This page has only limited features, please log in for full access.
Coronavirus disease 2019 (COVID-19) is an infectious disease characterised by symptoms that are like the common cold. The current pandemic situation in anticipation of a vaccine has posed serious threats to the health and economic sectors of countries worldwide. To overcome the quick transmission of the virus, the government of Australia has also taken drastic measures to prevent its spread. These policies include an international and interstate travel ban, social distancing rules, lockdown, shutdown of educational institutes and work-from-home policies. Such rules have affected people on both behavioural and psychological levels. This study aims to analyse the effect of COVID-19 on Australian citizens, and therefore, the changed behaviour of citizens concerning their mobility patterns, transport preferences and shopping methods under the pandemic have been studied. A detailed literature search was adopted for gathering data related to the study theme, along with real-time evidence of changes in the behaviour of people following the pandemic. The socioeconomic impact of the pandemic on social inequality and thereby the effect on the vulnerable people of the population are also studied. Authentic surveys and statistical data are consulted to figure out how the new lifestyle choices of people will linger in the post-pandemic era. It was found that people in Australia have adopted the work-from-home regime, and new habits suiting the nationwide restrictions have become routine for many people.
Hafiz Suliman Munawar; Sara Imran Khan; Zakria Qadir; Yusra Sajid Kiani; Abbas Z. Kouzani; M. A. Parvez Mahmud. Insights into the Mobility Pattern of Australians during COVID-19. Sustainability 2021, 13, 9611 .
AMA StyleHafiz Suliman Munawar, Sara Imran Khan, Zakria Qadir, Yusra Sajid Kiani, Abbas Z. Kouzani, M. A. Parvez Mahmud. Insights into the Mobility Pattern of Australians during COVID-19. Sustainability. 2021; 13 (17):9611.
Chicago/Turabian StyleHafiz Suliman Munawar; Sara Imran Khan; Zakria Qadir; Yusra Sajid Kiani; Abbas Z. Kouzani; M. A. Parvez Mahmud. 2021. "Insights into the Mobility Pattern of Australians during COVID-19." Sustainability 13, no. 17: 9611.
Australia is a regular recipient of devastating bushfires that severely impacts its economy, landscape, forests, and wild animals. These bushfires must be managed to save a fortune, wildlife, and vegetation and reduce fatalities and harmful environmental impacts. The current study proposes a holistic model that uses a mixed-method approach of Geographical Information System (GIS), remote sensing, and Unmanned Aerial Vehicles (UAV)-based bushfire assessment and mitigation. The fire products of Visible Infrared Imager Radiometer Suite (VIIRS) and Moderate-resolution Imaging Spectroradiometer (MODIS) are used for monitoring the burnt areas within the Victorian Region due to the 2020 bushfires. The results show that the aggregate of 1500 m produces the best output for estimating the burnt areas. The identified hotspots are in the eastern belt of the state that progressed north towards New South Wales. The R2 values between 0.91–0.99 indicate the fitness of methods used in the current study. A healthy z-value index between 0.03 to 2.9 shows the statistical significance of the hotspots. Additional analysis of the 2019–20 Victorian bushfires shows a widespread radius of the fires associated with the climate change and Indian Ocean Dipole (IOD) phenomenon. The UAV paths are optimized using five algorithms: greedy, intra route, inter route, tabu, and particle swarm optimization (PSO), where PSO search surpassed all the tested methods in terms of faster run time and lesser costs to manage the bushfires disasters. The average improvement demonstrated by the PSO algorithm over the greedy method is approximately 2% and 1.2% as compared with the intra route. Further, the cost reduction is 1.5% compared with the inter-route scheme and 1.2% compared with the intra route algorithm. The local disaster management authorities can instantly adopt the proposed system to assess the bushfires disasters and instigate an immediate response plan.
Hafiz Munawar; Fahim Ullah; Sara Khan; Zakria Qadir; Siddra Qayyum. UAV Assisted Spatiotemporal Analysis and Management of Bushfires: A Case Study of the 2020 Victorian Bushfires. Fire 2021, 4, 40 .
AMA StyleHafiz Munawar, Fahim Ullah, Sara Khan, Zakria Qadir, Siddra Qayyum. UAV Assisted Spatiotemporal Analysis and Management of Bushfires: A Case Study of the 2020 Victorian Bushfires. Fire. 2021; 4 (3):40.
