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73
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Introduction
ANIS UR RAHMAN received the master's degree in parallel and distributed systems from UJF, France, and the Ph.D. degree in computer science from Grenoble University, France, in 2013. He is currently an Assistant Professor with NUST-SEECS, Pakistan. Besides, he is also working as Research Fellow at the Department of Information Systems, FSKTM, University of Malaya, Malaysia. His main research interests include IoT and machine learning.
Additional affiliations
March 2019 - March 2020
August 2013 - present
October 2009 - April 2013
Education
October 2009 - April 2013
September 2008 - September 2009
Publications
Publications (73)
Joint species distribution modelling (JSDM) is a widely used statistical method that analyzes combined patterns of all species in a community, linking empirical data to ecological theory and enhancing community-wide prediction tasks. However, fitting JSDMs to large datasets is often computationally demanding and time-consuming. Recent studies have...
Bird populations respond rapidly to environmental change making them excellent ecological indicators. Climate shifts advance migration, causing mismatches in breeding and resources. Understanding these changes is crucial to monitor the state of the environment. Citizen science offers vast potential to collect biodiversity data. We outline a project...
Bird populations respond rapidly to environmental change making them excellent ecological indicators. Climate shifts advance migration, causing mismatches in breeding and resources. Understanding these changes is crucial to monitor the state of environment. Citizen science offers vast potential to collect biodiversity data. We outline a project tha...
Joint Species Distribution Modelling (JSDM) is a powerful and increasingly widely used statistical methodology in biodiversity modelling, enabling researchers to assess and predict the joint distribution of species across space and time. However, JSDM can be computationally intensive and even prohibitive, especially for large datasets and sophistic...
With advancing vehicular technology, there are challenges related to the computing capabilities of the deployed infrastructure. In a dense vehicular network, the system performance quickly degrades due to the scarcity of computing capacity and the heavy workload on the coordinating nodes. In situations of a road accident or slow-moving traffic, man...
Substantial research has been done in saliency modeling to make intelligent machines that can perceive and interpret their surroundings and focus only on the salient regions in a visual scene. But existing spatio-temporal saliency models either treat videos as merely image sequences excluding any audio information or are unable to cope with inheren...
The industrial environment augments resource-constrained devices to bring services closer to autonomous devices. However, over time, these devices get overburdened due to computational workload, which results in degraded network performance. Therefore, the devices are programmed to share resources with nearby devices. However, due to real-time coll...
Vehicular fog computing is an emerging paradigm for delay-sensitive computations. In this highly dynamic resource-sharing environment, optimal offloading decision for effective resource utilization is a challenging task. In recent years, deep reinforcement learning has emerged as an effective approach for dealing with resource allocation problems b...
Modern vehicles are developed with increasing levels of automation and connectivity. To improve the driving experience, the software requires frequent alterations adding new functionality and/or fixing software-related issues. In a typical connected vehicle ecosystem, over-the-air (OTA) updates provide a platform for safely distributing new softwar...
Pansharpening enhances spatial details of high spectral resolution multispectral images using features of high spatial resolution panchromatic image. There are a number of traditional pansharpening approaches but producing an image exhibiting high spectral and spatial fidelity is still an open problem. Recently, deep learning has been used to produ...
With recent advancements in software-defined vehicles, over-the-air (OTA) software updates are crucial to roll out new software and patches for connected vehicles. Traditionally, outdated vehicles are recalled by the manufacturers, however, owners are notoriously difficult to reach with recall notices. Also, organizational and procedural challenges...
A vehicular fog network is an emerging paradigm adopted to facilitate delay-sensitive and innovative applications. Since vehicular environments are inherently dynamic, it becomes a challenge to effectively utilize all available resources. Often a centralized resource distribution model is adopted for effective resource utilization but this comes wi...
Connected vehicle technology is rapidly evolving. In the U.S. the government targets that 50% of all vehicles be electric by 2030 in order to reduce climate change. This initiative comes in the wake of an increased spate of ransomware attacks targeting transportation companies. Unlike traditional ransomware targeting computer networks, the compromi...
With an ever-increasing number of connected devices on roads, it becomes unsustainable to provide nearby specialized execution resources (compute and storage) for servicing innovative applications. Moreover, the vehicular environment being inherently ad hoc and opportunistic, not to mention highly mobile, makes it unsuitable to use traditional clou...
