VOXAIOT: A Voice-Activated IoT System for Real-Time Automation and Smart Control Using Google Assistant and Arduino
DOI:
https://doi.org/10.64229/nmmevt80Keywords:
IoT, Voice Assistants, Smart Automation, Arduino, SDG 9 (Industry, Innovation, and Infrastructure)Abstract
Supported by the Internet of Things (IoT) and voice assistance, the project VOXAIOT is about developing a new high-level automation system. Google Assistant is used to control and display feedback for an Arduino Uno project that is made up of a buzzer, LED, PIR sensor, ultrasonic sensor, resistor, breadboard, and jumper wires. Monitoring via voice commands is allowed with this smooth integration, contributing to the enhancement of user experience and system interaction. The system is based on different types of sensors performing motion detection and distance measurement, providing both security and automation features. The PIR sensor is used to motion detection, and the ultrasonic sensor is used to displacement measurement, which can provide precise data to the control system. Google Assistant serves as voice interface, through which the user can enable/disable the sensors, and do actions such as turning the LED light on/off, blow the buzzer, etc. The primary feature that differentiates VOXAIOT is the marriage of hardware with the cloud, which facilitates high-acuity voice control with very low lag time. This allows the system to quickly heeds voice commands, leaving the interaction uninterrupted. The experiment reveals the feasibility of using voice recognition and IoT to design a smart home/industrial automation based solution. The findings demonstrate the effectiveness of the framework to integrate low-level hardware with cloud services, yielding a novel way to command and monitor automation system by voice commands.
References
[1]Kumar, R., & Singh, M. (2023). Smart Home Automation Using IoT and Voice Assistants. IEEE Transactions on IoT.
[2]K Rai, A., Singh, S., & Kushwaha, S. (2024). Optimized handwritten digit recognition: A convolutional neural network approach. 2024 International Conference on Communication, Control, and Intelligent Systems (CCIS), 1-5. Mathura, India.
[3]Rai, A., Singh, S., & Kushwaha, S. (2024). Hybrid watermarking techniques in medical imaging: A comprehensive analysis and performance evaluation. 2024 International Conference on Communication, Control, and Intelligent Systems (CCIS), 1-5. Mathura, India.
[4]Sharma, G., & Kushwaha, S. (2024). A comprehensive review of multi-layer convolutional sparse coding in semantic segmentation. 2024 9th International Conference on Communication and Electronics Systems (ICCES), 2050-2054.
[5]Kushwaha, S., Kondaveeti, S., Vasanthi, S. M., W, T. M., Rani, D. L., & Megala, J. (2024). Graph-informed neural networks with green anaconda optimization algorithm based on automated classification of condition of mental health using alpha band EEG signal. 2024 4th International Conference on Sustainable Expert Systems (ICSES), 44–50.
[6]Kushwaha, S., & Rai, A. (2024). Mobile cloud computing: The future of cloud. 2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0, 1-6.
[7]Kushwaha, S., Sathish, P., Thankam, T., Rajkumar, K., Kumar, M. D., & Gadde, S. S. (2024). Segmentation of breast cancer from mammogram images using fuzzy clustering approach. In Proceedings of the 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-6). Chennai, India.
[8]Singh, C., V, S. R., Vyas, N. K., Gupta, M., Kushwaha, S., & Prasanna, N. M. S. (2024). Sending query data to mobile sinks at high speed in wireless sensor networks. In Proceedings of the 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) (pp. 1-5). Chennai, India.
[9]Kushwaha, S., Amuthachenthiru, K., K, G., Narasimharao, J., M, D. K., & Gadde, S. S. (2024). Development of advanced noise filtering techniques for medical image enhancement. In Proceedings of the 5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV) (pp. 906-912). Tirunelveli, India. https://doi.org/10.1109/ICICV62344.2024.00149.
[10]Kumar, V., & Kushwaha, S. (2024). Optimized hybrid metaheuristic model for MapReduce task scheduling applications – A novel framework. In Proceedings of the IEEE 5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2024) (pp. 1-7). Tirunelveli, India.
[11]Kushwaha, S. (2023). An effective adaptive fuzzy filter for SAR image noise reduction. In Proceedings of the IEEE Global Conference on Information Technologies and Communications (GCITC) hosted by REVA University (pp. 1-5). India.