Chicago/Turabian StyleHafiz Munawar; Fahim Ullah; Sara Khan; Zakria Qadir; Siddra Qayyum. 2021. "UAV Assisted Spatiotemporal Analysis and Management of Bushfires: A Case Study of the 2020 Victorian Bushfires." Fire 4, no. 3: 40.
The magnetic levitation (MAGLEV) train uses magnetic field to suspend, guide, and propel vehicle onto the track. The MAGLEV train provides a sustainable and cleaner solution for train transportation by significantly reducing the energy usage and greenhouse gas emissions as compared to traditional train transportation systems. In this paper, we propose an advanced control mechanism using an Arduino microcontroller that selectively energizes the electromagnets in a MAGLEV train system to provide dynamic stability and energy efficiency. We also design the prototype of an energy-efficient MAGLEV train that leverages our proposed control mechanism. In our MAGLEV train prototype, the levitation is achieved by creating a repulsive magnetic field between the train and the track using magnets mounted on the top-side of the track and bottom-side of the vehicle. The propulsion is performed by creating a repulsive magnetic field between the permanent magnets attached on the sides of the vehicle and electromagnets mounted at the center of the track using electrodynamic suspension (EDS). The electromagnets are energized via a control mechanism that is applied through an Arduino microcontroller. The Arduino microcontroller is programmed in such a way to propel and guide the vehicle onto the track by appropriate switching of the electromagnets. We use an infrared-based remote-control device for controlling the power, speed, and direction of the vehicle in both the forward and the backward direction. The proposed MAGLEV train control mechanism is novel, and according to the best of our knowledge is the first study of its kind that uses an Arduino-based microcontroller system for control mechanism. Experimental results illustrate that the designed prototype consumes only 144 W-hour (Wh) of energy as compared to a conventionally designed MAGLEV train prototype that consumes 1200 Wh. Results reveal that our proposed control mechanism and prototype model can reduce the total power consumption by 8.3 × as compared to the traditional MAGLEV train prototype, and can be applied to practical MAGLEV trains with necessary modifications. Thus, our proposed prototype and control mechanism serves as a first step towards cleaner engineering of train transportation systems.
Zakria Qadir; Arslan Munir; Tehreem Ashfaq; Hafiz Suliman Munawar; Muazzam A. Khan; Khoa Le. A prototype of an energy-efficient MAGLEV train: A step towards cleaner train transport. Cleaner Engineering and Technology 2021, 4, 100217 .
AMA StyleZakria Qadir, Arslan Munir, Tehreem Ashfaq, Hafiz Suliman Munawar, Muazzam A. Khan, Khoa Le. A prototype of an energy-efficient MAGLEV train: A step towards cleaner train transport. Cleaner Engineering and Technology. 2021; 4 ():100217.
Chicago/Turabian StyleZakria Qadir; Arslan Munir; Tehreem Ashfaq; Hafiz Suliman Munawar; Muazzam A. Khan; Khoa Le. 2021. "A prototype of an energy-efficient MAGLEV train: A step towards cleaner train transport." Cleaner Engineering and Technology 4, no. : 100217.
Detecting buildings from high-resolution satellite imagery is beneficial in mapping, environmental preparation, disaster management, military planning, urban planning and research purposes. Differentiating buildings from the images is possible however, it may be a time-consuming or complicated process. Therefore, the high-resolution imagery from satellites needs to be automated to detect the buildings. Additionally, buildings exhibit several different characteristics, and their appearance in these images is unplanned. Moreover, buildings in the metropolitan environment are typically crowded and complicated. Therefore, it is challenging to identify the building and hard to locate them. To resolve this situation, a novel probabilistic method has been suggested using local features and probabilistic approaches. A local feature extraction technique was implemented, which was used to calculate the probability density function. The locations in the image were represented as joint probability distributions and were used to estimate their probability distribution function (pdf). The density of building locations in the image was extracted. Kernel density distribution was also used to find the density flow for different metropolitan cities such as Sydney (Australia), Tokyo (Japan), and Mumbai (India), which is useful for distribution intensity and pattern of facility point f interest (POI). The purpose system can detect buildings/rooftops and to test our system, we choose some crops with panchromatic high-resolution satellite images from Australia and our results looks promising with high efficiency and minimal computational time for feature extraction. We were able to detect buildings with shadows and building without shadows in 0.4468 (seconds) and 0.5126 (seconds) respectively.