In developed countries like the USA, Germany, and the UK, the security forces used highly sophisticated equipment, fast vehicles, drones, and helicopters to catch offenders' vehicles. Whereas, in developing countries with limited resources such schemes cannot be utilized due to management cost and other constraints. In this paper, we proposed a fra...
Smart cities play a vital role to develop a sustainable infrastructure with efficient management of the Internet of things devices. The infrastructure is used to support various applications for smart hospitals, smart factories, and intelligent transportation systems. With the extensive deployment of Internet of things devices, unprecedented growth...
The industrial internet of things (IIoT) has emerged as an essential paradigm to enhance industrial operations and productivity through efficient utilization of available resources. The paradigm allows industrial devices to share computing resources based on locality constraints to support innovative services. In this paper, we propose a trusted mu...
Food and emotions are correlated. Recent research on the relationship between foods and emotions mainly focused on identifying emotions when viewing food images. The studies try to find image attributes that evoke food-related emotions. We concentrate on affective image classification and investigate the performance of different features in a food-...
Evolution of 3D graphics and graphical worlds has brought issues like content optimization, real-time processing, rendering, and shared storage limitation under consideration. Generally, different simplification approaches are used to make 3D meshes viable for rendering. However, many of these approaches ignore vertex attributes for instanced 3D me...
Substantial research has been done in saliency modeling to develop intelligent machines that can perceive and interpret their surroundings. But existing models treat videos as merely image sequences excluding any audio information, unable to cope with inherently varying content. Based on the hypothesis that an audiovisual saliency model will be an...
The recent development of deep neural networks attempts to go deeper through the layered architecture to solve complex problems. As expected, the deepening impacts the processing times for inferences in tasks like object classification and localization. This demands solutions for balancing computational resource requirements and extend the versatil...
National economy and growth rely heavily on electricity but rapid urbanization, expeditious industrialization and increased domestic use due to population growth are among the reasons for the severe energy crisis in developing countries. The extended demand-supply gaps, depleting reservoirs of fossil fuel, and the environmental hazards altogether i...
Collaborative robots are an emerging area where robots share resources among each other for mutual benefit. They are particularly becoming popular in a modern industrial environment, primarily to improve production efficiency. This often involves some sort of decision making at the robots. Traditionally, the robots are connected to the cloud infras...
Wireless Sensor Networks grow rapidly due to the sensing and scanning capabilities of nodes. The sensors are capable to move randomly and send periodic reports, hence they must be processed efficiently. This requirement increases the indexing burden, in particular, indexing the mobile sensors’ data. The grid-based indexing techniques in random mobi...
Vehicular ad hoc networks have enabled applications for real-time data sharing such as safety and infotainment services in smart cities. Notably, with the widespread adoption of the internet of things (IoT), the back-end networks are not designed to carry large amounts of data as it leads up to network congestion and consumes a significant amount o...
Streaming large amounts of data to cloud data centers cause network congestion resulting in high network and energy consumption. The concept of fog computing is introduced to reduce workload from backbone networks and support delay-sensitive Internet of Things (IoT) applications. The concept places compute, storage, and network services closer to t...
Streaming large amounts of data to cloud data centers cause network congestion resulting in high network and energy consumption. The concept of fog computing is introduced to reduce workload from backbone networks and support delay-sensitive Internet of Things (IoT) applications. The concept places compute, storage, and network services closer to t...
Recent advancement in communication among smart devices, vehicular fog computing introduces new dimensions for delay-sensitive applications. The traditional computing paradigm to install edge locations is no longer viable due to incurred latency while decision making, especially in delay-sensitive applications. In this paper, we propose a vehicle-t...
Outbreaks can overwhelm fragile health systems that lack the tools, infrastructure, policies, and systems to keep communities healthy and safe. Timely detection, preparedness, and appropriate response are essential for limiting both the loss of human life and social economic disaster due to disease outbreaks. Countries must build effective and sust...
With the widespread adoption of the internet of things (IoT) technologies towards building a smart city, connected devices often offload computation tasks to nearby edge locations (base stations) to reduce overall computation and network delay. However, serving an ever-increasing number of end devices at these traditional edge locations is becoming...
Since the inception of smart cities, vehicular networks has introduced new dimensions for delay-sensitive applications. The use of backend cloud data centers is no longer a viable solution due to incurred latency. Thus, to support such applications, computing devices are placed at edge locations to reduce communication delay improving the quality o...
Advancement of technology has enabled access to innovative applications for connected devices. To handle growing computation requirements, the backend cloud data centers become an inefficient solution due to the caused network overhead. This is generally alleviated using edge locations deployed to meet the increasing computing demands. This work pr...
