Enhancing IoT Device Behavior Prediction through Machine Learning Models
الموضوعات :
Shubham Minhass
1
,
Ritu Chauhan
2
,
Harleen Kaur
3
1 - Amity Institute of Information Technology, Amity university, Noida, Uttar Pradesh, India
2 - Artificial Intelligence and IoT Lab, Center for Computational Biology and Bioinformatics, Amity university, Noida, Uttar Pradesh, India
3 - Department of Computer Science and Engineering, Jamia Hamdard, Delhi, India
الکلمات المفتاحية: Machine learning, predictive model, Smart Devices, Google Home Mini, Alexa, IoT, KNN,
ملخص المقالة :
There is an urgent need for precise and trustworthy models to forecast device behavior and evaluate vulnerabilities as a result of the Internet of Things' (IoT) explosive growth. By assessing the effectiveness of several machine learning algorithms logistic regression, decision trees, random forests, Naïve Bayes, and KNN on two popular IoT devices Alexa and Google Home Mini this study seeks to enhance IoT device behavior forecasting. Our results show that Naïve Bayes and random forest models are more accurate and efficient than other algorithms at predicting device behavior. These findings demonstrate how important algorithm selection is for maximizing the performance of IoT systems. The study also emphasizes the usefulness of precise device behavior prediction for practical uses such as industrial control systems, home automation, and medical monitoring. For example, accurate forecasts can improve decision-making in crucial situations, facilitate more seamless automation, and stop system failures. In addition to adding to the expanding corpus of research on IoT data analysis, this study establishes the foundation for the creation of increasingly sophisticated machine learning models that can manage the intricate and ever-changing nature of IoT ecosystems. Future studies should concentrate on increasing the dataset's diversity to encompass a wider range of IoT environments and devices and enhancing the model's adaptability to changing IoT environments.
[1] Bandyopadhyay, D., & Sen, J. (2011). Internet of things: Applications and challenges in technology and standardization. Wireless Personal Communications,58(1),49 69.
[2] A. Ghaffari, and A. Mahdavi, “Embedding Virtual Machines in Cloud Computing Based on Big Bang–Big Crunch Algorithm,” Journal of Information Systems and Telecommunication (JIST), vol. 28, no. 7, pp. 305-315, 2020.
[3] Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010
[4] Han, B., Zhang, Y., Chen, S., Liu, H., & Yu, Y. (2021). Human-centric IoT: A survey. IEEE Internet of Things Journal, 8(5), 3475–3494.
[5] He, L., Huang, X., Wang, Z., & Wang, S. (2019). An IoT-based intelligent home monitoring system using deep learning. Journal of Network and Computer Applications, 126, 9–18.
[6] Nazarpour, M., & Shokouhyar, S. (2022). Detection of Attacks and Anomalies in the Internet of Things System using Neural Networks Based on Training with PSO Algorithms, Fuzzy PSO, Comparative PSO and Mutative PSO. Journal of Information Systems and Telecommunication (JIST), 4(40), 270.
[7] Islam, M. R., Islam, M. R., Islam, M. R., & Hossain, M. S. (2019). A comparative analysis of machine learning algorithms for the prediction of stock prices. International Journal of Computers and Applications, 179(23), 44–50.
[8] Tehrani, Y. H., Fazel, Z., & Atarodi, S. M. (2018). A survey of two dominant low power and long range communication technologies. Journal of Information Systems and Telecommunication, 6(2), 60-66.
[9] Kanchan, A, and Agarwal, S. (2021). Internet of Things: A comprehensive review on architecture, applications, and future directions. Journal of Ambient Intelligence and Humanized Computing, 12(1), 1087–1110.
[10] Kavitha, M., & Saranya, T. (2018). IoT-based home automation system using deep learning. International Journal of Engineering and Technology, 7(4.22), 33–36.
[11] Kim, K. H., Kim, H. G., Kim, T. J., & Kim, S. W. (2019). A survey on IoT security technologies for IoT-based smart homes. Journal of Information Processing Systems, 15(2), 256–276.
[12] Kumar, P., Sharma, S., & Kumar, A. (2019). A study on the use of machine learning algorithms in predicting credit scores. Journal of Emerging Technologies and Innovative Research, 6(4), 207–212.
[13] Kussul, E., & Baidyk, T. (2020). Satellite big data analytics for disaster management: A review. International Journal of Disaster Risk Reduction, 49, 101759.
[14] Li, X., Wang, K., & Ma, J. (2019). A survey of machine learning for big data processing. EURASIP Journal on Wireless Communications and Networking, 2019(1), 1–20.
[15] Liu, Y., & Yang, S. (2021). Internet of Things (IoT) for supply chain management: A review. International Journal of Production Research, 59(18)
[16] Mukhopadhyay, S., Sung, A. H., & Lu, S. (2021). Internet of things: Challenges, advances, and applications. CRC Press.
[17] McGrath, M. J., Hussain, M. S., & Karim, S. (2020). The Internet of things: A review of the literature and future directions. Journal of Industrial Integration and Management, 5(1), 1–23.
[18] Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of things: A survey. Computer Networks, 54(15), 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010
[19] Dlay, S. S., Al-Sumaiti, S. A., & Al-Nuaimi, W. A. (2017). Internet of Things (IoT): Review of its security and privacy challenges. IEEE Access, 5, 16667–16677.
[20] Khazaei, M. (2022). Dynamic Tree-Based Routing: Applied in Wireless Sensor Network and IOT. Journal of Information Systems and Telecommunication (JIST), 3(39), 191.
[21] Suresh, A. M. Shehabeldin, and S. S. Al-Saqabi, "A Comprehensive Review on Internet of Things: Challenges and Future Directions," IEEE Access, vol. 7, pp. 68638-68659, 2019.
[22] Zandhessami, H., Alborzi, M., & Khayyatian, M. (2022). Reducing Energy Consumption in Sensor-Based Internet of Things Networks Based on Multi-Objective Optimization Algorithms. Journal of Information Systems and Telecommunication (JIST), 3(39), 180.
[23] Hamidi, H. (2016). Safe use of the internet of things for privacy enhancing. Journal of Information Systems and Telecommunication, 4(3), 145-151.
[24] Lopes, G. S., Da Silva, M. A., & Guimaraes, J. S. (2018). A survey on Internet of things: Architecture, security, and privacy. Journal of Network and Computer Applications, 108, 82–93.
[25] Fernandes, J. P., Gomes, D. A., & Khan, M. S. (2020). A comprehensive review on Internet of things: Applications, challenges, and future directions. Journal of Ambient Intelligence and Humanized Computing, 11(5), 2025–2055.
[26] Das, P. R., Pati, N. P., & Nayak, S. K. (2020). A review on the Internet of Things (IoT): Architecture, applications, security, and future directions. Journal of Network and Systems Management, 28(4), 1227–1253.
[27] Ahmed, T., Hussain, M., & Karim, S. (2019). Internet of Things (IoT) for smart agriculture: A comprehensive review. IEEE Access, 7, 139934–139951.
[28] Wang, Y., Guo, L., Li, Y., & Li, Y. A review of Internet of things.
