A method of communicating configuration data of a tire pressure monitoring device configured to be affixed to a wheel is disclosed. The method includes, at the tire pressure monitoring device, receiving a request to confirm configuration data, and responsive to receipt of the request to confirm configuration data, transmitting a configuration data signal which encodes the configuration data. The configuration data signal is configured to be received and understood by a human.

A method of communicating configuration data of a tire pressure monitoring device configured to be affixed to a wheel is disclosed. The method includes, at the tire pressure monitoring device, receiving a request to confirm configuration data, and responsive to receipt of the request to confirm configuration data, transmitting a configuration data signal which encodes the configuration data. The configuration data signal is configured to be received and understood by a human.

Embodiments described herein provide an animal acoustic augmentor (AAA) for an animal acoustic augmentation system. The AAA includes an audio system configured to generate audio proximal and/or for delivery to an ear of an animal and a logic device configured to communicate with and control operation of the audio system. The logic device is configured to detect an AAA trigger associated with operation of the AAA and/or the audio system and generate an animal-audible trigger response via the audio system of the AAA based, at least in part, on the detected AAA trigger, where the animal-audible trigger response includes a preprogrammed AAA trigger response stored within a memory of the AAA and/or a live AAA trigger response based, at least in part, on a control sequence and/or an owner command provided by a personal electronic device associated with the AAA and/or an acoustic environment of the animal.

Embodiments described herein provide an animal acoustic augmentor (AAA) for an animal acoustic augmentation system. The AAA includes an audio system configured to generate audio proximal and/or for delivery to an ear of an animal and a logic device configured to communicate with and control operation of the audio system. The logic device is configured to detect an AAA trigger associated with operation of the AAA and/or the audio system and generate an animal-audible trigger response via the audio system of the AAA based, at least in part, on the detected AAA trigger, where the animal-audible trigger response includes a preprogrammed AAA trigger response stored within a memory of the AAA and/or a live AAA trigger response based, at least in part, on a control sequence and/or an owner command provided by a personal electronic device associated with the AAA and/or an acoustic environment of the animal.

A portable system that allows blind or visually impaired persons to interpret the surrounding environment by sound or touch, said system comprising: two cameras separate from one another and configured to capture an image of the environment simultaneously, and means for generating sound and/or touch output signals. Advantageously, the system also comprises processing means connected to the cameras and to the means for generating sound and/or touch signals. The processing means are configured to combine the images captured in real time and to process the information associated with at least one vertical band with information relating to the depth of the elements in the combined image.

A portable system that allows blind or visually impaired persons to interpret the surrounding environment by sound or touch, said system comprising: two cameras separate from one another and configured to capture an image of the environment simultaneously, and means for generating sound and/or touch output signals. Advantageously, the system also comprises processing means connected to the cameras and to the means for generating sound and/or touch signals. The processing means are configured to combine the images captured in real time and to process the information associated with at least one vertical band with information relating to the depth of the elements in the combined image.

A universal threat awareness management system for occupant safety has a primary interface device that is positioned with a secured location. The interface device enables an authorized individual to monitor and manage an entire facility for hazardous situations. The system also has audio output devices, visual output devices, and environmental sensors. The audio output devices, visual output devices, and environmental sensors are positioned external to the secured location and enable the authorized individual to monitor and communicate with other people within and around the facility. The system is intended to be used as a campus-wide threat mitigation platform.

A universal threat awareness management system for occupant safety has a primary interface device that is positioned with a secured location. The interface device enables an authorized individual to monitor and manage an entire facility for hazardous situations. The system also has audio output devices, visual output devices, and environmental sensors. The audio output devices, visual output devices, and environmental sensors are positioned external to the secured location and enable the authorized individual to monitor and communicate with other people within and around the facility. The system is intended to be used as a campus-wide threat mitigation platform.

Embodiments described herein relate to a threat detection system that shows a user an incident as it develops in real time by leveraging artificial intelligence (AI) to more accurately focus cameras and highlight the areas of concern within those feeds, providing a much more efficient user interface to the operator. These annotated feeds and feed focused triggering events can also be connected to third party systems. This timeline of events and evidence (small annotated clip of detection when available) is archived and can be reviewed at a later date, containing an accurate timeline of the incident as it progressed.

Embodiments described herein relate to a threat detection system that shows a user an incident as it develops in real time by leveraging artificial intelligence (AI) to more accurately focus cameras and highlight the areas of concern within those feeds, providing a much more efficient user interface to the operator. These annotated feeds and feed focused triggering events can also be connected to third party systems. This timeline of events and evidence (small annotated clip of detection when available) is archived and can be reviewed at a later date, containing an accurate timeline of the incident as it progressed.