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

Jia-Shing Sheu; Chen-Yin Han

doi:10.46604/aiti.2020.4284

Authors

Jia-Shing Sheu Department of Computer Science, National Taipei University of Education, Taipei, Taiwan
Chen-Yin Han Department of Computer Science, National Taipei University of Education, Taipei, Taiwan

DOI:

https://doi.org/10.46604/aiti.2020.4284

Keywords:

TensorFlow, computer vision, neural network, scene recognition, cloud computing

Abstract

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.

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