiver, receiving a second alarm signal from a barrier alarm device after receiving the alarm signal, determining, by a processor, an elapsed time from when the alarm signal from the occupancy sensor was received to when the second alarm signal from the barrier alarm device was received, transmitting, by the processor via a network interface, a message to a personal communication device indicating that a false alarm has occurred when the elapsed time is less than the predetermined time.

A method and a target monitoring system (TMS) to generate descriptive parameters of one or more target objects in a region are provided. The TMS dynamically receives first data comprising image data and/or audio data of the target objects in the region and second data comprising circumstantial information related to the first data from one or more sensors positioned in one or more spatial directions in the region over a network. The TMS filters the dynamically received first data and identifies the target objects in the region using image data extracted from the filtered data. The TMS generates descriptive parameters associated with each identified target object in the region using the filtered first data and the circumstantial information.

An infusion pump is configured to execute one or more alarm actions according to an alarm protocol. An alarm manager of the infusion pump is configured to receive alarm configuration comprising one or more alarm protocols, each protocol comprising one or more alarm parameters. The alarm manager is also configured to determine the presence of an alarm condition and perform an action associated with the one or more alarm parameters in response to determining the presence of the error condition.

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 process for tagging incident data captured by non-public-safety agency controlled cameras. In operation, an electronic computing device detects an occurrence of an incident and obtains an incident identifier associated with the incident. The electronic computing device determines that a non-public-safety agency controlled camera is available for capturing incident data corresponding to the incident. The electronic computing device then controls a public-safety agency controlled internet-of-things (IoT) infrastructure deployed at an incident location to emit a signal including one of an audible signal, visible signal, or a combination of audible and visible signals to enable the non-public-safety agency controlled camera to tag incident data using the emitted signal. The electronic computing device links a unique tag representing the emitted signal to the incident identifier. The electronic computing device then searches the incident data captured by the non-public-safety agency controlled camera using the unique tag representing the emitted signal.