Azzedine Boukerche's research while affiliated with University of Ottawa and other places
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Publications (854)
Metaverse and affective computing are two promising areas. We envision a new generation of smart metaverse that will consider affective computing to develop artificial intelligence (AI)-empowered avatars capable of expressing emotions and enhancing interactions on users' metaverse sessions. This paper advocates for the symbiotic design of affective...
The Industrial Internet of Things (IIoT) has played a key role in enabling an efficient and interconnected industry through real-time communication and processing systems, thereby building on the principles of Industry 4.0. Nowadays, industrial systems are in the process of transitioning towards Industry 5.0, where humans will once again take cente...
Vehicle trajectory data is paramount in many applications and research areas, such as vehicular networks and Intelligent Transportation Systems (ITS). However, data gathered from location acquisition devices generally contain positional errors that hinder its applicability, and therefore processing techniques are necessary to improve the quality of...
As one of the most indispensable means of transportation in modern society, vehicles guarantee our daily commuting and logistics transportation. However, with the increasing number of vehicles, vehicles have also caused increasingly serious traffic safety problems while providing convenience to our lives. One of the most common of these is traffic...
Digital maps have been installed and attached to vehicles recently. They help with the GPS receivers to determine the relative locations of vehicles to other existing traffic and objects over the road network such as entrance/exit points, obstacles, road intersections, etc. This helps drivers or autonomous vehicles to decide the most appropriate re...
One of the main issues in the design of vehicular networks is understanding vehicles' mobility, which is determined by their type. In this work, we investigate how the mobility of buses influences the structure of a bus-based vehicular network. In this direction, we present a comprehensive analysis of bus mobility in vehicular networks. We generate...
Traveling vehicles participate in emphasizing the global warming problem due to the gases produced by them. The exponential increase in the number of daily traveling vehicles has exaggerated the world pollution problem threatening the life on the planet. This encourages several environmental organizations to look for designing green vehicles. Moreo...
The advancements in Internet of Things (IoT) and embedded systems, 5G networks and next-generation wireless systems, and embedded and distributed artificial intelligence are empowering Industry 4.0. In this new industrial era, smart autonomous and connected systems will improve efficiency, reduce cost and pollution, and increase productivity and sa...
The Internet of Drones (IoD) is a novel mobile network paradigm with particular aspects, demanding security and privacy requirements. Mix Zones (MZ) is a location privacy protection mechanism in traditional mobile networks focusing on anonymizing a node's identity. In this regard, Mix Zone Placement (MZP) is a current challenge related to the desig...
Marine farms must employ innovative solutions and new technologies to increase productivity and supply the seafood demand sustainably. In this paper, we propose a novel four-layers architecture for smart marine farms. The proposed architecture relies on recent advancements and proposes the integration of Internet of Things (IoT) and Internet of Und...
In the next years, drones will be part of our daily lives composing a parallel environment “over our heads,” having a dynamic traffic flow. The Internet of Drones (IoD) defines a robust and reliable distributed mobile network to manage and provide fair navigation and communication to drones. In this envisioned network environment, location privacy...
The Internet of Drones (IoD), also known as the Internet of Flying Things (IoFT), has grown significantly over the last years in several civilian areas. It has particular aspects compared to other mobile networks, such as drones' mobility and power constraints. Security is a mandatory requirement in this network paradigm, including location privacy...
A Internet of Drones (IoD) é uma arquitetura que possibilita que diferentes drones compartilhem o mesmo espaço aéreo. Um protocolo store-carry-forward pode ser adequado para manter a comunicação na rede. Além disso, diferentes redes podem colaborar para preencher as lacunas de comunicação. O objetivo principal deste trabalho é apresentar o IoDSCF –...
A Internet dos Drones (IoD) é um paradigma de rede no qual os drones voam por vias aéreas bem definidas. O Jamming Attack (JA) representa um risco grave para a IoD, podendo afetar a trajetória dos drones. Embora o JA tenha sido investigado em redes de UAVs, as soluções existentes consideram o espaço aéreo livre para voo, enquanto na IoD os drones v...
Trajectory data mining-based applications benefit from the increasing availability of vehicle trajectory and road network datasets. For instance, the application of trajectory prediction makes it possible to design more efficient routing protocols for vehicular networks. This paper proposes a novel cluster-based framework for the long-term predicti...
Urban computing (UC) is an interdisciplinary field that seeks to improve people's lives in urban areas. To achieve this objective, UC collects and analyzes data from several sources. In recent years, the Internet of Drones (IoD) has received significant attention from the academic community and has emerged as a potential data source for UC applicat...
With the recent demand of sustainable and green smart cities, we are witnessing a growing research initiative toward the development of efficient energy‐aware 5G/Wifi‐6 wireless networks. This has led to the development of what is referred to as the Internet of Energy‐based technology to support heterogeneous and complex wireless systems such as in...
The advancements of mobile devices and the rapid development of computing applications are encouraging a trend shift from traditional, centralized mobile cloud computing to decentralized mobile edge computing (e.g., cloudlet, fog, and multi-access edge computing) focused on the quality of service (QoS) of applications and quality of experience of u...
