Techniques and systems are described for generating and using a sound localization model. A described technique includes obtaining for a building a sound sensor map indicating locations of first and second sound sensor devices in respective first and second rooms of the building; causing an autonomous device to navigate to the first room and to emit, during a time window, sound patterns at one or more frequencies within the first room; receiving sound data including first and second sound data respectively from the first and second sound sensor devices that are observed during the time window; and generating and storing a sound localization model based on the sound sensor map, autonomous device location information, and the received sound data, the model being configured to compensate for how sounds travels among rooms in at least a portion of the building such that an origin room of a sound source is identifiable.

Disclosed are techniques to conserve battery of an endpoint device. Example techniques include adjusting the size of messages transmitted by an endpoint device and/or adjusting the transmission rate of an endpoint device. In some configurations, the one or more criteria are used by an endpoint device to determine what data fields to include within a message and/or adjust a transmission rate associated with the transmission of messages by the endpoint device. For instance, the one or more criteria may include the battery level of the device, the time of year, whether the data has already been transmitted by the endpoint device, whether the data has been acknowledged as received by another device, whether the endpoint device has been instructed by another device to reduce the message size and/or adjust the transmission rate, and the like.

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.

A wireless sensor network at a monitored location can be configured to generate sensor channel(s) of data to assess operational conditions at the monitored location. Inputs based on the sensor channel(s) of data are provided to a host system for analysis of a demand to one or more resources at the monitored location. Response messages can be generated based on the demand analysis and transmitted to actuator(s) at the monitored location to effect an adjustment to the operational conditions.

Systems and methods for temperature monitoring and environmentally related calculations are disclosed herein. A system according to embodiments herein may include a memory, a network interface, and one or more processors. The system may receive one or more environmental readings from a sensor taking readings at an environmentally controlled area. The system may further determine a timestamp corresponding to each of the one or more readings and calculate, using the one or more readings and their corresponding timestamps, an exposure of a good stored within the temperature-controlled area. The system may further determine that the calculated exposure of the good has surpassed a pre-determined exposure threshold for the good and send an electronic message configured to indicate such determination to a user. The system may use a neural network to predict future readings and/or events based on current readings and use the predictions in methods described herein.

A method and system for inspecting and monitoring an elevator installation includes sending an autonomous flying object having at least one sensor to the elevator installation, and granting access to a hoistway of the elevator installation to the autonomous flying object. The autonomous flying object is positioned within the hoistway, and data collected by the associated sensor is sent to a remote elevator service center. The autonomous flying object and the associated sensor can be used to monitor and inspect the elevator installation on a temporary basis, for example for a specific number of hours, days or weeks. Once the autonomous flying object has gained access to the hoistway, the elevator installation can resume normal operation thereby keeping downtime to a minimum. After completing its tasks at one elevator installation, the autonomous flying object can be directed by the remote elevator service center to monitor and inspect another elevator installation.

A wireless sensor network at a monitored location can be configured to generate sensor channel(s) of data to assess operational conditions at the monitored location. Inputs based on the sensor channel(s) of data are provided to a host system for analysis of a demand to one or more resources at the monitored location. Response messages can be generated based on the demand analysis and transmitted to actuator(s) at the monitored location to effect an adjustment to the operational conditions.

Systems and methods for temperature monitoring and environmentally related calculations are disclosed herein. A system according to embodiments herein may include a memory, a network interface, and one or more processors. The system may receive one or more environmental readings from a sensor taking readings at an environmentally controlled area. The system may further determine a timestamp corresponding to each of the one or more readings and calculate, using the one or more readings and their corresponding timestamps, an exposure of a good stored within the temperature controlled area. The system may further determine that the calculated exposure of the good has surpassed a pre-determined exposure threshold for the good and send an electronic message configured to indicate such determination to a user. The system may use a neural network to predict future readings based on current readings and use the predicted future readings in methods described herein.

Examples disclosed herein relate generally to providing frames at a network port. Some examples relate to an apparatus. The apparatus may include a network port to directly couple the apparatus to a switch. The apparatus may also include a transmission logic to provide a frame at the network port at a time slot of a switch-associated cycle time. The transmission logic may provide the frame at the time slot at least partially responsive to an offset value and a port number. Related devices, systems and methods are also disclosed.

Provided is an energy harvester and an engine monitoring system. An engine monitoring system using an energy harvester includes at least one or more self-power generation wireless sensor nodes for generating electric energy using the energy harvester and monitoring an engine; and a management server that receives and manages sensing information received from the self-power generation wireless sensor nodes. The self-power generation wireless sensor nodes includes sensor modules monitoring the engine; a data processing unit identifying and packaging sensing information; a wireless communication unit wirelessly transmitting the packaged sensing information to the management server; the energy harvester generating electric energy to be supplied to the sensor modules, the data processing unit, and the wireless communication unit by converting vibration energy of the engine into the electric energy; and a power management unit controlling the electric energy to supply the electric energy to the sensor modules, the data processing unit.