Convergence of Machine Learning and IoT: Towards Intelligent Sensing and Decision-Making

Authors

  • Sanjeev Gour Asst. Professor, Dept. of CS, Medi-Caps University, Indore.
  • Abdul Razzak Khan Qureshi Asst. Professor, Dept. of CS, Medi-Caps University, Indore.
  • Jitendra Choudhary Associate Professor, Dept. of CS, Medi-Caps University, Indore.
  • Ruby Bhatt Asst. Professor, Dept. of CS, Medi-Caps University, Indore.
  • Hemant Pal Asst. Professor, Dept. of CS, Medi-Caps University, Indore.
  • Govinda Patil Asst. Professor, Dept. of CS, Medi-Caps University, Indore.

Keywords:

artificial intelligence, machine learning, deep learning, predictive analytics, prescriptive analytics, data mining, big data, IoT and Machine Leaning based decision making

Abstract

In today's complex business landscape, organizations contend with an avalanche of data. Yet, the true value lies in the ability to transform this extensive data repository into insightful revelations that illuminate more strategic corporate maneuvers. This is precisely where the practice of IoT and Machine Leaning based decision-making emerges. By harnessing the potential of data and leveraging artificial intelligence (AI) capabilities, enterprises can seize the opportunity for well-informed selections that eventually lead to enhanced outcomes. This paper explores the concept of Machine Learning and IoT-powered decision-making and scrutinizes the pivotal role of AI in shaping these astute business resolutions.

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Published

10.11.2023

How to Cite

Gour, S. ., Qureshi, A. R. K. ., Choudhary, J. ., Bhatt, R. ., Pal, H. ., & Patil, G. . (2023). Convergence of Machine Learning and IoT: Towards Intelligent Sensing and Decision-Making. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 301–308. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3793

Issue

Vol. 12 No. 4s (2024)

Section

Research Article

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