Hafiz Munawar; Riya Aggarwal; Zakria Qadir; Sara Khan; Abbas Kouzani; M. Mahmud. A Gabor Filter-Based Protocol for Automated Image-Based Building Detection. Buildings 2021, 11, 302 .
AMA StyleHafiz Munawar, Riya Aggarwal, Zakria Qadir, Sara Khan, Abbas Kouzani, M. Mahmud. A Gabor Filter-Based Protocol for Automated Image-Based Building Detection. Buildings. 2021; 11 (7):302.
Chicago/Turabian StyleHafiz Munawar; Riya Aggarwal; Zakria Qadir; Sara Khan; Abbas Kouzani; M. Mahmud. 2021. "A Gabor Filter-Based Protocol for Automated Image-Based Building Detection." Buildings 11, no. 7: 302.
Sound localization is a vast field of research and advancement which is used in many useful applications to facilitate communication, radars, medical aid, and speech enhancement to but name a few. Many different methods are presented in recent times in this field to gain benefits. Various types of microphone arrays serve the purpose of sensing the incoming sound. This paper presents an overview of the importance of using sound localization in different applications along with the use and limitations of ad-hoc microphones over other microphones. In order to overcome these limitations certain approaches are also presented. Detailed explanation of some of the existing methods that are used for sound localization using microphone arrays in the recent literature is given. Existing methods are studied in a comparative fashion along with the factors that influence the choice of one method over the others. This review is done in order to form a basis for choosing the best fit method for our use.
Muhammad Liaquat; Hafiz Munawar; Amna Rahman; Zakria Qadir; Abbas Kouzani; M. Mahmud. Localization of Sound Sources: A Systematic Review. Energies 2021, 14, 3910 .
AMA StyleMuhammad Liaquat, Hafiz Munawar, Amna Rahman, Zakria Qadir, Abbas Kouzani, M. Mahmud. Localization of Sound Sources: A Systematic Review. Energies. 2021; 14 (13):3910.
Chicago/Turabian StyleMuhammad Liaquat; Hafiz Munawar; Amna Rahman; Zakria Qadir; Abbas Kouzani; M. Mahmud. 2021. "Localization of Sound Sources: A Systematic Review." Energies 14, no. 13: 3910.
Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Previously, sound source has been localized using six or more microphones. The precision of sound localization has been demonstrated to increase with the use of more microphones. In this research, however, we minimized the use of microphones to reduce the complexity of the algorithm and the computation time as well. The method results in novelty in the field of sound source localization by using less resources and providing results that are at par with the more complex methods requiring more microphones and additional tools to locate the sound source. The average accuracy of the system is found to be 96.77% with an error factor of 3.8%.
Muhammad Liaquat; Hafiz Munawar; Amna Rahman; Zakria Qadir; Abbas Kouzani; M. Mahmud. Sound Localization for Ad-Hoc Microphone Arrays. Energies 2021, 14, 3446 .
AMA StyleMuhammad Liaquat, Hafiz Munawar, Amna Rahman, Zakria Qadir, Abbas Kouzani, M. Mahmud. Sound Localization for Ad-Hoc Microphone Arrays. Energies. 2021; 14 (12):3446.
Chicago/Turabian StyleMuhammad Liaquat; Hafiz Munawar; Amna Rahman; Zakria Qadir; Abbas Kouzani; M. Mahmud. 2021. "Sound Localization for Ad-Hoc Microphone Arrays." Energies 14, no. 12: 3446.
Contaminated site management is currently a critical problem area all over the world, which opens a wide discussion in the areas of policy, research and practice at national and international levels. Conventional site management and remediation techniques are often aimed at reducing the contaminant levels to an acceptable level in a short period of time at low cost. Owing to the fact that the conventional approach may not be sustainable as it overlooks many ancillary environmental effects, there is an immense need of “sustainable” or “green” approaches. Green approaches address environmental, social and economic impacts throughout the remediation process and are capable of conserving the natural resources and protecting air, water and soil quality through reduced emissions and other waste burdens. This paper presents a methodology to quantify the environmental footprint of a cleanup for a hypothetical contaminated site by using the US Environmental Protection Agency’s (EPA) Spreadsheet for Environmental Footprint Assessment (SEFA). The hypothetical contaminated site is selected from a metropolitan city of Pakistan and the environmental footprint of the cleanup is analyzed under three different scenarios: cleanup without any renewable energy sources at all, cleanup with a small share of renewable energy sources, and cleanup with a large share of renewable energy sources. It is concluded that integration of renewable energy sources into the remedial system design is a promising idea which can reduce CO2, NOx, SOx, PM and HAP emissions up to 68%.
