Shadi Basurra

• Birmingham City University

The Internet of Things (IoT) and unmanned aerial vehicles (UAVs) continue to advance the low-carbon smart agriculture technologies for next-generation consumer electronics and unlock more informed agricultural practices. Reinforcement learning (RL), federated learning (FL), and federated reinforcement learning (FRL) have demonstrated notable achiev...

Detecting faulty pipelines in water management systems is crucial for ensuring a reliable supply of clean water. Traditional inspection methods are often time-consuming, costly, and prone to errors. This study introduces an AI-based model utilizing images to detect pipeline defects, focusing on leaks, cracks, and corrosion. The YOLOv8 model is empl...

The growing problem of unsolicited text messages (smishing) and data irregularities necessitates stronger spam detection solutions. This paper explores the development of a sophisticated model designed to identify smishing messages by understanding the complex relationships among words, images, and context-specific factors, areas that remain undere...

Metastatic breast cancer (MBC) continues to be a leading cause of cancer-related deaths among women. This work introduces an innovative non-invasive breast cancer classification model designed to improve the identification of cancer metastases. While this study marks the initial exploration into predicting MBC, additional investigations are essenti...

The unregulated proliferation of counterfeit branding in the era of digital technology poses a significant risk to the worth of brands and erodes the confidence of consumers. In order to tackle this particular-ular difficulty, the present study focused on the domain of counterfeit logo identification, with a specific emphasis on three widely recogn...

With current and predicted economic pressures within English Children’s Services in the UK, there is a growing discourse around the development of methods of analysis using existing data to make more effective interventions and policy decisions. Agent-Based modelling shows promise in aiding in this, with limitations that require novel methods to ov...

This article introduces a prototype laser communication system integrated with uncrewed aerial vehicles (UAVs), aimed at enhancing data connectivity in remote healthcare applications. Traditional radio frequency systems are limited by their range and reliability, particularly in challenging environments. By leveraging UAVs as relay points, the prop...

Cardiovascular diseases present a significant global health challenge that emphasizes the critical need for developing accurate and more effective detection methods. Several studies have contributed valuable insights in this field, but it is still necessary to advance the predictive models and address the gaps in the existing detection approaches....

Ensuring consistent high water quality is paramount in water management planning. This paper addresses this objective by proposing an intelligent edge-cloud framework for water quality monitoring within the water distribution system (WDS). Various scenarios—cloud computing, edge computing, and hybrid edge-cloud computing—are applied to identify the...

Breast cancer is a major health problem worldwide, and accurate prediction of its recurrence is crucial to early detection of recurrence and personalised treatment. In recent years, various AI techniques have been applied to predict cancer recurrence with increasingly high accuracy. Graph Neural Networks (GNNs) have emerged as powerful tools for an...

Automated compliance checking (ACC) in the Architecture, Engineering, and Construction (AEC) sector represents a pivotal task which is traditionally executed manually, demanding significant time and labor. This work investigates the automation of the Requirement, Applicability, Selection, and Exception (RASE) methodology for building regulatory com...

Floorplan energy assessments present a highly efficient method for evaluating the energy efficiency of residential properties without requiring physical presence. By employing computer modelling, an accurate determination of the building’s heat loss or gain can be achieved, enabling planners and homeowners to devise energy-efficient renovation or r...

This work explored six machine learning algorithms: Extreme Gradient Boosting (XGBoost), Logistic Regression, Random Forest, Decision tree, Support Vector Machine (SVM), and Naïve Bayes to determine the best algorithm for detecting insurance fraud. The following were used to evaluate the six models: Confusion matrix, Accuracy, Precision, Recall, an...

The major goal of water management planning and the iterative evaluation of operational policies and procedures is to ensure that good water quality is always maintained. Effective water monitoring requires examining many water samples, which is a time-consuming and labor-intensive process that takes a lot of effort. This paper aims to evaluate the...

The stigma surrounding mental health in IT education and industry impacts productivity, health, and career prospects. Little research focuses on mental health factors and efforts in science, technology, engineering, and mathematics (STEM). This chapter collates important factors affecting mental health in STEM, identifies existing efforts, and high...

On March 11, 2020, the World Health Organization declared COVID-19 to be in a pandemic status after the number of confirmed cases had surpassed 118,000 cases in more than 110 countries worldwide. To aid decision-makers in battling the epidemic, accurate modelling and forecasting of the spread of confirmed and recovered COVID-19 cases is essential....

Cryptocurrency is branded as a digital currency, an alternative exchange currency system with significant ramifications for the economies of rising nations and the global economy. In recent years, cryptocurrency has infiltrated almost all financial operations; hence, cryptocurrency trading is frequently recognized as one of the most popular and pro...

With the dramatic increase of the global population and with food insecurity increasing, it has become a major concern for both individuals and governments to fulfill the need for foods such as vegetables and fruits. Moreover, the desire for the consumption of healthy food, including fruit, has increased the need for applications in the field of ag...

With current and predicted economic pressures within English Children's Services in the UK, there is a growing discourse around the development of methods of analysis using existing data to make more effective interventions and policy decisions. Agent-Based modelling shows promise in aiding in this, with limitations that require novel methods to ov...

Floorplan energy assessments present a highly efficient method for evaluating the energy efficiency of residential properties without requiring physical presence. By employing computer modeling, accurate determination of the building’s heat loss or gain can be achieved, enabling planners and homeowners to devise energy-efficient renovation or redev...

