Obstacle detection using AI
MRS.K.Sangeetha
, Dhanvarshini.R , Divya.N , Biyyapu Vaishmitha Reddy
autonomous obstacle detection, onboard of vision, road ,traditional computer vision technique, AI-based vision.
People while driving encounter a variety of issues in life, with the detection of impediments while moving being one of the most significant issues. Our study focuses on detecting obstacles to minimize accidents on the road and other difficulties for driving people. The visible environment must be changed into an auditory one that can alert individuals about barriers in order to assist them. This research proposes a deep learning system for real-time obstacle tracking and identification. One of the key uses of deep learning is obstacle detection. A pre-trained CNN (Convolution Neural Network) model, transfer learning, or starting from scratch by inputting n number of datasets to identify the obstacle with higher number of epochs to raise the accuracy of the output can all be used to do this. More photos are used to train the model to spot the obstruction. An obstacle such as Person, Animal, Vehicle monitoring, and etc. It for is used to above deep learning processing along with AI, The implementation of on-board sensors for road cars has been extensively researched for this purpose, and developments in AI and sensory technologies have inspired students to get degrees in research and development in the automotive industry. Research and development have, however, been limited in the domain of road obstacle verification. This is the first thorough analysis of onboard barrier detection techniques for road applications, to the best of our knowledge. Due to the widespread adoption in the region, vision sensors receive additional consideration in this paper's review of currently in use detectors.
Volume 11
Issue 2,
February-2024
Pages : 575-579
Paper Reg. ID: TIJER_151031
Published Paper Id: TIJERB001091
Downloads: 000298
Research Area: Science and Technology
Country: Thiruvallur, Chennai, Tamilnadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
