Katcher LLC

Roger S Hollander

John Trevor Morrison

Jace William Files

Shivshanker S Naimpally

In some examples, a sensor node is mounted to a structure and includes a microphone that is coupled to the structure. The sensor node records, at a first time, first audio data, using the microphone, filters the first audio data to create first filtered audio, records, at a second time that occurs after the first time, second audio data using the microphone, filters the second audio data to create second filtered audio, and determines a difference in decibels between a first volume of the first filtered audio and a second volume of the second filtered audio. If the sensor node determines that the difference in decibels is greater than a predetermined threshold, then the sensor node sends a notification of intrusion activity that includes the difference in decibels.

Using artificial intelligence (AI) to detect tunneling and other activities

In some examples, a sensor node is mounted to a wood item using two metal fasteners. The sensor node measures an ambient temperature using a thermometer, measures an ambient humidity using a hygrometer, and measures, using an ohmmeter, a resistance of the wood item between the two metal fasteners. The sensor node determines, based on the resistance, a moisture content of the wood item. Based at least in part on determining that: the ambient temperature is greater than a temperature threshold, the ambient humidity is greater than a humidity threshold, and the moisture content is greater than a moisture threshold, the sensor node captures audio data using a microphone that is coupled to the wood item. Based at least in part on determining that the audio data indicates pest activity, the sensor node sends, using a communication interface, a notification of pest activity that includes the audio data.

Using artificial intelligence (AI) to detect pest activity

In some examples, a central hub receives, from a sensor node that is mounted to a wood item, a notification including sensor data comprising audio data captured by a microphone of the sensor node that is coupled to the wood item. The audio data is captured by the sensor node based at least in part on the sensor node determining that: an ambient temperature is greater than a temperature threshold, an ambient humidity is greater than a humidity threshold, and a moisture content of the wood item is greater than a moisture threshold. The hub performs an analysis of the sensor data using an artificial intelligence algorithm. Based on the analysis, the hub determines a presence of a pest in the wood item and sends a message, indicating the presence of the pest, to a computing device.

In some examples, a sensor node is mounted to a wood item inside a wall of a building. The sensor node measures, using a thermometer, an ambient temperature inside the wall of the building, measuring, using a hygrometer, an ambient humidity inside the wall of the building; and measures, using an ohmmeter, a resistance of the wood item between two metal fasteners used to mount the sensor node to the wood item. The sensor node determines, based on the resistance, a moisture content of the wood item. The sensor node determines, based on the ambient temperature, the ambient humidity, and the moisture content, that conditions inside the wall of the building are conducive to pest activity and sends, using a communications interface, a notification that conditions are conducive to pest activity. The notification includes the ambient temperature, the ambient humidity, and the moisture content.

Using artificial intelligence (AI) to detect conditions conducive to pest activity

In some examples, a sensor node measures, using a thermometer, an ambient temperature of a location in which the wood item is located, measures, using a hygrometer, an ambient humidity of the location, measures, using an ohmmeter, a resistance of the wood item between two metal fasteners used to mount the sensor node to the wood item, determines, based on the resistance, a moisture content of the wood item, and determines, based on the ambient temperature, the ambient humidity, and the moisture content, whether conditions are conducive to pest activity. If conducive, the sensor node uses a microphone that is coupled to the wood item to capture audio data and determine whether the audio data indicates pest activity. If pest activity is detected, the sensor node sends a notification of pest activity, the notification includes the ambient temperature, the ambient humidity, the moisture content, and the audio data.

In some examples, a sensor node mounted to a wood item inside a wall of a building using two metal fasteners measures a resistance of the wood item and determines a difference between: the resistance of the wood item and a previous resistance of the wood item to determine a moisture content of the wood item. The sensor node measures, using a hygrometer, an ambient humidity inside the wall of the building. The sensor node sends a notification indicating a possible leak inside the wall of the building based at least in part on determining that: the moisture content of the wood item satisfies a moisture threshold, the ambient humidity inside the wall of the building satisfies an ambient humidity threshold, and the difference between the resistance of the wood item and the previous resistance satisfies a resistance threshold.

Using artificial intelligence (AI) to detect a leak within a wall of a building

In some examples, a sensor node is mounted, using two metal fasteners, to a wood item located indoors. The sensor node measures, using a thermometer, an ambient temperature of a location in which the wood item is located, measures, using a hygrometer, an ambient humidity of the location, measures, by an ohmmeter, a resistance of the wood item between the two metal fasteners, determines, based on the resistance, a moisture content of the wood item, and determines, based on the ambient temperature, the ambient humidity, and the moisture content, that conditions are conducive to pest activity. The sensor node captures audio data. using a microphone coupled to the wood item, determines that the audio data indicates pest activity, and sends a notification of pest activity. The notification includes the ambient temperature, the ambient humidity, the moisture content, and the audio data.

Using artificial intelligence (AI) to detect conditions conducive to pests

In some examples, a central hub receives, from a sensor node that is mounted to a wood item inside a wall of a building, a notification including sensor data. The sensor data includes: an ambient temperature inside the wall of the building, an ambient humidity inside the wall of the building, a resistance of the wood item between two metal fasteners used to fasten the sensor node to the wood item, and audio data captured by a microphone of the sensor node that is coupled to the wood item. The hub performs an analysis of the sensor data using an artificial intelligence algorithm. After determining, based on the analysis, a presence of a pest in the wood item, the hub sends a message indicating the presence of the pest to a computing device.

Using artificial intelligence (AI) to detect pest activity within a wall of a building

In some examples, a sensor node mounted to a wood item inside a wall of a building uses a thermometer to measure an ambient temperature and uses a hygrometer to measure an ambient humidity inside the wall of the building. The sensor node uses an ohmmeter to measure a resistance of the wood item between two metal fasteners used to mount the sensor node to the wood item. The sensor node determines a moisture content of the wood item based on the resistance. If the sensor node determines, based on the ambient temperature, the ambient humidity, and the moisture content, that conditions inside the wall of the building are conducive to pest activity, then the sensor node captures, using a microphone that is coupled to the wood item, audio data. The sensor node sends a notification of pest activity to a central bub for analysis using artificial intelligence.

In some example, a hub receives a notification of activity from a particular sensor node of a plurality of sensor nodes that are monitoring an area. The notification includes sensor data including: a difference in decibels between a first volume of a first filtered audio and a second volume of a second filtered audio and at least a portion of the second filtered audio. The hub performs an analysis of the sensor data using an artificial intelligence algorithm. The hub determines, based on the analysis, a presence of one or more tunneling activities and sends, by a communications interface of the hub, a message indicating the presence of the one or more tunneling activities to a computing device.

Using artificial intelligence (AI) to detect tunneling activity

In some examples, a sensor node is mounted to a post and includes a microphone that is coupled to the post. The sensor node records, at a first time, first audio data, using the microphone, filters the first audio data to create first filtered audio, records, at a second time that occurs after the first time, second audio data using the microphone, filters the second audio data to create second filtered audio, and determines a difference in decibels between a first volume of the first filtered audio and a second volume of the second filtered audio. If the sensor node determines that the difference in decibels is greater than a predetermined threshold, then the sensor node sends a notification of activity that includes the difference in decibels.

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Austin, TX, United States of America

Roger S Hollander