Mobile Crowdsensing (MCS) is a sensing paradigm that has transformed the way that various service providers collect, process, and analyze data. MCS offers novel processes where data is sensed and shared through mobile devices of the users to support various applications and services for cutting-edge technologies. However, various threats, such as d...
Driver identification has emerged as an active field of study to further personalize the integrated advanced driver-assistance systems into intelligent vehicles, provide security and safety for ride-hailing services, and prevent auto theft. Several studies, within recent years, have investigated non-intrusive identification approaches, focusing on...
5G-enabled Tactile Internet (TI) will rely on sensors, actuators, and ultra-reliable and ultralow latency communication for providing haptic human-machine interaction services. However, stringent requirements in terms of high reliability and sub-millisecond latency pose many daunting challenges that have limited the development of Tl services. In t...
Breast cancer is the second fatal disease among cancers patients both in Canada and across the globe. However, when detected early, a patients’ survival rate can be raised. Thus, researchers and scientists have been practicing to develop Computer-Aided Detection (CADe) and Computer-Aided Diagnosis (CADx) systems. Traditional CAD systems depend on m...
Breast cancer is the second most deadly type of cancer globally among women and can be preventable to a great extent in the case of early detection. Research scientists have conducted several experiments to develop tools to alleviate this problem in order to raise the survival rate, including Computer-Aided Diagnosis (CADx) systems. Deep Learning a...
In Mobile Crowdsensing (MCS), fake tasks can drain significant amount of resources. This paper proposes a new methodology to determine a proper time window for the training dataset and the impact of the accuracy of task legitimacy detection on the MCS campaign performance. To reach the desired performance, the task legitimacy detection is utilized...
The COVID-19 pandemic has stretched public health resources to the limits, and the only realistic way to keep the infection rates low is effective testing to prevent community transmission. In this research study, we propose an innovative method to empower autonomous vehicle-driven mobile assessment facilities to support early detection of the case...
The Internet of Drones (IoD) is a novel network paradigm that presents a unique mobile network scenario with particular characteristics. Hence, privacy is a mandatory aspect to be assured, but there is a lack of studies regarding location privacy protection in IoD. Mix Zones is a location privacy protection mechanism well explored in terrestrial mo...
Floods are the most common disaster in the world and cause deaths, damages to houses, buildings, and possessions, as well as disruption to communications. In such dynamic scenarios, it is needed to search and track mobile objects transported by the water flows, such as humans, animals, vehicles, and debris. The use of Unmanned Aerial Vehicles (UAVs...
Internet of Things (IoT) systems have advanced greatly in the past few years, especially with the support of Machine Learning (ML) and Artificial Intelligence (AI) solutions. Numerous AI-supported IoT devices are playing a significant role in providing complex and user-specific smart city services. Given the multitude of heterogeneous wireless netw...
Automated and coordinated vehicle platoon driving is challenging as the complexity of vehicle control and the presence of unreliable wireless inter-vehicle communication. This subject has an interdisciplinary nature, involving control theories, vehicle dynamics, and communication. Due to the constant interaction between control logic and communicat...
Internet of Things (IoT) and 5G network are fundamental building blocks for Industrial Internet of Things (IIoT). IoT has enabled real-time monitoring and actuation in industrial floors and machinery,aimed at improving the efficiency and safety of industrial activities and processes. On the other hand,5G networks will provide ultra-reliable and low...
With the vast data loads produced by numerous applications and services, network softwarization became a vital addition to the design of intelligent heterogeneous vehicular networks. Smart Software-Defined Vehicular Networks (S-SDVN) are promising solutions that support various applications and protocols such as network mobility management, routing...
The next generation of sustainable vehicular networks is expected to have a wide range of access technologies, multi-homing capabilities, and traffic demand and pattern heterogeneity. In order to deliver massive data loads from various services and applications to end-users, network softwarization is a key contributor that mitigates challenges in h...
Internet of Things(IoT) facilitates key technologies that rely on sensing, communication and processing in daily routines. As an IoT-enabled paradigm, mobile crowdsensing (MCS) can offer more possibilities for data collection to support various IoT applications and services. As an extension, MCS can be used for data gathering amid COVID-19 pandemic...
In wireless sensor networks, energy efficiency is a very critical issue as it impacts the network’s lifetime and performance. Mobile data collection and wireless charging are two promising emerging techniques for enhancing energy efficiency. To achieve high charging rates and implement data collection with less energy consumption of sensors, we des...
The advent of in-vehicle networking systems as well as state-of-the-art sensors and communication technologies have facilitated the collection of large volume and almost real-time data on vehicles and drivers, thus opening up future possibilities. Processing and analyzing this data provides unprecedented opportunities to offer remarkable insights a...
Fuel consumption and gas emissions of traveling vehicles have become of great consideration for green environmental researchers. Several technologies have been developed to enhance the efficiency of daily traveling vehicles in terms of fuel consumption. Moreover, many protocols have been developed to reduce the fuel consumption and emissions of tra...
