Real-time intelligent image processing for the internet of things

Chen, Mu-Yen; Wu, Hsien‐Tsai

doi:10.1007/s11554-021-01149-0

Cited by 6 publications

(1 citation statement)

References 11 publications

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“…Real-time optimization provides technological excellence, which helps to maximize the plant's contribution to business profit by providing best-in-class performance, optimizing plant operation, and increasing safety and reliability [36], RTO (Recovery Time Objective) contributed to optimizing key process operating variables by shifting the unit margin toward the optimum, and operation was better placed to challenge targets and operating conditions. Due to the increased application of image processing, the increase in speed on the part of hardware components has enabled the development of artificial intelligence, which has also included IoT, where one application is the real-time detection of anomalies in the car registration table in traffic [37].However, just because many specialized architectures and analytics models have been developed for this field does not mean that they are applicable in every case; in these cases, time optimization is frequently done manually by noting errors and their permissions and putting them in the code. Real-time image processing differs from other types of processing in that its analysis and accuracy must be realized quickly.…”

Section: Related Workmentioning

confidence: 99%

Applying Image Processing to Implement Optimization Approaches

2023

jjmie

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Real-time plays a pivotal role in diverse scientific application, and optimizing the measurement process is essential to enhance efficiency. This study proposes the implementation of geometric methods to optimize real-time measurements through image processing. By evaluating the available space for a mobile robot to move, indirect measurement of the object as an obstacle in real time is achieved. This technique effectively reduces data transmission speed, a critical parameter for real-time measurements, with the potential to lower costs by necessitating smaller and simpler technical specifications for equipment. In order to enhance measurement accuracy, stereo cameras capturing images from various angles are employed simultaneously. However, this may introduce complexities in calculations, such as parallax errors. To address this issue, filters and restoration methods are applied, such as Gauss, to correct noise and accurately measure space. The study presents real-time results for a static object using the dynamic system, which demonstrated an accuracy exceeding 99%. By utilizing the same image for different calculations, the system complexity is minimized, also measurement time is reduced. While current optimization focuses on 2D, there is potential for extension in 3D. The methodologies presented in this study primarily involve analytical approaches such as Distance-Based Optimization and Multicriteria Decision Analytics.The study's findings and proposed technology pave the way for exciting future research and practical implementations, potentially revolutionizing real-time measurements in numerous scientific and technology domains.

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Section: Related Workmentioning

confidence: 99%

Applying Image Processing to Implement Optimization Approaches

2023

jjmie

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Three-Dimensional Animation Generation and Image Enhancement Technology Based on Multi-Column Convolutional Neural Network Model

Cao¹,

Ten²,

et al. 2023

IEEE Access

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Edge intelligence-assisted animation design with large models: a survey

Zhu,

Hu,

Khezri

et al. 2024

J Cloud Comp

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The integration of edge intelligence (EI) in animation design, particularly when dealing with large models, represents a significant advancement in the field of computer graphics and animation. This survey aims to provide a comprehensive overview of the current state and future prospects of EI-assisted animation design, focusing on the challenges and opportunities presented by large model implementations. Edge intelligence, characterized by its decentralized processing and real-time data analysis capabilities, offers a transformative approach to handling the computational and data-intensive demands of modern animation. This paper explores various aspects of EI in animation and then delves into the specifics of large models in animation, examining their evolution, current trends, and the inherent challenges in their implementation. Finally, the paper addresses the challenges and solutions in integrating EI with large models in animation, proposing future research directions. This survey serves as a valuable resource for researchers, animators, and technologists, offering insights into the potential of EI in revolutionizing animation design and opening new avenues for creative and efficient animation production.

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Real-time intelligent image processing for the internet of things

Cited by 6 publications

References 11 publications

Applying Image Processing to Implement Optimization Approaches

Applying Image Processing to Implement Optimization Approaches

Three-Dimensional Animation Generation and Image Enhancement Technology Based on Multi-Column Convolutional Neural Network Model

Edge intelligence-assisted animation design with large models: a survey

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