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

An Optimization Algorithm for Embedded Raspberry Pi Pico Controllers for Solar Tree Systems

April 30, 2024 8:40 am
Solar photovoltaic (PV) systems stand out as a promising solution for generating clean, carbon-free energy. However, traditional solar panel installations often require extensive land resources, which could become scarce as the population grows. To address this challenge, innovative approaches are needed to maximize solar power generation within limited spaces. One...Read More
EIT publication

Design Optimization of a Grid-Tied Hybrid System for a Department at a University with a Dispatch Strategy-Based Assessment

March 23, 2024 1:51 pm
In this research project, the optimal design and design evaluation of a hybrid microgrid based on solar photovoltaics, wind turbines, batteries, and diesel generators were performed. The conventional grid-tied mode was used in addition to dispatch strategy-based control. The study’s test location was the loads in the Electrical, Electronic and...Read More
Renewable Energy Engineering

Enhancing Off-Grid Renewable Systems with Demand-Side Management

June 26, 2023 12:37 pm
Rural electrification is necessary for both the country’s development and the well-being of the villagers. The current study investigates the feasibility of providing electricity to off-grid villages in the Indian state of Odisha by utilizing renewable energy resources that are currently available in the study area. However, due to the...Read More

Cloud-Empowered Data-Centric Paradigm for Smart Manufacturing

April 3, 2023 2:10 pm
In the manufacturing industry, there are claims about a novel system or paradigm to overcome current data interpretation challenges. Anecdotally, these studies have not been completely practical in real-world applications (e.g., data analytics). This article focuses on smart manufacturing (SM), proposed to address the inconsistencies within manufacturing that are often...Read More
Dr Akhlaqur Rahman

A glance at engineering skill gaps, and how to address them

August 1, 2022 10:09 pm
Looking at the year ahead, we approached EIT lecturers, esteemed academics and industry professionals, to share their wisdom and identify potential engineering skill gaps which could be faced in 2023. We posed the following three questions to each of our experts: What are some skill gaps engineers could possibly face...Read More
EIT publication

Efficient Energy Distribution for Smart Household Applications

March 3, 2022 9:46 am
Energy distribution technique is an essential obligation of an intelligent household system to assure optimal and economical operation. This paper considers a small-scale household system detached from the power grids consisting of some electrical components in day-to-day life. Optimal power distribution generated from a photovoltaic system is vital for ensuring...Read More
EIT publication

A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data

January 4, 2022 10:31 am
Peak load reduction is one of the most essential obligations and cost-effective tasks for electrical energy consumers. An isolated microgrid (IMG) system is an independent limited capacity power system where the peak shaving application can perform a vital role in the economic operation. This paper presents a comparative analysis of...Read More
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