Muhammad Khan; Zakria Qadir; Muhammad Asad; Abbas Kouzani; M. Parvez Mahmud. Environmental Footprint Assessment of a Cleanup at Hypothetical Contaminated Site. Applied Sciences 2021, 11, 4907 .
AMA StyleMuhammad Khan, Zakria Qadir, Muhammad Asad, Abbas Kouzani, M. Parvez Mahmud. Environmental Footprint Assessment of a Cleanup at Hypothetical Contaminated Site. Applied Sciences. 2021; 11 (11):4907.
Chicago/Turabian StyleMuhammad Khan; Zakria Qadir; Muhammad Asad; Abbas Kouzani; M. Parvez Mahmud. 2021. "Environmental Footprint Assessment of a Cleanup at Hypothetical Contaminated Site." Applied Sciences 11, no. 11: 4907.
The study was conducted to assess the post 2010 flood risk management and resilience-building practices in District Layyah, Pakistan. Exploratory research was applied to gain knowledge of flood risk management to embed the disaster risk reduction, mitigation, and adaptation strategies at the local government and community level. Around 200 questionnaires were collected from the four devastated areas/union councils. Primary data from the field uncovered flood risk management practices by organizations, local government, and the community. It highlights resilience-building practices undertaken by the community through rehabilitation, community participation, and local indigenous practices. The role of the District Layyah’s local government and organizations to mitigate the 2010 flood and their contribution towards flood resilience in affected communities was investigated, as no comparable studies were carried out in the riverine belt of District Layyah previously. Moreover, the tangible and non-tangible measures to lessen the vulnerability to floods and improve flood risk governance at a local level were identified. This study makes a valuable contribution in strengthening the resilience building of vulnerable communities by recommending few changes in existing practices concerning flood risk at a local level.
Hafiz Munawar; Sara Khan; Numera Anum; Zakria Qadir; Abbas Kouzani; M. Parvez Mahmud. Post-Flood Risk Management and Resilience Building Practices: A Case Study. Applied Sciences 2021, 11, 4823 .
AMA StyleHafiz Munawar, Sara Khan, Numera Anum, Zakria Qadir, Abbas Kouzani, M. Parvez Mahmud. Post-Flood Risk Management and Resilience Building Practices: A Case Study. Applied Sciences. 2021; 11 (11):4823.
Chicago/Turabian StyleHafiz Munawar; Sara Khan; Numera Anum; Zakria Qadir; Abbas Kouzani; M. Parvez Mahmud. 2021. "Post-Flood Risk Management and Resilience Building Practices: A Case Study." Applied Sciences 11, no. 11: 4823.
Load forecasting plays a crucial role in the world of smart grids. It governs many aspects of the smart grid and smart meter, such as demand response, asset management, investment, and future direction. This paper proposes time-series forecasting for short-term load prediction to unveil the load forecast benefits through different statistical and mathematical models, such as artificial neural networks, auto-regression, and ARIMA. It targets the problem of excessive computational load when dealing with time-series data. It also presents a business case that is used to analyze different clusters to find underlying factors of load consumption and predict the behavior of customers based on different parameters. On evaluating the accuracy of the prediction models, it is observed that ARIMA models with the (P, D, Q) values as (1, 1, 1) were most accurate compared to other values.
Muhammad Shaukat; Haafizah Shaukat; Zakria Qadir; Hafiz Munawar; Abbas Kouzani; M. Mahmud. Cluster Analysis and Model Comparison Using Smart Meter Data. Sensors 2021, 21, 3157 .
AMA StyleMuhammad Shaukat, Haafizah Shaukat, Zakria Qadir, Hafiz Munawar, Abbas Kouzani, M. Mahmud. Cluster Analysis and Model Comparison Using Smart Meter Data. Sensors. 2021; 21 (9):3157.
Chicago/Turabian StyleMuhammad Shaukat; Haafizah Shaukat; Zakria Qadir; Hafiz Munawar; Abbas Kouzani; M. Mahmud. 2021. "Cluster Analysis and Model Comparison Using Smart Meter Data." Sensors 21, no. 9: 3157.
