Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area

This study developed scene recognition and cloud computing technology for real-time environmental image-based regional planning using artificial intelligence. TensorFlow object detection functions were used for artificial intelligence technology. First, an image from the environment is transmitted...

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Main Authors: Jia-Shing Sheu, Chen-Yin Han
Format: Article
Language:English
Published: Taiwan Association of Engineering and Technology Innovation 2020-01-01
Series:Advances in Technology Innovation
Subjects:
Online Access:http://ojs.imeti.org/index.php/AITI/article/view/4284
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spelling doaj-2a897fe28acd4c91b842b3a9a219af022020-11-25T02:09:58ZengTaiwan Association of Engineering and Technology InnovationAdvances in Technology Innovation2415-04362518-29942020-01-0151Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable AreaJia-Shing Sheu0Chen-Yin Han1Department of Computer Science, National Taipei University of Education, Taipei, TaiwanDepartment of Computer Science, National Taipei University of Education, Taipei, Taiwan This study developed scene recognition and cloud computing technology for real-time environmental image-based regional planning using artificial intelligence. TensorFlow object detection functions were used for artificial intelligence technology. First, an image from the environment is transmitted to a cloud server for cloud computing, and all objects in the image are marked using a bounding box method. Obstacle detection is performed using object detection, and the associated technique algorithm is used to mark walkable areas and relative coordinates. The results of this study provide a machine vision application combined with cloud computing and artificial intelligence scene recognition that can be used to complete walking space activities planned by a cleaning robot or unmanned vehicle through real-time utilization of images from the environment. http://ojs.imeti.org/index.php/AITI/article/view/4284TensorFlowcomputer visionneural networkscene recognitioncloud computing
collection DOAJ
language English
format Article
sources DOAJ
author Jia-Shing Sheu
Chen-Yin Han
spellingShingle Jia-Shing Sheu
Chen-Yin Han
Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area
Advances in Technology Innovation
TensorFlow
computer vision
neural network
scene recognition
cloud computing
author_facet Jia-Shing Sheu
Chen-Yin Han
author_sort Jia-Shing Sheu
title Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area
title_short Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area
title_full Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area
title_fullStr Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area
title_full_unstemmed Combining Cloud Computing and Artificial Intelligence Scene Recognition in Real-time Environment Image Planning Walkable Area
title_sort combining cloud computing and artificial intelligence scene recognition in real-time environment image planning walkable area
publisher Taiwan Association of Engineering and Technology Innovation
series Advances in Technology Innovation
issn 2415-0436
2518-2994
publishDate 2020-01-01
description This study developed scene recognition and cloud computing technology for real-time environmental image-based regional planning using artificial intelligence. TensorFlow object detection functions were used for artificial intelligence technology. First, an image from the environment is transmitted to a cloud server for cloud computing, and all objects in the image are marked using a bounding box method. Obstacle detection is performed using object detection, and the associated technique algorithm is used to mark walkable areas and relative coordinates. The results of this study provide a machine vision application combined with cloud computing and artificial intelligence scene recognition that can be used to complete walking space activities planned by a cleaning robot or unmanned vehicle through real-time utilization of images from the environment.
topic TensorFlow
computer vision
neural network
scene recognition
cloud computing
url http://ojs.imeti.org/index.php/AITI/article/view/4284
work_keys_str_mv AT jiashingsheu combiningcloudcomputingandartificialintelligencescenerecognitioninrealtimeenvironmentimageplanningwalkablearea
AT chenyinhan combiningcloudcomputingandartificialintelligencescenerecognitioninrealtimeenvironmentimageplanningwalkablearea
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