# US 11,451,868 B2 · Intelligent routing of notifications related to media programming > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,451,868 B2 - Document ID: US11451868B2 - Status: Granted - Kind: B2 - Application number: 16/985,473 - Filed: 2020-08-05 - Published: 2021-01-28 - Granted: 2022-09-20 - Earliest claimed: 2018-11-14 - Assignees: QUALCOMM Incorporated - Applicants: QUALCOMM Incorporated - Inventors: Ravi Teja Mandavilli; Prathviraj Shetty; Sravan Kumar Reddy Achamola; Kiran Koona; Vitesh Kempanna Nataraj; Pavan Kumar Patted; Tejasree Depa; Sidhartha Kumar Kar; Chaitanya Panuganti; Manoj Kannan Venugopal; Naman Pandey; Anshul Gupta; Venkata Ramana Reddy Yaddula; Lakshmana Rao Venigalla; Venkata SubbaRao Annam - Web page: https://patentgrep.com/patent/US11451868B2 ## CPC - H04N 21/44218: {Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV programme (methods or arrangements for recognising human body or animal bodies or body parts G06V40/10; methods or arrangements for acquiring or recognising human faces, facial parts, facial sketches, facial expressions G06V40/16; methods or arrangements for recognising movements or behaviour G06V40/20; arrangements for identifying users in broadcast systems H04H60/45)} - G06V 40/172: {Classification, e.g. identification} - H04N 21/42203: {sound input device, e.g. microphone} - H04N 21/4223: Cameras (H04N23/00 takes precedence) - H04N 21/44226: {on social networks} - H04N 21/454: Content {or additional data} filtering, e.g. blocking advertisements - H04N 21/4666: {using neural networks, e.g. processing the feedback provided by the user} - H04N 21/4826: {using recommendation lists, e.g. of programmes or channels sorted out according to their score} - H04N 21/4882: {for displaying messages, e.g. warnings, reminders (arrangements for providing short real-time information to substation in data switching networks H04L12/1895)} - G10L 17/00: Speaker identification or verification techniques - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING ## Abstract This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media for intelligent routing of notifications related to media programming. In one aspect, a smart television (TV) can be implemented to track a user's TV watching behavior, and anticipate programming based on that behavior. In some other aspects, the smart TV can be implemented to detect a user's presence, and based on that detection, can automatically change the TV channel to media programming analyzed to be desirable to the user. In some further aspects, the smart TV can be implemented to transmit notification instructions to electronic devices within a network in an attempt to alert the user to upcoming media programming. Additionally, the smart TV can be implemented to transmit detection instructions to the electronic devices within the network, whereby the electronic devices attempt to detect a user's presence through voice or facial recognition. ## Claims ### Claim 1 A method for presenting media programming on an electronic device, comprising: obtaining viewing data, wherein the viewing data includes at least one of a historical time and a historical date associated with at least one media program viewed on the electronic device or a second electronic device in communication with the electronic device; determining, based on the obtained viewing data, a duration that the at least one media program was viewed on the electronic device or the second electronic device; obtaining at least one of a current time and a current date; employing a neural network model to determine, based on the duration and at least one of the current time and the current date, a probability of the at least one media program being viewed on the electronic device, wherein employing the neural network model includes comparing the duration to a threshold time duration; and presenting, based on the probability exceeding a threshold and the duration being greater than the threshold time duration, the media program on the electronic device. ### Claim 2 (depends on 1) The method of claim 1, wherein the media program is presented in a favorite channel list on the electronic device. ### Claim 3 (depends on 1) The method of claim 1, further comprising adjusting at least one of a volume or a brightness of the electronic device, wherein the adjusting is based on at least one of the historical time and the historical date. ### Claim 4 (depends on 1) The method of claim 1, further comprising: detecting a presence of a user; and accessing user profile data associated with the user, wherein the user profile includes the viewing data. ### Claim 5 (depends on 4) The method of claim 4, wherein detecting the presence of the user includes employing one or more of a camera, a microphone, or a fingerprint sensor associated with the electronic device or the second electronic device. ### Claim 6 (depends on 4) The method of claim 4, further comprising restricting the presenting of the media program based on the user profile data. ### Claim 7 (depends on 6) The method of claim 6, wherein upon the restricting the presenting of the media program, further comprising switching to another media program for presentation. ### Claim 8 (depends on 4) The method of claim 4, further comprising adjusting at least one of a volume or a brightness of the electronic device, wherein the adjusting is based on the user profile data. ### Claim 9 An electronic device capable of presenting media programming, comprising: a network interface; a non-transitory computer-readable medium; and a processor in communication with the network interface, and the non-transitory