Intelligent Imaging Apparatus with Adaptive Power Management and Space Boundary Detection

Publication ID: 24-11857155_0010_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Intelligent Imaging Apparatus with Adaptive Power Management and Space Boundary Detection,” Published Technical Disclosure No. 24-11857155_0010_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857155_0010_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,155.

Summary of the Inventive Concept

A next-generation imaging apparatus that leverages machine learning and modular sensor arrays to dynamically adjust imaging parameters, optimize power consumption, and generate accurate 3D maps of spaces with changing boundaries.

Background and Problem Solved

The original patent disclosed an imaging apparatus with power-saving control based on object detection. However, this approach has limitations in adapting to complex and dynamic space boundaries. The new inventive concept addresses this problem by integrating machine learning, modular sensor arrays, and advanced power management to provide a more efficient, accurate, and adaptive imaging solution.

Detailed Description of the Inventive Concept

The new inventive concept comprises an imaging apparatus with a neural network trained to predict space boundaries, which integrates with a modular sensor array to dynamically adjust imaging parameters. The apparatus can detect changes in space boundaries using machine learning models and adjust power consumption accordingly. Additionally, the imaging apparatus can generate a 3D map of a space using imaging data, where the method uses machine learning to predict space boundaries and adjust the 3D map accordingly. The wearable imaging device features a flexible, shape-memory alloy-based imaging module that conforms to changing space boundaries and optimizes imaging parameters.

Novelty and Inventive Step

The new claims introduce a paradigm shift in imaging technology by incorporating machine learning, modular sensor arrays, and advanced power management, which enables the imaging apparatus to adapt to complex and dynamic space boundaries in real-time. This is a significant departure from the original patent's object detection-based approach, offering a more efficient, accurate, and adaptive imaging solution.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning models, such as computer vision or deep learning, to predict space boundaries. Variations of the modular sensor array could include different sensor types, such as lidar or radar, to provide additional data for space boundary detection. Furthermore, the wearable imaging device could be integrated with other wearable devices, such as smart glasses or smartwatches, to provide a more comprehensive imaging solution.

Potential Commercial Applications and Market

The new inventive concept has significant commercial potential in various industries, including healthcare, robotics, autonomous vehicles, and smart homes. The ability to adapt to complex and dynamic space boundaries enables the imaging apparatus to operate efficiently in a wide range of environments, making it an attractive solution for applications such as medical imaging, object recognition, and navigation.

CPC Classifications

SectionClassGroup
A A61 A61B1/00036
A A61 A61B1/00006
A A61 A61B1/00009
A A61 A61B1/0655
A A61 A61B1/0661
G G02 G02B7/36
G G02 G02B23/2484
G G03 G03B13/36
H H04 H04N23/71
H H04 H04N23/74
A A61 A61B1/00016
A A61 A61B1/00032
H H04 H04N23/555

Field of Art

Medical and scientific imaging systems, with expertise in optical imaging, sensor technologies, power management, and computational image processing across medical, industrial, and wearable device contexts

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with advanced engineering degrees in electrical/mechanical engineering, proficient in machine learning, sensor integration, computational imaging, and adaptive electronics design with 3-5 years of industry experience

Obviousness Rationale

A PHOSITA would recognize that the published technical disclosure represents a predictable extension of the source patent's core imaging apparatus concepts by applying machine learning techniques to enhance space boundary detection and power management. The fundamental technological problem of adaptive imaging in constrained spaces remains consistent, with the PTD offering a more sophisticated computational approach to solving the same core challenge. The neural network and modular sensor array represent incremental improvements that would be obvious to implement using standard machine learning and sensor integration techniques.

Obvious Combinations & Variations

Source Patent Element
Processor configured to determine imaging device position relative to surrounding objects
PTD Variation
Neural network trained to predict space boundaries using machine learning models
Obviousness Reasoning
Applying machine learning to object detection is a known technique in sensor systems, representing a predictable technological evolution with expected improvements in accuracy and adaptability
Source Patent Element
Power-saving control mechanisms for imaging apparatus
PTD Variation
Dynamic power consumption adjustment based on detected space boundaries
Obviousness Reasoning
Adaptive power management is a standard design approach in electronic systems, with machine learning providing a more sophisticated method of implementing known power optimization strategies
Source Patent Element
Imaging device insertable into confined spaces
PTD Variation
Wearable imaging device with shape-memory alloy module conforming to space boundaries
Obviousness Reasoning
Flexible sensor design is a predictable solution for improving device adaptability in constrained environments, representing a straightforward engineering design choice
Source Patent Element
Processor determining spatial relationships of imaging device
PTD Variation
3D map generation using machine learning to predict and adjust space boundaries
Obviousness Reasoning
Computational mapping of spatial environments is a well-established technique in imaging and robotics, with machine learning providing an incremental improvement in accuracy and adaptability
Source Patent Element
Light source and imaging device with configurable parameters
PTD Variation
Modular sensor array with individual modules dynamically adjusting imaging parameters
Obviousness Reasoning
Modular sensor design represents a known approach to improving system flexibility, with individual module configuration being a predictable engineering solution
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857155 and the published technical disclosure, a person having ordinary skill in the art would find the claimed variations obvious, as the PTD represents a predictable application of machine learning and computational techniques to the fundamental imaging apparatus concepts disclosed in the source patent, thereby rendering subsequent claims involving similar technological approaches anticipated and non-patentable.

Original Patent Information

Patent NumberUS 11,857,155
TitleImaging apparatus, method of operating imaging apparatus, and recording medium
Assignee(s)OLYMPUS CORPORATION