Invention Grant
- Patent Title: Visual representation of signal strength using machine learning models
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Application No.: US15079502Application Date: 2016-03-24
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Publication No.: US09949135B2Publication Date: 2018-04-17
- Inventor: Edward L. Chatelain , Jeremy A. Greenberger , Nicholas R. Sandonato
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business machines Corporation
- Current Assignee: International Business machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Alexander G. Jochym
- Main IPC: H04W16/18
- IPC: H04W16/18 ; H04L12/24 ; H04L12/26 ; H04B17/318 ; H04B17/373 ; H04B17/391 ; H04B17/23 ; H04B17/27

Abstract:
Information about a signal device is received at a first location in a first physical environment. The signal device broadcasts a signal to a computing device. A first indication is received from the computing device. The first indication includes a first strength of signal of the signal device received by the computing device. Whether the first strength of signal is above a threshold is determined. A second location is determined. The second location is where the computing device is located when the first strength of signal is above the threshold. The second location is within the first physical environment. A first visual representation of the first physical environment is displayed. The first visual representation includes one or more of the following: the signal device at the first location, at least one physical item found in the physical environment, a broadcasting power of the signal device, and the second location.
Public/Granted literature
- US20170280332A1 VISUAL REPRESENTATION OF SIGNAL STRENGTH USING MACHINE LEARNING MODELS Public/Granted day:2017-09-28
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