Samsara Inc.

Cisco Technology, Inc.

Samsara Networks Inc.

Justin Joel Delegard

Brian Tuan

Jesse Chen

Robert Tristan Shanks

John Charles Bicket

Patrick Douglas Verkaik

Bodecker John DellaMaria

Saleh ElHattab

Sylvie Lee

Jennifer Leung

Kavya U Joshi

Mathew Chasan Calmer

Timothy John Passaro

Dylan Jason Koenig

Jignesh Devji Patel

Justin Pan

Selahattin Daghan Altas

Joseph Morgan Aronow

Ingo Gerhard Wiegand

Jason Frederic Symons

Sabrina Quinn Shemet

Saumya Jain

James Michael Roewe

Sean Kyungmok Bae

Angel Manalastas Lim

Maxwell Anton Dergosits

Elias Ray Dykaar

Cassandra Lee Rommel

Meelap Shah

Harrison Riley Davis

Ryan Milligan

Dan Aguayo

James Michael Rowson

Clifford Arthur Frey

James Duffield

Adam Weis

Kong Kee Poon

Christian Peter Almer

Grant Allen Marvin

Muhammad Ali Akhtar

Sharan Srinivasan

Matthew Lee Basham

Margaret Irene Finch

Bruce Kellerman

Vincent Shieh

Derrek Harrison

Ava O'Neill

David Liang

Casey Takahashi

Kirti Varun Munjeti

Frances Peijin Guo

Tina Quach

Siddhartha Datta Roy

Marvin Arroz

Mitch Lin

Naveen Chinya Krishnamurthy

Kevin R Lloyd

Nathaniel Brahms

Narendran Rajan

Daghan Altas

Ryan Young

Kiren Sekar

Kavya Joshi

Joel Feinstein

Jacob Corr Valentic

Arthur Po-Hsiang Huang

Ryan Reading

Matthew Chasan

Abhinav Acharya

Example embodiments described herein therefore relate to an event detection system that comprises a plurality of sensor devices, to perform operations that include: generating sensor data at the plurality of sensor devices; accessing the sensor data generated by the plurality of sensor devices; detecting an event, or precursor to an event, based on the sensor data, wherein the detected event corresponds to an event category; accessing an object model associated with the event type in response to detecting the event, wherein the object model defines a procedure to be applied by the event detection system to the sensor data; and streaming at least a portion of a plurality of data streams generated by the plurality of sensor devices to a server system based on the procedure, wherein the server system may perform further analysis or visualization based on the portion of the plurality of data streams.

Event detection system

Disclosed are systems, methods, and non-transitory computer-readable media for a device arrangement to derive unknown portions of a communication data scheme. A proxy node is established in a communication path between two nodes configured to transmit communications according to a communication bus standard. The communication data included in the communications transmitted between the nodes conforms to a communication data scheme. The proxy node logs communications transmitted between the nodes via the communication path, resulting in a communication log. The communication log can then be used to derive unknown portion of the communication data scheme, such as commands for requesting specified data types and the data format for transmitting data of specified data types.

Device arrangement for deriving a communication data scheme

An improved system and method of selectively transmitting asset data from one or more sensors associated with the vehicle to a backend server, which is configured to analyze the asset data and, if necessary for further analysis of the asset data (e.g., to determine whether a safety event has occurred) and/or to provide actionable data for review by a safety analyst, requests further asset data from a vehicle device.

Dynamic delivery of vehicle event data

A selective recording system to perform operations that include: accessing, at a system gateway, a data stream generated by a sensor device; determining a property of a portion of the data stream at the system gateway, the property of the portion of the data stream comprising a value; determining that the value of the property of the portion of the data stream transgresses a threshold value; and recording the portion of the data stream within a database of the system gateway in response to the determining that the property of the portion of the data stream transgresses the threshold value.

Selective recording of sensor data within a system gateway

Example embodiments described herein therefore relate to an object-model based event detection system that comprises a plurality of sensor devices, to perform operations that include: generating sensor data at the plurality of sensor devices; accessing the sensor data generated by the plurality of sensor devices; detecting an event, or precursor to an event, based on the sensor data, wherein the detected event corresponds to an event category; accessing an object model associated with the event type in response to detecting the event, wherein the object model defines a procedure to be applied by the event detection system to the sensor data; and streaming at least a portion of a plurality of data streams generated by the plurality of sensor devices to a server system based on the procedure, wherein the server system may perform further analysis or visualization based on the portion of the plurality of data streams.

Machine-learned model based event detection

Various implementations disclosed herein provide a mechanism for determining that a configuration status of a compliant device is too far out-of-date, and subsequently bridging the configuration status of the compliant device to the up-to-date configuration data and instructions in response. In various implementations, determination of the configuration status of the compliant device is possible using a single request from the compliant device, which in turn reduces the amount of network traffic and utilization of network resources needed to update the compliant device with the up-to-date configuration data and instructions.

Bridging configuration changes for compliant devices

A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

Dash cam with artificial intelligence safety event detection

An Internet of Things (IoT) or vehicle dash cam may store both a high-resolution and low-resolution video stream on a device. The video streams are selectively accessible by remote devices. Because of the relatively smaller storage requirements of low-resolution video files, retaining of additional video data on the vehicle device (beyond what would be possible with only high-resolution video) is possible. The user may be provided an option to adjust the amount of low-resolution and high-resolution video to store on the device. A combined media file may be generated by a device to include time-synced high-resolution video, low-resolution video, and/or metadata for a particular time period.

Dual-stream video management

Multiple cameras within a vehicle, such as placed at multiple locations inside and/or outside a bus or semi-truck and trailer, may be chained together to provide a consolidated video stream that may be recorded and/or transmitted wirelessly to a cloud storage device. Rather that each of the cameras independently recording and/or streaming video content, each camera may be configured to deserialize an input video to identify video streams from separate cameras (e.g., such as based on associate virtual channel identifiers) and reserialize its own video stream with the other video streams in the received input. The serialized video stream is then transmitted to a next camera in the daisy chain and/or a video storage device.

Daisy chaining dash cams

Object-model based event detection system

Various implementations disclosed herein include systems, methods and apparatuses of a first device, that obtain contact point information of a second device associated with the first device, as a peer device in a private network, where the contact point information of the second device includes one or more peer uplink identifiers and each respective peer uplink identifier corresponds to a respective peer device uplink of the second device. The systems, methods and apparatuses establish a first private network data tunnel from a first uplink of the first device to the second device, using the contact point information of the second device, and a first uplink identifier associated with the first uplink, and establish a second private network data tunnel from a second uplink of the first device to the second device, using the contact point information of the second device, and a second uplink identifier associated with the second uplink.

Establishing a private network using multi-uplink capable network devices

Growing community of inventors

San Francisco, CA, United States of America

Justin Joel Delegard