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Praneeth N

Student

K.S. Institute of Technology, Bangalore, India  · India

2

Papers

Published Papers

AI BASED VOICE ORIENTED SIGNAL RECEPTION SYSTEM USING BLYNK
International Journal of Technology & Emerging Research Vol.?, No. May 2026 pp. 128–133

https://doi.org/10.64823/ijter.2605010

The rapid advancement of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has enabled the development of intelligent and user-friendly communication systems. This paper presents an AI voice-based oriented signal reception system using the Blynk platform, designed to facilitate seamless wireless communication and control through voice commands. The system integrates speech recognition techniques with IoT modules to receive, process, and transmit signals efficiently in real time. Voice inputs are captured using a microphone, processed through AI-based models for command interpretation, and transmitted via RF communication modules to a receiver unit. The receiver system decodes the incoming signals and performs corresponding actions, which can be monitored and controlled remotely using the Blynk mobile application. The proposed framework emphasizes low-cost implementation, ease of use, and accessibility for applications such as smart home automation, assistive technologies for physically challenged individuals, and remote monitoring systems

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AI BASED VOICE ORIENTED SIGNAL RECEPTION SYSTEM USING BLYNK
International Journal of Technology & Emerging Research Vol.?, No.

The rapid advancement of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has enabled the development of intelligent and user-friendly communication systems. This paper presents an AI voice-based oriented signal reception system using the Blynk platform, designed to facilitate seamless wireless communication and control through voice commands. The system integrates speech recognition techniques with IoT modules to receive, process, and transmit signals efficiently in real time. Voice inputs are captured using a microphone, processed through AI-based models for command interpretation, and transmitted via RF communication modules to a receiver unit. The receiver system decodes the incoming signals and performs corresponding actions, which can be monitored and controlled remotely using the Blynk mobile application. The proposed framework emphasizes low-cost implementation, ease of use, and accessibility for applications such as smart home automation, assistive technologies for physically challenged individuals, and remote monitoring systems.

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