Smart sensor methods and systems are described that improve on prior systems. An example device includes a sensor, a memory, a network connection, and two processing units, wherein a first processing unit compares current data provided by the first sensor to the reference data previously provided by the first sensor. Based on the result of the comparison, a second processing unit may be enabled to process the current data, or may be disabled to prevent the second processing unit from processing the current data.

A distributed air data module system includes several air data systems and a control module communicatively connected to each air data system via a data channel. Each of the air data systems includes a sensor that is configured to sense an air data parameter and to provide a sensor output signal that is indicative of the sensed air data parameter, and a sensor analog-to-digital converter that produces a digital air data parameter signal that is representative of the sensor output signal. Each air data system has an associated air data system address code. The control module is configured to generate a selected air data system address code corresponding to a selected air data systems, receive the digital air data parameter signal associated with the selected air data system via the data channel, and transmit the digital air data parameter signal via an aircraft data bus.

Techniques are provided which may be implemented using various methods and/or apparatuses in a mobile device to address maximum permissible exposure (MPE) proximity sensor failure. A mobile device may include a maximum permissible exposure (MPE) sensor control unit to actively monitor signals associated with proper operation of the MPE proximity sensors. Upon detecting an anomaly in any of these signals. such as a value drop below a given threshold, an MPE sensor control Unit will inform an AP (application processor, or other processor or controller) which in turn trigger display of a warning message on the display of the mobile device or the issuance of other warnings such an audible or tactile alert to inform the end user about the maximum permissible exposure (MPE) proximity sensor malfunction and/or notify the end use of a condition resulting in deactivation of the 5G new radio transceiver.

A computer-implemented method for detecting vehicle crashes is presented. The method may include detecting, at a first mobile computing device a condition corresponding to a potential crash of a vehicle. The method may also include operating a beacon receive mode in response to detecting the potential crash condition, and receiving data from a second mobile computing device operating in a beacon transmit mode, the data indicating that the second mobile computing device detected an actual crash condition of the vehicle. The method may further include confirming, based on the potential crash condition and the data received from the second mobile computing device, that the potential crash is an actual crash.

The disclosure relates to a method and a system for a wireless data communication between a sensor system and a receiver capable of receiving analyte values sensed by the sensor system in a continuous analyte monitoring. The method includes establishing an unconnected mode operation for the system. The receiver receives a first data package broadcasted by the sensor system that has first status data indicative of a device status and/or an analyte value status. The first status data is processed by a receiver controller. A connected mode operation is established for the system responsive to determining at least one of a critical device status and a critical analyte value status. The establishing includes establishing a communication channel between the sensor system and the receiver and receiving a second data package transmitted by the sensor system in the receiver, the second data package comprising one or more analyte values.

Embodiments relate to a closed loop communication system. The system can include a consumer mobile device configured with a mobile application to identify its load consumption pattern and communicate the identified load consumption pattern to a utility device. The mobile device also sets a limit for maximum energy consumption through the mobile application. The system can also include the utility device that receives the identified load consumption pattern, and configured to send a short message service (SMS) alert to the mobile device to alert the mobile device to read meter energy consumption reading from energy meter and share with utility device due to direct connection failure with an energy meter. The system can also include an energy meter configured to communicate with the utility device, wherein the utility device attempts to receive the meter energy consumption reading from the energy meter.

A riding floor cleaning machine having an intelligent system including a main frame sub-assembly, a steering and drive wheel sub-assembly, a solution tank sub-assembly, a recovery tank sub-assembly, a recovery tank cover sub-assembly, a control panel sub-assembly, a main controller sub-assembly, a seat and detergent system sub-assembly, a battery sub-assembly, a scrub head sub-assembly, a scrub head lift sub-assembly, a squeegee sub-assembly, a solution and detergent sub-assembly, and an intelligent system associated with at least one of the above-identified sub-assemblies, wherein the intelligent system selectively gathers, obtains, monitors, stores, records, and/or analyzes data associated with components of the riding floor cleaning machine, and controllably communicates and/or disseminates such data with another system and/or user.

A sensor system for a structure comprises a sensor node in force transmitting contact with an impact receiving surface of a structure envelope of the structure. The sensor node is configured to generate first sensor data associated with the structure envelope of the structure and perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset. The sensor system includes a sensor hub in communication with the sensor node. The sensor hub is configured to receive the first filtered dataset from the sensor node and perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor node to produce the first sensor data.

Systems and methods are described for securely monitoring a shipping container for an environmental anomaly using elements of a wireless node network of sensor-based ID nodes disposed within the container and a command node associated with the container. The method has the command node identifying which of the ID nodes are confirmed as trusted sensors based upon a security credential specific to each of the ID nodes; monitoring only the confirmed ID nodes for sensor data broadcast those ID nodes; detecting the anomaly based upon the sensor data from at least one of the confirmed ID nodes; automatically generating an alert notification related to the detected environmental anomaly for the shipping container; and transmitting the alert notification to the external transceiver to initiate a mediation response related to the detected environmental anomaly.

Embodiments disclosed herein include a power management apparatus including a smart circuit breaker (“iCB”) that wirelessly communicates with one or multiple power consuming devices. The iCB also communicates with a power provider (power company) to manage preset power quotas for consumers. Aspects include management of device priorities such that devices with higher priorities receive power before those with lower priorities when quotas are exceeded for a consumer premises.