Underwater wireless sensor networks (UWSNs) have emerged as an enabling technology for aquatic monitoring. However, data delivery in UWSNs is challenging, due to the harsh aquatic environment and characteristics of the underwater acoustic channel. In recent years, underwater nodes with multi-modal communication capabilities have been proposed to cr...
Intelligent vehicular networks emerge as a promising technology to provide efficient data communication in transportation systems and smart cities. At the same time, the popularization of devices with attached sensors has allowed the obtaining of a large volume of data with spatiotemporal information from different entities. In this sense, we are f...
Improving the efficiency of traffic signal control is an effective way to alleviate traffic congestion at signalized intersections. To achieve effective management of the system-wide traffic flows, current researches tend to focus on applying reinforcement learning (RL) techniques for collaborative traffic signal control in a traffic road network....
The concept of Multi-access Edge Computing (MEC) extends the provisioning of computing and storage capabilities from remote Cloud Data Centers (DC) to the proximity of end users via heterogeneous networks. By augmenting User Equipment (UE) with external computing power under the local coverage, Cloudlet-based offloading performs as a critical enabl...
Software-Defined Vehicular Networks (SDVNs) have been a vital component to various radio access technologies that supports massive data loads in various security and infotainment applications. SDVNs elevate the constraints of static hardware network devices to programmable units and provide a global view of the network's status and a common interfa...
Fifth generation (5G) wireless networks are designed to meet various end-user quality of service (QoS) requirements through high data rates (typically of gigabits per second) and low latencies. Coupled with fog and mobile edge computing, 5G can achieve high data rates, enabling complex autonomous smart city services such as the large deployment of...
Artificial Intelligence (AI) has revolutionized today's Internet of Things (IoT) applications and services by introducing significant technological enhancements across a multitude of domains. With the deployment of the fifth generation (5G) mobile communication network, smart city visions of fast, on-demand, intelligent user-specific services are n...
Citations
... To address this challenge, the concept of the Internet of Drones (IoD) has emerged, aimed at enhancing communication, navigation, and surveillance capabilities while concurrently integrating drone flight management [4][5][6]. Automatic drone identification (ADI) [7] is the essential component of the IoD framework to ascertain the presence of drones. ADI technology can be divided into two main categories: active and non-cooperative. ...
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... This allows for the real-time coordination of traffic and intelligent routing decisions, which can improve traffic flow and reduce congestion. SDIoV also provides a platform for deploying a wide range of ITSs, such as collision avoidance, automated parking, and smart traffic lights [126]. By enabling more efficient communication and data sharing among vehicles and infrastructure, SDIoV can improve the efficiency, safety, and sustainability of transportation systems [61]. ...
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... Path planning encompasses traditional path planning algorithms, bio-inspired intelligent algorithms, and deep reinforcement learning (DRL) algorithms. Currently, path planning is applied in various domains, including robotics [5,6], unmanned aerial vehicles [7,8], autonomous vehicles [9,10], road network construction through way-points [11,12], map navigation [13], and ship navigation [14]. Unlike path planning for robots and autonomous vehicles, path planning for large vessels such as ships presents unique challenges due to their size and the complexity of maneuvering in narrow waters. ...
... It has brought about significant advancements in many areas of research and industry. Notable deep learning architectures include Convolutional Neural Networks (CNNs) for image processing [14], Recurrent Neural Networks (RNNs) for sequential data [15], and Generative Adversarial Networks (GANs) for generating realistic images and data [16]. ...
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... 3) Smart cities: A set of smart devices are deployed in smart cities to improve the quality of life and services of their inhabitants [240]. Many applications and services are mainly based on the use of UAVs and IoT devices where the DC process constitutes an integral part of ensuring their proper functionalities (c.f., Fig. 9(c)). ...
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... This includes data like vehicular movements, speed, location updates, and other relevant interactions. Each event recorded in this chain undergoes rigorous validation processes to ensure authenticity and accuracy [77]. Roadside units (RSUs) and certain vehicles equipped with enhanced computational resources are responsible for validating these events before they are added to the event chain. ...
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... For multiintersection traffic signal control, a deep reinforcement learning-based cooperative approach was presented in [13]. In [14], introduced a traffic light scheduling algorithm called SmartLight that controls the competing traffic flows at the road intersections. ...
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... As artificial intelligence continues to advance, a number of scholars have begun to explore technological approaches to building assisted DIA using machine learning and deep learning in recent years [11][12][13][14]. Haq et al. [15] proposed a hybrid CNN and LSTM depth learning model to effectively predict the water quality of aquaculture. ...
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... Traffic forecasting is pivotal in the Intelligent Traffic System (ITS) since it can provide accurate road status data that aids informed decision-making for agencies Wang, Sun, and Boukerche 2022;Wang et al. 2022a). Consequently, it has gained considerable attention from both academia and industry (Wang et al. 2023a. ...
... Therefore, when dropping the rows of missing values the size of the dataset was shrunk to 1649 records. Table I [18]. High values of R 2 and lower values of RM SE are desired to reflect the high quality of the results. ...
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