Study and Implementation of a Mobile Robot for Object Detection Based on VLC Technology

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DC Field	Value	Language
dc.contributor.author	REZAIGUIA, Oussama	-
dc.date.accessioned	2024-12-09T08:41:53Z	-
dc.date.available	2024-12-09T08:41:53Z	-
dc.date.issued	2024-06	-
dc.identifier.uri	http://dspace.univ-guelma.dz/jspui/handle/123456789/16531	-
dc.description.abstract	In this work, we studied and addressed artificial intelligence for robots. We used advanced algorithms based on deep learning and neural networks with the Python language and its libraries to train our model for fire detection. We used a Raspberry Pi as a small-embedded processor in the robot for operation, and Arduino as a microcontroller unit to establish communication with the robot through visible light communication technology, enabling us to send detection results and control the robot movement	en_US
dc.language.iso	en	en_US
dc.publisher	universitie 8 mai 1945 guelma	en_US
dc.subject	Artificial Intelligence, Robot, Algorithms, Deep learning, Neural Network, Fire Detection, Processor, Microcontroller, Visible Light Communication.	en_US
dc.title	Study and Implementation of a Mobile Robot for Object Detection Based on VLC Technology	en_US
dc.type	Working Paper	en_US
Appears in Collections:	Master

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