computer-readable medium, and capable of executing processor-executable program code stored in the non-transitory computer-readable medium, to cause the electronic device to: obtain viewing data, wherein the viewing data includes at least one of a historical time and a historical date associated with at least one media program viewed on the electronic device or a second electronic device in communication with the electronic device; determine, based on the obtained viewing data, a duration that the at least one media program was viewed on the electronic device or the second electronic device; obtain at least one of a current time and a current date; determine, based on the duration and on at least one of the current time and the current date, a probability of the at least one media program being viewed on the electronic device by employing a neural network model, wherein employing the neural network model includes comparing the duration to a threshold time duration; and present, based on the probability exceeding a threshold and the duration being greater than the threshold time duration, the media program on the electronic device. ### Claim 10 (depends on 9) The electronic device of claim 9, wherein the media program is presented in a favorite channel list on the electronic device. ### Claim 11 (depends on 9) The electronic device of claim 9, further comprising adjusting at least one of a volume or a brightness of the electronic device, wherein the adjusting is based on at least one of the historical time and the historical date. ### Claim 12 (depends on 9) The electronic device of claim 9, further comprising: detecting a presence of a user; and accessing user profile data associated with the user, wherein the user profile includes the viewing data. ### Claim 13 (depends on 12) The electronic device of claim 12, wherein detecting the presence of the user includes employing one or more of a camera, a microphone, or a fingerprint sensor associated with the electronic device or the second electronic device. ### Claim 14 (depends on 12) The electronic device of claim 12, further comprising restricting the presenting of the media program based on the user profile data. ### Claim 15 (depends on 14) The electronic device of claim 14, wherein upon the restricting the presenting of the media program, further comprising switching to another media program for presentation. ### Claim 16 (depends on 12) The electronic device of claim 12, further comprising adjusting at least one of a volume or a brightness of the electronic device, wherein the adjusting is based on the user profile data. ### Claim 17 A non-transitory computer-readable medium comprising processor-executable program code configured to cause a processor of an electronic device to: obtain viewing data, wherein the viewing data includes at least one of a historical time and a historical date associated with at least one media program viewed on the electronic device or a second electronic device in communication with the electronic device; determine, based on the obtained viewing data, a duration that the at least one media program was viewed on the electronic device or the second electronic device; obtain at least one of a current time and a current date; employ a neural network model to determine, based on the duration and at least one of the current time and the current date, a probability of the at least one media program being viewed on the electronic device, including comparing the duration to a threshold time duration; and present, based on the probability exceeding a threshold and the duration being greater than the threshold time duration, the media program on the electronic device. ### Claim 18 (depends on 13) The non-transitory computer-readable medium of claim 13, wherein the media program is presented in a favorite channel list on the electronic device. ### Claim 19 (depends on 17) The non-transitory computer-readable medium of claim 17, wherein the processor is further capable of executing processor-executable program code to: adjust at least one of a volume or a brightness of the electronic device, wherein the adjusting is based on at least one of the historical time and the historical date. ### Claim 20 (depends on 17) The non-transitory computer-readable medium of claim 17, wherein the processor is further capable of executing processor-executable program code to: detect a presence of a user; and access user profile data associated with the user, wherein the user profile includes the viewing data. ### Claim 21 (depends on 20) The non-transitory computer-readable medium of claim 20, wherein detecting the presence of the user includes employing one or more of a camera, a microphone, or a fingerprint sensor associated with the electronic device or the second electronic device. ### Claim 22 (depends on 20) The non-transitory computer-readable medium of claim 20, wherein the processor is further capable of executing processor-executable program code to: restrict the presenting of the media program based on the user profile data. ### Claim 23 (depends on 22) The non-transitory computer-readable medium of claim 22, wherein upon the restricting the presenting of the media program, the processor is further capable of executing processor-executable program code to: switch to another media program for presentation. ### Claim 24 (depends on 20) The non-transitory computer-readable medium of claim 20, wherein the processor is further capable of executing processor-executable program code to: adjust at least one of a volume or a brightness of the electronic device, wherein the adjusting is based on the user profile data.