The Coronavirus Disease 2019 (COVID-19) is a major virus outbreak of the 21st century. The Australian government and local authorities introduced some drastic strategies and policies to control the outspread of this virus. The policies related to lockdown, quarantine, social distancing, shut down of educational institute, work from home, and international and interstate travel bans significantly affect the lifestyle of citizens and, thus, influence their activity patterns. The transport system is, thus, severely affected due to the COVID-19 related restrictions. This paper analyses how the transport system is impacted because of the policies adopted by the Australian government for the containment of the COVID-19. Three main components of the transport sector are studied. These are air travel, public transport, and freight transport. Various official sources of data such as the official website of the Australian government, Google mobility trends, Apple Mobility trends, and Moovit were consulted along with recently published research articles on COVID-19 and its impacts. The secondary sources of data include databases, web articles, and interviews that were conducted with the stakeholders of transport sectors in Australia to analyse the relationship between COVID-19 prevention measures and the transport system. The results of this study showed reduced demand for transport with the adoption of COVID-19 prevention measures. Declines in revenues in the air, freight, and public transport sectors of the transport industry are also reported. The survey shows that transport sector in Australia is facing a serious financial downfall as the use of public transport has dropped by 80%, a 31.5% drop in revenues earned by International airlines in Australia has been predicted, and a 9.5% reduction in the freight transport by water is expected. The recovery of the transport sector to the pre-pandemic state is only possible with the relaxation of COVID-19 containment policies and financial support by the government.
Hafiz Munawar; Sara Khan; Zakria Qadir; Abbas Kouzani; Mortoza Mahmud. Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective. Sustainability 2021, 13, 1276 .
AMA StyleHafiz Munawar, Sara Khan, Zakria Qadir, Abbas Kouzani, Mortoza Mahmud. Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective. Sustainability. 2021; 13 (3):1276.
Chicago/Turabian StyleHafiz Munawar; Sara Khan; Zakria Qadir; Abbas Kouzani; Mortoza Mahmud. 2021. "Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective." Sustainability 13, no. 3: 1276.
In the current technological era, predicting the power and energy output based on the changing weather factors play an important role in the economic growth of the renewable energy sector. Unlike traditional fossil fuel-based resources, renewable energy sources potentially play a pivotal role in sustaining a country’s economy and improving the quality of life. As our planet is nowadays facing serious challenges due to climate change and global warming, this research could be effective to achieve good prediction accuracy in smart grids using different weather conditions. In the current study, different machine learning models are compared to estimate power and energy of hybrid photovoltaic (PV)-wind renewable energy systems using seven weather factors that have a significant impact on the output of the PV–wind renewable energy system. This study classified the machine learning model which could be potentially useful and efficient to predict energy and power. The historic hourly data is processed with and without data manipulation. While data manipulations are carried out using recursive feature elimination using cross-validation (RFECV). The data is trained using artificial neural network (ANN) regressors and correlations between different features within the dataset are identified. The main aim is to find meaningful patterns that could help statistical learning models train themselves based on these usage patterns. The results suggest that opting feature selection technique using linear regression model outperforms all the other models in all evaluation metrics having to mean squared error (MSE) of 0.000000104, mean absolute error (MAE) of 0.00083, R2 of 99.6%, and computation time of 0.02 s The results investigated depict that the sustainable computational scheme introduced has vast potential to enhance smart grids efficiency by predicting the energy produced by renewable energy systems.
Zakria Qadir; Sara Imran Khan; Erfan Khalaji; Hafiz Suliman Munawar; Fadi Al-Turjman; M.A. Parvez Mahmud; Abbas Z. Kouzani; Khoa Le. Predicting the energy output of hybrid PV–wind renewable energy system using feature selection technique for smart grids. Energy Reports 2021, 1 .
AMA StyleZakria Qadir, Sara Imran Khan, Erfan Khalaji, Hafiz Suliman Munawar, Fadi Al-Turjman, M.A. Parvez Mahmud, Abbas Z. Kouzani, Khoa Le. Predicting the energy output of hybrid PV–wind renewable energy system using feature selection technique for smart grids. Energy Reports. 2021; ():1.
Chicago/Turabian StyleZakria Qadir; Sara Imran Khan; Erfan Khalaji; Hafiz Suliman Munawar; Fadi Al-Turjman; M.A. Parvez Mahmud; Abbas Z. Kouzani; Khoa Le. 2021. "Predicting the energy output of hybrid PV–wind renewable energy system using feature selection technique for smart grids." Energy Reports , no. : 1.