Cancer has received extensive recognition for its high mortality rate, with metastatic cancer being the top cause of cancer-related deaths. Metastatic cancer involves the spread of the primary tumor to other body organs. As much as the early detection of cancer is essential, the timely detection of metastasis, the identification of biomarkers, and...

Federated Learning (FL) is an innovative area of machine learning that enables different clients to collaboratively generate a shared model while preserving their data privacy. In a typical FL setting, a central model is updated by aggregating the clients’ parameters of the respective artificial neural network. The aggregated parameters are then se...

The wastewater quality index (WWQI) is one of the most significant methods of presenting meaningful values that reflect a fundamental characteristic of wastewater. Therefore, this study was performed to develop a prediction approach using WWQI for a regional wastewater treatment plant (WWTP) in Melaka, Malaysia. The regional system of WWTP provides...

The concept of molecular similarity has been commonly used in rational drug design, where structurally similar molecules are examined in molecular databases to retrieve functionally similar molecules. The most used conventional similarity methods used two-dimensional (2D) fingerprints to evaluate the similarity of molecules towards a target query....

Maintaining high water quality is the main goal for water management planning and iterative evaluation of operating policies. For effective water monitoring, it is crucial to test a vast number of drinking water samples that is time-consuming and labour-intensive. The primary objective of this study is to determine, with high accuracy, the quality...

Most recently, with the proliferation of IoT devices, computational nodes in manufacturing systems IIoT(Industrial-Internet-of-things) and the lunch of 5G networks, there will be millions of connected devices generating a massive amount of data. In such an environment, the controlling systems need to be intelligent enough to deal with a vast amount...

Deep neural networks have achieved state-of-art performance in many domains including computer vision, natural language processing and self-driving cars. However, they are very computationally expensive and memory intensive which raises significant challenges when it comes to deploy or train them on strict latency applications or resource-limited e...

Deep neural networks have achieved state-of-art performance in many domains including computer vision, natural language processing and self-driving cars. However, they are very computationally expensive and memory intensive which raises significant challenges when it comes to deploy or train them on strict latency applications or resource-limited e...

In response to the increased energy consumption in residential buildings, various efforts have been devoted to increase occupant awareness using energy feedback systems. However, it was shown that feedback provided by these systems is not enough to inform occupant actions to reduce energy consumption. Another approach is to control energy consumpti...

The Internet of Things (IoT) is the result of the convergence of sensing, computing, and networking technologies, allowing devices of varying sizes and computational capabilities (things) to intercommunicate. This communication can be achieved locally enabling what is known as edge and fog computing, or through the well‐established Internet infrast...

Machine learning has traditionally been solely performed on servers and high-performance machines. However, advances in chip technology have given us miniature libraries that fit in our pockets and mobile processors have vastly increased in capability narrowing the vast gap between the simple processors embedded in such things and their more comple...

This paper presents a novel model for simulating peer pressure effect on energy awareness and consumption of families. The model is built on two well-established theories of human behaviour to obtain realistic peer effect: the collective behaviour theory and the theory of cognitive dissonance. These theories are implemented in a collective agent-ba...

This paper presents a methodology to cascade probabilistic models and agent-based models for fine-grained data simulation, which improves the accuracy of the results and flexibility to study the effect of detailed parameters. The methodology is applied on residential energy consumption behaviour, where an agent-based model takes advantage of proba...

Several agent-based and probabilistic models were proposed to simulate human behaviour, which is an important cause of high energy consumption in buildings. However, some of these models ignore behavioural energy waste at occupant level, and when they model it, they are based on small case studies and produce high level energy consumption data. Thi...

Rising carbon emission levels present a pressing need for designers to develop zero carbon retrofit solutions. However, designers are constrained in exploring the various possibilities (design space) for developing a passive design based zero carbon retrofit solutions. This is due to the practice of a top-down approach provided by the contemporary...

Several energy systems have been developed and studied to help occupants reduce energy usage by providing feedback about their consumption. But recently, a major challenge has emerged about how to enable users to make informed energy efficiency decisions based on consumption feedback. This is because existing systems only present abstract consumpti...

Existing electricity feedback systems provide home occupants with real-time consumption data to enable them to control their consumption. However, these systems provide abstract consumption data that is not related to the occupants surrounding. Although there are some attempts to enrich consumption data with some context information, the presented...

Mobile Ad Hoc Networks (MANET) are self-configuring infrastructureless networks of mobile devices connected via wireless links. Each device can send and receive data, but it should also forward traffic unrelated to its own use. All need to maintain their autonomy, and effectively preserve their resources (e.g. battery power). Moreover, they can lea...

We are interested in organizations whose goals do not primarily involve profit, if it even figures at all, but which instead seek to create social capital in a wide variety of forms. Such organizations have widely varying lifetimes, but without an equivalent to accountancy to analyse their state of health and their evolution, it can be hard to esta...

In wireless mesh networks (WMN), most routing algorithms apply broadcasting at some stage of the path discovery process. They thereby consume large chunks of the network throughput. Intelligent rebroadcast algorithms aim to reduce this overhead by calculating the usefulness of a rebroadcast and the likelihood of collisions. Unfortunately, this intr...

In mobile ad-hoc networks (MANET), broadcasting is used intensively for path discovery. Minimizing redundant rebroadcasts and time latency during re-broadcast can considerably improve network performance and node connectivity. In this paper we propose a Zone-based Routing Protocol with Parallel Collision Guidance Broadcasting (ZCG) for MANET. The n...