Dr. Akhlaqur Rahman

Dr. Akhlaqur Rahman (AK) is the Academic Course Coordinator and Lecturer for the school of Industrial Automation at Engineering Institute of Technology (EIT), Melbourne, Australia. AK is also member of IEEE and Engineers Australia (MIEAust). Akhlaqur completed his PhD from Swinburne University of Technology in 2019. Before joining Swinburne, he was a Lecturer and Coordinator for the Department of Electrical and Electronic Engineering, Uttara University, Dhaka, Bangladesh, from 2013 to 2014. From 2018 to 2019, he was involved as Research Assistant at Deakin University.

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EIT publication

A Study on Sensor System Latency in VR Motion Sickness

August 6, 2021 11:49 am
One of the most frequent technical factors affecting Virtual Reality (VR) performance and causing motion sickness is system latency. In this paper, we adopted predictive algorithms (i.e., Dead Reckoning, Kalman Filtering, and Deep Learning algorithms) to reduce the system latency. Cubic, quadratic, and linear functions are used to predict and...Read More
EIT publication

Industry 4.0 Applications for Medical/Healthcare Services

June 30, 2021 12:52 pm
At present, the whole world is transitioning to the fourth industrial revolution, or Industry 4.0, representing the transition to digital, fully automated environments, and cyber-physical systems. Industry 4.0 comprises many different technologies and innovations, which are being implemented in many different sectors. In this review, we focus on the healthcare...Read More
EIT publication

A Magnetic Hybrid Stationary Bicycle Design for Improved Standalone Power Generation

March 5, 2021 11:05 am
With the aim of developing smart standalone systems for improving power generation, this paper is focused on implementation of a hybrid stationary exercise bicycle for generating electricity with increased output power. With that in mind, the concept of magnetic forces has been utilized to assist the cyclist pedaling action, which...Read More
EIT publication

Load Profile Segmentation using Residential Energy Consumption Data

March 5, 2021 8:01 am
In this paper, a new approach for load profile segmentation is investigated for residential energy consumption. The proposed approach considers the daily level granularity and identifies dominant patterns of energy consumption for individual participants. The analysis uses adaptive k-means clustering to determine the number of clusters that improve the distances...Read More
EIT publication

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

February 23, 2021 1:33 pm
Robotic applications nowadays are widely adopted to enhance operational automation and performance of real-world Cyber-Physical Systems (CPSs) including Industry 4.0, agriculture, healthcare, and disaster management. These applications are composed of latency-sensitive, data-heavy, and compute-intensive tasks. The robots, however, are constrained in the computational power and storage capacity. The concept of...Read More
EIT publication

Detecting SARS-CoV-2 From Chest X-Ray Using Artificial Intelligence

February 23, 2021 1:05 pm
Chest radiographs (X-rays) combined with Deep Convolutional Neural Network (CNN) methods have been demonstrated to detect and diagnose the onset of COVID-19, the disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). However, questions remain regarding the accuracy of those methods as they are often challenged by limited...Read More
EIT publication

An Awareness Study of Smart Meters Radiation on Human Head

December 16, 2020 8:10 am
In the current state-of-the-art for smart grid technology, A key proponent for progress has been the advances made in the domain of smart meters. Essentially, smart meters are digital devices that use the wireless radio frequency (RF) technology to communicate in real-time with the energy utility company. Similar to their...Read More
EIT publication

Energy-efficient optimal task offloading in cloud networked multi-robot systems

May 28, 2019 2:58 pm
Task offloading plays a critical role in cloud networked multi-robot systems for leveraging computation support from cloud infrastructure and benefiting greatly from the well-developed cloud network facilities. However, considering the delay constraint, the extra costs of data transmission and remote computation, it is not trivial to make optimized offloading decisions....Read More
EIT publication

Communication-aware cloud robotic task offloading with on-demand mobility for smart factory maintenance

October 7, 2018 2:53 pm
The fourth industrial revolution introduces an ideal opportunity for inclusion of cloud-enabled robots in a factory environment to improve productivity and reduce human intervention. For this novel paradigm, task offloading plays a critical role in leveraging computation support from resourceful cloud infrastructure. In particular, network connectivity and on-demand mobility of...Read More
EIT publication

Cloud-Enhanced Robotic System for Smart City Crowd Control

December 21, 2016 3:05 pm
Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS)....Read More