UAVs are increasingly incorporated in a wide range of domains such as disaster management and rescue missions. UAV path planning deals with finding the most optimal or shortest path for UAVs such that minimum energy and resources are utilized. This paper examines the path planning algorithms for UAVs through a literature survey conducted on 139 systematically retrieved articles published in the last decade that are narrowed down to 36 highly relevant articles. As retrieved from the shortlisted articles, the path planning algorithms include RRT, Artificial Potential, Voronoi, D-Star, A-Star, Dijkstra, MILP, Neural Network, Ant Colony Optimization, and Particle Swarm Optimization that are classified into four main types: Model-based, Conventional, Learning-based, and Cell-based. Most of the disaster-related articles are focused on the post-disaster phase only and use conventional and learning-based algorithms with applications to localize victims and optimize paths. Regarding the UAV communication network (UAVCN), the key challenges are communication issues, resource allocation, UAV deployment, defining UAV trajectory, and content security. UAV path planning’s key barriers are path optimization, path completeness, optimality, efficiency, and achieving robustness. Accordingly, a holistic IoT-powered UAV-based smart city management system has been recommended in the current study where all the smart city key components are integrated to address disasters like floods, earthquakes, and bush fire. The proposed holistic system can help prepare for disasters and mitigate them as soon as these arise and help enhance the smart city governance.
Zakria Qadir; Fahim Ullah; Hafiz Suliman Munawar; Fadi Al-Turjman. Addressing disasters in smart cities through UAVs path planning and 5G communications: A systematic review. Computer Communications 2021, 168, 114 -135.
AMA StyleZakria Qadir, Fahim Ullah, Hafiz Suliman Munawar, Fadi Al-Turjman. Addressing disasters in smart cities through UAVs path planning and 5G communications: A systematic review. Computer Communications. 2021; 168 ():114-135.
Chicago/Turabian StyleZakria Qadir; Fahim Ullah; Hafiz Suliman Munawar; Fadi Al-Turjman. 2021. "Addressing disasters in smart cities through UAVs path planning and 5G communications: A systematic review." Computer Communications 168, no. : 114-135.
Emerging Trends in the use of smart portable accessories, particularly within the context of the Internet of Things (IoT), where smart sensor devices are employed for data gathering, require advancements in energy management mechanisms. This study aims to provide an intelligent energy management mechanism for wearable/portable devices through the use of predictions, monitoring, and analysis of the performance indicators for energy harvesting, majorly focusing on the hybrid PV-wind systems. To design a robust and precise model, prediction algorithms are compared and analysed for an efficient decision support system. Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG) prediction algorithms are used to develop a Shallow Neural Network (SNN) for time series prediction. The proposed SNN model uses a closed-loop NARX recurrent dynamic neural network to predict the active power and energy of a hybrid system based on the experimental data of solar irradiation, wind speed, wind direction, humidity, precipitation, ambient temperature and atmospheric pressure collected from Jan 1st 2015 to Dec 26th 2015. The historical hourly metrological data set is established using calibrated sensors deployed at Middle East Technical University (METU), NCC. The accessory considered in this study is called as Smart Umbrella System (SUS), which uses a Raspberry Pi module to fetch the weather data from the current location and store it in the cloud to be processed using SNN classified prediction algorithms. The results obtained show that using the SNN model, it is possible to obtain predictions with 0.004 error rate in a computationally efficient way within 20 s. With the experiments, we are able to observe that for the period of observation, the energy harvested is 178 Wh/d, where the system estimates energy as 176.5 Wh/d, powering the portable accessories accurately.
Zakria Qadir; Enver Ever; Canras Batunlu. Use of Neural Network Based Prediction Algorithms for Powering Up Smart Portable Accessories. Neural Processing Letters 2021, 1 -36.
AMA StyleZakria Qadir, Enver Ever, Canras Batunlu. Use of Neural Network Based Prediction Algorithms for Powering Up Smart Portable Accessories. Neural Processing Letters. 2021; ():1-36.
Chicago/Turabian StyleZakria Qadir; Enver Ever; Canras Batunlu. 2021. "Use of Neural Network Based Prediction Algorithms for Powering Up Smart Portable Accessories." Neural Processing Letters , no. : 1-36.
