Home Automation Using AI and IoT

K. D. Patil; Liladhar Gaikwad; Sujit Bhoite; Aditya Tajane; D. D. Kulkarni

doi:10.48001/jocevd.2024.2116-19

Authors

K. D. Patil Department of Electronics and Telecommunications Engineering, Trinity Academy of Engineering, Pune, Maharashtra, India
Liladhar Gaikwad Department of Electronics and Telecommunications Engineering, Trinity Academy of Engineering, Pune, Maharashtra, India
Sujit Bhoite Department of Electronics and Telecommunications Engineering, Trinity Academy of Engineering, Pune, Maharashtra, India
Aditya Tajane Department of Electronics and Telecommunications Engineering, Trinity Academy of Engineering, Pune, Maharashtra, India
D. D. Kulkarni Department of Electronics and Telecommunications Engineering, Trinity Academy of Engineering, Pune, Maharashtra, India

DOI:

https://doi.org/10.48001/jocevd.2024.2116-19

Keywords:

Artificial Intelligence (AI), Google Assistant, Home, Implementation, IoT (Internet of Things)

Abstract

The IoT network's massive data flows and storage can be easily managed with AI. IoT is currently growing more and more popular because to the development of high-speed internet networks and several cutting-edge sensors that can be incorporated into microcontrollers. The data that is now flowing across the internet includes user data that is sent and received from workstations as well as sensor data. Fewer data may really be experiencing challenges on the storage side, latency, channels limitation, and suffocation inside the networks due to the increase in the number of workstations and numerous sensors. Over the past ten years, several algorithms have been presented to prevent these issues. AI is still the only algorithm that can manage and regulate network congestion in addition to mining information. This paper's purpose is to demonstrate how an AI system is being used in the Internet of Things. The study emphasizes the significance of information management and mining. Additionally, the approach used in synthetic intelligence, such as fuzzy logics or neural networks, will be examined in this study in relation to IoT network. The software in specified networks and self-modifying networks are some of the essential parameters in the AI IoT system.

Downloads

Download data is not yet available.

References

Khan, S., Arshad, A., Mushtaq, G., Khalique, A., & Husein, T. (2020). Implementation of decentralized blockchain e-voting. EAI Endorsed Transactions on Smart Cities, 4(10).

http://dx.doi.org/10.4108/eai.13-7-2018.164859.

Kshetri, N., & Voas, J. (2018). Blockchain-enabled e-voting. IEEE Software, 35(4), 95-99.

https://doi.org/10.1109/MS.2018.2801546.

Kumar, S., & Qadeer, M. A. (2012). Application of AI in home automation. International Journal of Engineering and Technology, 4(6), 803.

https://doi.org/10.7763/IJET.2012.V4.488.

Panja, S., & Roy, B. (2021). A secure end-to-end verifiable e-voting system using blockchain and cloud server. Journal of Information Security and Applications, 59, 102815.

https://doi.org/10.1016/j.jisa.2021.102815.

Parihar, A. S., Prasad, D., Gautam, A. S., & Chakraborty, S. K. (2021). Proposed end-to-end automated e-voting through blockchain technology to increase voter’s turnout. In Proceedings of International Conference on Machine Intelligence and Data Science Applications: MIDAS 2020 (pp. 55-71). Springer Singapore.

https://doi.org/10.1007/978-981-33-4087-9_5.

Rathee, G., Iqbal, R., Waqar, O., & Bashir, A. K. (2021). On the design and implementation of a blockchain enabled e-voting application within IoT-oriented smart cities. IEEE Access, 9, 34165-34176.

https://doi.org/10.1109/ACCESS.2021.3061411.

Zhang, S., Wang, L., & Xiong, H. (2020). Chaintegrity: blockchain-enabled large-scale e-voting system with robustness and universal verifiability. International Journal of Information Security, 19, 323-341.

https://doi.org/10.1007/s10207-019-00465-8.