SYSC 4907

CSE	SE	Comm	Biomed	EE	Aero	Special
Yes	Yes	Yes	No	No	No	No

Description

Artificial intelligence (AI) is quickly emerging as one of the fundamental technologies in communication networks that aims to tackle the resource management problems of complex networks such as the Internet of Things (IoT) networks. IoT systems are composed of different technologies such as edge computing and cloud computing that collaborate to deliver novel services such as smart city services and eHealth. However, training Machine Learning (ML) algorithms requires large amounts of data, which is where big data comes in. The project focuses on enabling the utilization of big data from different parts of an IoT system, including the sensor domain, edge, and cloud networks. Particularly, the project requires a data analytic component to be deployed in an edge server of a real IoT system. After that, big data can be gathered from the IoT system using network monitoring software. This is expected to support the big data requirements of ML algorithms and ultimately enhance the resource management of IoT systems. The objective of the project is to enable machine learning-based resource management of IoT systems by utilizing big data integrated from the different IoT domains, edge, cloud, and sensor domains. This includes: (i): learning about IoT systems and their main challenges, (ii): learning about machine learning and big data analytic for IoT resource management, (iii) implementing a basic IoT network that include, Raspberry Pie, edge server and cloud resources (iv) deploy a data analytics component for IoT data generation (v) utilize a network monitoring tool to gather real IoT data and (vi) verify the performance of the designed model by utilizing the big data for intelligent IoT resource management.

Prerequisites:

Excellent programming skills, some basic knowledge of AI and IoT

Keywords:

AI, IoT, Big Data Analytics