The significance of renewable energy resources provide a great opportunity to meet a single household electricity demand in Northern Cyprus. Purposefully, a 6 kW PV-Wind hybrid system seems to offer significant economic savings relative to the conventional grid system. Therefore, the main intention is to shed light on the technical as well as economic feasibility of combining renewable sources. The solar irradiance and wind speed data are analyzed for four populous cities of TRNC using RET-Screen software. The expected energy consumption for a normal household in Northern Cyprus comes out to be 11.27 kWh/d using HOMER software. The proposed hybrid model integrated with Ni-MH battery is designed in MATLAB software to visualize the possible energy output to be feed to the load. The results show that the proposed model provides alternative incentives to the consumers and it is economically feasible.
Fadi Al-Turjman; Zakria Qadir; Mohammad Abujubbeh; Canras Batunlu. Feasibility analysis of solar photovoltaic-wind hybrid energy system for household applications. Computers & Electrical Engineering 2020, 86, 106743 .
AMA StyleFadi Al-Turjman, Zakria Qadir, Mohammad Abujubbeh, Canras Batunlu. Feasibility analysis of solar photovoltaic-wind hybrid energy system for household applications. Computers & Electrical Engineering. 2020; 86 ():106743.
Chicago/Turabian StyleFadi Al-Turjman; Zakria Qadir; Mohammad Abujubbeh; Canras Batunlu. 2020. "Feasibility analysis of solar photovoltaic-wind hybrid energy system for household applications." Computers & Electrical Engineering 86, no. : 106743.
In an attempt to hinder the advancement in climate change impacts, concerned people are motivated to invest in renewable energy systems. Follows, the proliferation in energy demand, especially in residential sector, is another concern because fossil-fuel sources are depleting as time progresses. Fortunately, renewable energy resources in some countries are available in abundance and can cover a large portion of residential sector's energy demand. Jordan, like many other parts of the world, enjoys a great potential of renewable energy resources. To tackle the aforementioned issues, in this study we aim at conducting a techno-economic feasibility assessment for an on-grid PV-Wind hybrid system in order to cover a typical household annual energy demand in Amman, Jordan. The analysis show that there is a great potential of supplying the household energy demand in most of the months annually and the system is able to generate excess energy that can be exported to the national grid, which generates significant project revenues. Furthermore, the hybrid system provides a price of energy (LCOE) lower than the national grid tariff. Consequently, this study contributes greatly to the country plans of reducing the reliance on imported fossil fuels for meeting its domestic energy demands.
Mohammad Abujubbeh; Vincent T. Marazanye; Zakria Qadir; Murat Fahrioglu; Canras Batunlu. Techno-Economic Feasibility Analysis of Grid-Tied PV-Wind Hybrid System to Meet a Typical Household Demand: Case Study - Amman, Jordan. 2019 1st Global Power, Energy and Communication Conference (GPECOM) 2019, 418 -423.
AMA StyleMohammad Abujubbeh, Vincent T. Marazanye, Zakria Qadir, Murat Fahrioglu, Canras Batunlu. Techno-Economic Feasibility Analysis of Grid-Tied PV-Wind Hybrid System to Meet a Typical Household Demand: Case Study - Amman, Jordan. 2019 1st Global Power, Energy and Communication Conference (GPECOM). 2019; ():418-423.
Chicago/Turabian StyleMohammad Abujubbeh; Vincent T. Marazanye; Zakria Qadir; Murat Fahrioglu; Canras Batunlu. 2019. "Techno-Economic Feasibility Analysis of Grid-Tied PV-Wind Hybrid System to Meet a Typical Household Demand: Case Study - Amman, Jordan." 2019 1st Global Power, Energy and Communication Conference (GPECOM) , no. : 418-423.
The massive inadequacy of energy because of overwhelming dependence on imported fuels has turned into an essential barrier to socio-financial progression in Pakistan. This illustration makes dissemination in adjacent gas costs and limits possibilities in the present state of affairs of new modern technology. The current opening between the call for and creation of energy in Pakistan is about 5000- 8000 MW with a standard augmentation of 68 % as per annum. Except for irrigation and water supply, water resources are additionally used to provide power. Nationwide water sources have well off the potential for hydropower age, evaluated as 60000 MW, which might be monetarily tackled. Out of this broad hydropower capacity, 11 % has been developed up until now. Hydropower is the top of the line to be had a choice in the current situation of addressing difficulties of anticipated future quality needs of our nation as it is far economical, sustainable and indigenous, therefore can be the prevalent supply of power. In this paper, we are analyzing the contribution of hydropower, which can be more than 40% and at the same time reducing the share of oil and gas from 64 % to 11.8%, which is favorable for the sustainable development of Pakistan.