The concept of smart farming has led to the use of technology to enhance agricultural productivity. With access to low-cost sensors and management systems, more farmers are adopting this technology to achieve sustainable growth. However, in literature, there are no simulation platforms to help researchers and users understand sensor deployment, and...
Smart city systems are fast emerging as solutions that provide better and digitized urban services to empower individuals and organizations. Mobile and cloud computing technologies can enable smart city systems to (1) exploit the portability and context-awareness of mobile devices and (2) utilize the computation and storage services of cloud server...
Smart cities are based on connected devices generating large quantities of data every instant. This data can be stored at a nearby edge location for initial processing but later sending it to the backend data centers for storage and further analysis consumes considerable network bandwidth. In this paper, we propose a large-scale data migration fram...
Understanding human visual attention and saliency is an integral part of vision research. In this context, there is an ever-present need for fresh and diverse benchmark datasets, particularly for insight into special use cases like crowded scenes. We contribute to this end by: (1) reviewing the dynamics behind saliency and crowds. (2) using eye tra...
Congestion in vehicular ad hoc networks affects the performance of delay-sensitive applications when exchanging emergency or general information sharing messages. In particular, during emergencies on roads like road accidents and security warnings demand high reliability and low latency. However, in traditional solutions, such messages use the same...
Existing simulators are designed to simulate a few thousand nodes due to the tight integration of modules. Thus, with limited simulator scalability, researchers/developers are unable to simulate protocols and algorithms in detail, although cloud simulators provide geographically distributed data centers environment but lack the support for executio...
Smart cities and the Internet of Things have enabled the integration of communicating devices for efficient decision making. Notably, traffic congestion is one major problem faced by daily commuters in urban cities. In developed countries, specialized sensors are deployed to gather traffic information to predict traffic patterns. Any traffic update...
Cloud is a multi-tenant paradigm providing resources as a service. With its easily available computing infrastructure, researchers are adopting cloud for experimental purposes. However, using the platform efficiently for parallel and distributed simulations comes with new challenges. One such challenge is that the simulations comprise logical proce...
Understanding human visual attention and saliency is an integral part of vision research. In this context, there is an ever-present need for fresh and diverse benchmark datasets, particularly for insight into special use cases like crowded scenes. We contribute to this end by: (1) reviewing the dynamics behind saliency and crowds. (2) using eye tra...
Cloud adoption has significantly increased using the infrastructure-as-a-service (IaaS) paradigm, in order to meet the growing demands of computing, storage, and networking, in small as well as large enterprises. Different vendors provide their customized solutions for OpenStack deployment on bare metal or virtual infrastructure. Among these many a...
Parallel discrete event simulation frameworks have been widely used to analyze the performance of traditional applications under different scenarios. The existing frameworks are designed to work on a cluster and cloud-based computing environments. With the current advances in the internet of things, there is a strong need to revamp such traditional...
With the advancement in communication technologies, Internet of vehicles presents a new set of opportunities to efficiently manage transportation problems using vehicle-to-vehicle communication. However, high mobility in vehicular networks causes frequent changes in network topology, which leads to network instability. This frequently results in em...
In this work, we propose a graph-based superpixel segmentation technique to perform spatiotemporal oversegmentation of videos. The generated superpixels are post-processed by applying a straightforward threshold-based foreground separation model. These superpixels are used in a conditional random field, and a potential function is defined, which is...
With the advancement in technology and inception of smart vehicles and smart cities, every vehicle can communicate with the other vehicles either directly or through ad-hoc networks. Therefore, such platforms can be utilized to disseminate time-critical information. However, in an ad-hoc situation, information coverage can be restricted in situatio...
Images have always had a significant affect on their viewers at an emotional level by portraying so much in a single frame. These emotions have also been involved in human decision making. Machines can also be made emotionally intelligent using 'Affective Computing', giving them the ability of decision making by involving emotions. Emotional aspect...
Humans seamlessly perceive a massive amount of information while observing a scene. Though humans recognize real-world scenes easily and accurately but its not the same for computers due to scene images variability, ambiguity, and diverse illumination and scale conditions. Scene classification is a fundamental problem which provides contextual info...
Players in computer games continue to rely on assistance for navigation in the game environment, even after hours of gameplay. This behavior is in contrast to the real world where spatial knowledge of an unfamiliar environment develops with experience and reliance on navigational assistance declines. The slow development of spatial knowledge in vir...