Antenna Mount Location Detection via Image Processing

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Solution Overview

Problem

The current methods for selecting antenna mount locations are time-consuming, labor-intensive, and prone to errors, leading to sub-optimal service deployment and increased costs due to miscommunication between technicians and engineers, with potential overlooking of optimal locations.

Innovation Solution

A system that uses image processing algorithms, including machine learning and deep learning, to identify and select suitable locations for antenna mounts by analyzing images from various sources, comparing characteristics and attributes to determine the best placement for communication network resources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual site survey and image analysis methods are used to identify antenna mount locations, then the selection process is performed with human expertise, but the process becomes time-consuming, labor-intensive, and prone to errors

Engineering Contradiction:

Improveaccuracy of location selectionVSAvoidtime for site survey and location identification

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical inspection methods with automated image processing algorithms and machine learning models. The system automatically analyzes images to identify antenna mount locations, eliminating the need for technicians to manually examine each potential site, thus reducing time while maintaining or improving accuracy through consistent algorithmic evaluation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the image processing algorithm to autonomously identify and evaluate potential antenna mount locations without human intervention. The machine learning model automatically processes images, detects objects, and ranks locations based on suitability criteria, making the system self-sufficient in performing the location selection task

Inventive Principle:

Principle #25Self-service

2Loss of information

If multiple technicians conduct site surveys and prepare reports, then comprehensive data is collected, but the process increases labor costs and introduces miscommunication errors between technicians and engineers

Engineering Contradiction:

Improvecompleteness of location dataVSAvoidcomplexity of coordination between technicians and engineers

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent uses image capture equipment to create digital copies of potential antenna mount locations. These image copies are then processed by algorithms that extract and analyze relevant features, replacing the need for multiple technicians to physically visit and document each site. The digital images serve as faithful reproductions that can be analyzed repeatedly without additional field visits

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The image processing system acts as an intermediary between data collection and decision-making. Instead of technicians directly communicating findings to engineers, the automated system processes images and generates standardized location assessments, eliminating miscommunication and creating a consistent intermediate representation of all candidate locations

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If traditional manual methods are used to evaluate candidate locations, then the process is simple to implement, but optimal locations may be overlooked and service deployment becomes sub-optimal

Engineering Contradiction:

Improveefficiency of service deploymentVSAvoidaccuracy of location evaluation

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies partial action by focusing the image processing algorithm on specific visual features and characteristics that are most indicative of suitable antenna mount locations. Rather than requiring exhaustive manual evaluation of every aspect of each site, the system selectively analyzes key indicators such as object type, mounting surface availability, and spatial characteristics, achieving high productivity while maintaining sufficient evaluation accuracy

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11228920B2Multi-stage object detection and categorization of antenna mount locations

Publication Date: 2022.01.18 AT&T INTELLECTUAL PROPERTY I L P

AI summary

Aspects of the disclosure include determining that a first instance of a first object is present in a first image in accordance with an execution of a first image processing algorithm, generating a first bounding region that at least partially surrounds the first instance of the first object in the first image, determining that the first instance of the first object in the first image has a first attribute in accordance with an execution of a second image processing algorithm, wherein the second image processing algorithm is operative on the first image in accordance with the first bounding region, and selecting the first instance of the first object and/or a second instance of the first object to receive a deployment of a network resource in accordance with the determining that the first instance of the first object in the first image has the first attribute. Other aspects are disclosed.