Zakria Qadir; Mohammad Abujubbeh; Alveena Mariam; Murat Fahrioglu; Canras Batunlu. Hydropower Capacity of Different Power Sectors in Pakistan. 2019 1st Global Power, Energy and Communication Conference (GPECOM) 2019, 408 -412.
AMA StyleZakria Qadir, Mohammad Abujubbeh, Alveena Mariam, Murat Fahrioglu, Canras Batunlu. Hydropower Capacity of Different Power Sectors in Pakistan. 2019 1st Global Power, Energy and Communication Conference (GPECOM). 2019; ():408-412.
Chicago/Turabian StyleZakria Qadir; Mohammad Abujubbeh; Alveena Mariam; Murat Fahrioglu; Canras Batunlu. 2019. "Hydropower Capacity of Different Power Sectors in Pakistan." 2019 1st Global Power, Energy and Communication Conference (GPECOM) , no. : 408-412.
Bone fracture is a common problem in daily life which occurs when high pressure is applied on bone or by simple accident and also due to osteoporosis and bone cancer. Different techniques are used today to detect bone fractures such as X-Ray, Computed Tomography (CT-scan), Magnetic Resonance Imaging (MRI) and Ultrasound. Among these four modalities, X-ray diagnosis is commonly used for fracture detection. However, if the fracture is complicated, a CT scan or MRI may be needed for further diagnosis and operation. In this paper, it is intended to make a low-cost portable device for bone fracture detection of patients, having age between 15 to 45 years using sound waves generated by the vibrator of a mobile phone. FFT technique in MATLAB was applied to the generated sound waves to examine the difference between cracked and healthy bone by applying 200 Hz of the sampling frequency. The device will be useful for doctors and public alike since it is portable, practical, mobile and affordable. It must be noted that the proposed device is not intended for a replacement of standard methodologies like X-Ray but rather will serve to be used as an initial detection phase. It is hoped that a negative scan of this device will discount the need for the more costly and time-consuming X-Ray procedure.
Zakria Qadir; Muhammad Ali; Tayfun Nesimoglu. Design and Development of a Low Cost Device for Bone Fracture Detection Using FFT Technique on MATLAB. 2018 18th Mediterranean Microwave Symposium (MMS) 2018, 321 -324.
AMA StyleZakria Qadir, Muhammad Ali, Tayfun Nesimoglu. Design and Development of a Low Cost Device for Bone Fracture Detection Using FFT Technique on MATLAB. 2018 18th Mediterranean Microwave Symposium (MMS). 2018; ():321-324.
Chicago/Turabian StyleZakria Qadir; Muhammad Ali; Tayfun Nesimoglu. 2018. "Design and Development of a Low Cost Device for Bone Fracture Detection Using FFT Technique on MATLAB." 2018 18th Mediterranean Microwave Symposium (MMS) , no. : 321-324.
Human heart cardiac muscles activities can be represented graphically using electrical impulses. Electrocardiography (ECG) signals are very important for physicians to diagnose heart disease. In this study, Bluetooth device is used to transmit data wirelessly. For this purpose, the generated signal from heart beat sensor is analyzed in MATLAB using Support Vector Machine (SVM) and Discrete Wavelet Transform (DWT) techniques. ECG Simulator compares the actual signal of infants with the reference signal and notify the physician about healthy or unhealthy ECG signals. Additionally, simulating the ECG pattern of different infants before designing and developing any biomedical technology is quite efficient and cost-effective.
Haroon Rashid; Zakria Qadir; Moaz Zia; Tayfun Nesimoglu; Raroon Rashid. Wireless Monitoring of ECG Signal in Infants Using SWM and DWT Techniques. 2018 18th Mediterranean Microwave Symposium (MMS) 2018, 317 -320.
AMA StyleHaroon Rashid, Zakria Qadir, Moaz Zia, Tayfun Nesimoglu, Raroon Rashid. Wireless Monitoring of ECG Signal in Infants Using SWM and DWT Techniques. 2018 18th Mediterranean Microwave Symposium (MMS). 2018; ():317-320.
Chicago/Turabian StyleHaroon Rashid; Zakria Qadir; Moaz Zia; Tayfun Nesimoglu; Raroon Rashid. 2018. "Wireless Monitoring of ECG Signal in Infants Using SWM and DWT Techniques." 2018 18th Mediterranean Microwave Symposium (MMS) , no. : 317-320.