Energy Management for Internet of Things-enabled Smart Cities in the UAE (Working Paper)

The drastic increase in urbanization over the past few years in UAE requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, etc. Smart city solutions must have the ability to efficiently utilize energy and handle associated challenges. Electric Vehicles (EVs) are considered as a step forward towards the green environmental and economical transportation. In order to increase the penetration of EVs in the future transportation system, the smart charging management for EVs becomes necessary to fulfill the charging needs efficiently. Internet of Things (IoT) is an enabling technology through which efficient charging management for EVs can be done in order to manage EVs, efficiently utilize consumer resources, and save money. In this work, we will present a brief overview of charging management for EVs and associated challenges in smart cities. We will further investigate placement of charging stations and scheduling optimization for EVs charging in smart cities. We will present experimental and simulation results to exhibit the tremendous impact of the proposed schemes/ algorithms on the performance of IoT-enabled smart charging management for EVs

Towards a Novel Intrusion Detection Architecture using Artificial Intelligence

Artificial intelligence (AI) is a transformative technology for potential replacement of human tasks and activities within industrial, social, intellectual, and digital applications. Network intrusion detection is crucial to identify cyber-attacks in critical infrastructures where a dynamic collection and analysis of network traffic can be conducted using AI. In this research paper we develop a novel intrusion detection architecture to mitigate malicious traffic passing through cyber infrastructure of an organization. We propose to design scenarios based on AI for intelligent self-protection or alert system that will facilitate countering actual cyber-attacks. The system will utilize machine learning algorithm - Random Forest - to offer more flexibility to discover new attacks and to ensure training the system to predict them in the future. Moreover, we design spam filtering program on python to detect spam emails as per email is one of the main attacking vectors that threatens the security of critical infrastructures