The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 06, 2018

Filed:

Jul. 20, 2016
Applicant:

Eturi Corp., San Diego, CA (US);

Inventors:

Edward Hunter, San Diego, CA (US);

Negeen Moussavian, San Diego, CA (US);

Amir Moussavian, San Diego, CA (US);

Mark Lewis, San Diego, CA (US);

Assignee:

ETURI CORP., San Diego, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04L 12/24 (2006.01); H04L 29/08 (2006.01); H04L 12/26 (2006.01); G06F 17/30 (2006.01); H04L 12/851 (2013.01); H04L 12/825 (2013.01); H04W 4/00 (2009.01); H04W 4/20 (2009.01);
U.S. Cl.
CPC ...
H04L 41/5019 (2013.01); G06F 17/30899 (2013.01); H04L 41/5009 (2013.01); H04L 43/08 (2013.01); H04L 47/2425 (2013.01); H04L 47/25 (2013.01); H04L 67/16 (2013.01); H04L 67/22 (2013.01); H04W 4/001 (2013.01); H04W 4/206 (2013.01);
Abstract

Throttles electronic devices based on compliance with rules for electronic communications such as emails, texts, or postings on social media sites. Rules may for example prohibit certain topics, language, or behaviors such as online bullying. If system detects a violation of the electronic communications rules, it may block access or reduce performance on one or more electronic devices as a consequence. In some cases, devices or selected apps or services may continue to function, but at a reduced level. Conversely the system may provide rewards for conforming with the rules. Throttling of devices may also depend on other factors, such as homework completion, test results, grades, and environmental conditions. Machine learning techniques may be applied to determine when electronic communications may violate the rules. For example, probabilistic topic models may be applied to determine the topics of electronic communications, and to assess whether these topics violate the rules.


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