ORCID Profile
0000-0002-9596-1765
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-07-2022
Publisher: MDPI AG
Date: 10-06-2021
DOI: 10.3390/EN14123446
Abstract: 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%.
Publisher: Elsevier BV
Date: 11-2021
Publisher: IEEE
Date: 10-2018
Publisher: MDPI AG
Date: 24-05-2021
DOI: 10.3390/APP11114823
Abstract: 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.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 02-2021
Publisher: IEEE
Date: 06-2019
Publisher: MDPI AG
Date: 29-06-2021
DOI: 10.3390/EN14133910
Abstract: 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.
Publisher: Springer Science and Business Media LLC
Date: 07-01-2021
Publisher: IEEE
Date: 06-2019
Publisher: IEEE
Date: 10-2018
Publisher: MDPI AG
Date: 26-08-2021
DOI: 10.3390/SU13179611
Abstract: 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.
Publisher: MDPI AG
Date: 26-05-2021
DOI: 10.3390/APP11114907
Abstract: 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%.
Publisher: MDPI AG
Date: 02-05-2021
DOI: 10.3390/S21093157
Abstract: 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.
Publisher: MDPI AG
Date: 26-07-2021
DOI: 10.3390/FIRE4030040
Abstract: 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.
Publisher: IEEE
Date: 10-2018
Publisher: IEEE
Date: 10-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: MDPI AG
Date: 26-01-2021
DOI: 10.3390/SU13031276
Abstract: 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.
Publisher: Elsevier BV
Date: 08-2021
Publisher: MDPI AG
Date: 08-07-2021
DOI: 10.3390/BUILDINGS11070302
Abstract: 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.
Publisher: MDPI AG
Date: 13-09-2021
DOI: 10.3390/SU131810207
Abstract: Bushfires have been a key concern for countries such as Australia for a long time. These must be mitigated to eradicate the associated harmful effects on the climate and to have a sustainable and healthy environment for wildlife. The current study investigates the 2019–2020 bushfires in New South Wales (NSW) Australia. The bush fires are mapped using Geographical Information Systems (GIS) and remote sensing, the hotpots are monitored, and damage is assessed. Further, an Unmanned Aerial Vehicles (UAV)-based bushfire mitigation framework is presented where the bushfires can be mapped and monitored instantly using UAV swarms. For the GIS and remote sensing, datasets of the Australian Bureau of Meteorology and VIIRS fire data products are used, whereas the paths of UAVs are optimized using the Particle Swarm Optimization (PSO) algorithm. The mapping results of 2019–2020 NSW bushfires show that 50% of the national parks of NSW were impacted by the fires, resulting in damage to 2.5 million hectares of land. The fires are highly clustered towards the north and southeastern cities of NSW and its border region with Victoria. The hotspots are in the Deua, Kosciu Sako, Wollemi, and Yengo National Parks. The current study is the first step towards addressing a key issue of bushfire disasters, in the Australian context, that can be adopted by its Rural Fire Service (RFS), before the next fire season, to instantly map, assess, and subsequently mitigate the bushfire disasters. This will help move towards a smart and sustainable environment.
Publisher: Elsevier BV
Date: 09-2020
Location: Cyprus
No related grants have been discovered for ZAKRIA QADIR.