[12]Kushwaha, S., Boga, J., Rao, B. S. S., Taqui, S. N., Vidhya, R. G., & Surendiran, J. (2023). Machine learning method for the diagnosis of retinal diseases using convolutional neural network. In Proceedings of the IEEE 2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) (pp. 1-6). Chennai, India.
[13]Kushwaha, S., V, A., Kumar, B. S., Singh, N., Prabagar, S., & Supriya, B. Y. (2023). Efficient software vulnerability detection with minimal data size in 5G-IoT. In Proceedings of the IEEE 2023 International Conference on Emerging Research in Computational Science (ICERCS) (pp. 1-6). Coimbatore, India.
[14]Kumar, V., & Kushwaha, S. (2023). Comparative study of map reduce task scheduling optimization techniques. In Proceedings of the IEEE 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT) (pp. 1-7). Bengaluru, India.
[15]Kousar, H., Fatima, S., Ahmed, S. I., Sajithra, S., Kushwaha, S., & Balaji, N. A. (2023). AI-based security for Internet of Transportation Systems. 2023 4th International Conference on Smart Electronics and Communication (ICOSEC), 701–708, India.
[16]Singh, C., Jayakumar, S., Venneti, K., Ponsudha, P., Kushwaha, S., & Kalpana, P. E. (2023). Integrated project for data communication in wireless sensor network. In Proceedings of the IEEE 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-5). India.
[17]Kushwaha, S., S, S., Hariharan, G., Vidhya, K., Reddy, R. V. K., & Madan, P. (2023). Kohonen self-organizable maps based classification of optical code division multiple access codes. In Proceedings of the 2023 International Conference on Inventive Computation Technologies (ICICT) (pp. 1580-1584). Lalitpur, Nepal.
[18]Raviraja, S., Seethalakshmi, K., Kushwaha, S., Priya, V. P. M., Kumar, K. R., & Dhyani, B. (2023). Optimization of the ART tomographic reconstruction algorithm - Monte Carlo simulation. In Proceedings of the 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 984-988). Salem, India.
[19]Kumar, V., & Kushwaha, S. (2023). Map-Reduce task scheduling optimization techniques: A comparative study. In Proceedings of the 2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) (pp. 729-736). Tirunelveli, India.
[20]Kushwaha, S. (2023). A futuristic perspective on artificial intelligence. In Proceedings of the IEEE OPJU International Technology Conference on Emerging Technologies For Sustainable Development (pp. 1-6). O.P. Jindal University, Raigarh, Chhattisgarh, India.
[21]Kushwaha, S. (2023). Review on artificial intelligence and human computer interaction. In Proceedings of the IEEE OPJU International Technology Conference on Emerging Technologies For Sustainable Development (pp. 1-6). O.P. Jindal University, Raigarh, Chhattisgarh, India.
[22]Gupta, S., Verma, S. K., Samanta, S., Khatua, S., & Kushwaha, S. (2022). Prospect of Li-ion battery in designing environment friendly hybrid electric vehicles. In Proceedings of the International Conference on Advanced Earth Sciences & Foundation Engineering (ICASF-2022) (Vol. 1110, pp. 1-8). Chandigarh University, Punjab, India.
[23]Kushwaha, S., Jayaprakash, M., Swamy, V. K., Senthil, V., Maddila, S. K., & Anusuya, M. (2022). Design and development of communication networks using IoT. In Proceedings of the International Conference on Materials, Computing, Communication Technologies (ICMCCT 2022) (pp. 275-283). Cheran College of Engineering, Karur, Tamilnadu, India. ISBN: 9788770229555.
[24]Kumar, V., & Kushwaha, S. (2022). An optimized job scheduling mechanism for MapReduce framework using DIW-WOA in big data. In Proceedings of the IEEE International Conference on Knowledge Engineering and Communication Systems (ICKECS-2022) (pp. 1-8). SJC Institute of Technology, Chickballapur, Karnataka, India.
[25]Mohan, M., Patil, A., Mohana, S., Subhashini, P., Kushwaha, S., & Pandian, S. M. (2022). Multi-tier kernel for disease prediction using texture analysis with MR images. In Proceedings of the IEEE International Conference on Edge Computing and Applications (ICECAA 2022) (pp. 1020-1024). Gnanamani College of Technology, Namakkal, Tamilnadu, India. ISBN: 978-1-6654-8232-5.
[26]Lee, S. H. (2019). A Study on Cloud-Based IoT Systems for Real-Time Data Monitoring. IEEE Transactions on Cloud Computing, 7(3), 430-438.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Sumit Kushwaha (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
