Traffic Sign Recognition and Voice Alert System Using CNN for Intelligent Assistance
Road signs are crucial for a safe and efficient traffic flow. Negligence in observing and misinterpreting traffic signboards is a key contributor to traffic accidents. The suggested technology aids in the recognition of traffic signs and provides the driver with a voice alarm via the speaker so that prompt decisions can be made. The system uses a Convolutional Neural Network (CNN) for traffic sign recognition and classification in addition to OpenCV for picture processing. To increase the accuracy of recognition, a set of traffic sign classes are established and trained. A voice alarm is produced and sent through a speaker to alert the driver when a traffic sign is detected. To help the driver keep informed of the regulations to follow along the road, the device also has a feature that notifies them of any nearby traffic signs. By reducing human error in traffic sign reading, this technology aims to improve the safety of drivers, passengers, and pedestrians.
Authors
- M. Farooq (ORCID: https://orcid.org/0000-0002-9243-744X)
- Moien AB Khan (ORCID: https://orcid.org/0000-0003-4970-4618)
- Zohraan Mohammed Abdul Moqsith
- Mohammed Abdul Bari
Institutions
- Dean College (US)
- English and Foreign Languages University (IN)
Publication Details
- Journal
- International jounal of information technology and computer engineering.
- Published
- 2025-06-11
- DOI
- https://doi.org/10.62647/ijitce2025v13i2spp59-66
- Primary Topic
- Vehicle License Plate Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00