• Dr.Vineetha K R
• Lincy John

- In a few years, billions of connected gadgets will be installed in our homes, cities, automobiles, and industries, transforming the globe. Users and the environment will interact with devices with restricted resources. Many of these devices will use machine learning models to decipher the meaning and behavior of sensor data, as well as to make accurate predictions and judgments. The bottleneck will be the high number of linked things, which may cause the network to become congested. As a result, machine learning techniques must be used to include intelligence on end devices. By allowing computations to be done close to data sources, deploying machine learning on such edge devices reduces network congestion. The purpose of this paper is to provide an overview of the field. By allowing computations to be done close to data sources, deploying machine learning on such edge devices reduces network congestion. The goal of this paper is to give a review of the key strategies for executing machine learning models on low- performance hardware in the Internet of Things paradigm, paving the way for the Internet of Conscious Things. The main purpose of this paper is to define the state of the art and envisage development needs for systems that apply edge machine learning on Internet of Things devices. Furthermore, an example of edge machine learning implementation on a microcontroller, also known as machine learning on the edge, will be presented.

Artificial intelligence; machine learning; Internet of Things; edge devices; deep learning

"A REVIEW OF EDGE MACHINE LEARNING ALGORITHM FOR ARTIFICIAL INTELLIGENCE ENABLE SYSTEM AND IOT DEVICES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.e14-e26, May-2022, Available :http://www.jetir.org/papers/JETIR2205502.pdf

"A REVIEW OF EDGE MACHINE LEARNING ALGORITHM FOR ARTIFICIAL INTELLIGENCE ENABLE SYSTEM AND IOT DEVICES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppe14-e26, May-2022, Available at : http://www.jetir.org/papers/JETIR2205502.pdf