Arduino based wireless digital notification board
Publication details: Ghaziabad MAT Journals 2024Edition: Vol.1(2), May-AugDescription: 10-15pSubject(s): Online resources: In: Journal of data engineering and knowledge discoverySummary: These days, notice boards are crucial in institutions, organizations, and public spaces like train stations, transportation hubs, and health centres. However, using the paper notes piled on a notice board could be laborious and expensive, significantly wasting time, paper, and labour. The receiver uses an inexpensive Arduino Uno microcontroller to receive and show messages on an LED display. Rather than writing notices by hand on a notice board, the authorized user can talk, and their voice message is transmitted. Bluetooth device is shown on the LED panel. In this project, we are utilizing the most adaptable and effective speech recognition method available: the Hidden Markov Model (HMM). After recognizing the speech, it is sampled and processed to identify it as verbalized text. The project consists of a 32-bit ARM-based microcontroller LPC2148, a GSM SIM900 module, an LED, a motor and an Android application for user interface with the hardware to facilitate Bluetooth and Wi-Fi connection between Android-based PDAs and remote wireless display boards.| Item type | Current library | Status | Barcode | |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2025-0322 |
These days, notice boards are crucial in institutions, organizations, and public spaces like train stations, transportation hubs, and health centres. However, using the paper notes piled on a notice board could be laborious and expensive, significantly wasting time, paper, and labour. The receiver uses an inexpensive Arduino Uno microcontroller to receive and show messages on an LED display. Rather than writing notices by hand on a notice board, the authorized user can talk, and their voice message is transmitted. Bluetooth device is shown on the LED panel. In this project, we are utilizing the most adaptable and effective speech recognition method available: the Hidden Markov Model (HMM). After recognizing the speech, it is sampled and processed to identify it as verbalized text. The project consists of a 32-bit ARM-based microcontroller LPC2148, a GSM SIM900 module, an LED, a motor and an Android application for user interface with the hardware to facilitate Bluetooth and Wi-Fi connection between Android-based PDAs and remote wireless display boards.
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