SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted Hospital's Agility and Lean in International Supply Chain Management during COVID-19(University of Exeter, 2024) Albadawi, Abdulrahman Ismail; Sam, Abraham JohnThis hypothesis stems from the assumption that even though KFSHRC had efficient strategies in place, the highly unforeseen nature of the pandemic illustrated the strategies that still needed to be improved. To do this, the study seeks to reject the following hypothesis: this research will analyze the employees' experiences and compare the efficiency of the approaches used in the hospital. The research aims to fill these gaps and limitations to evaluate KFSHRC precisely during the crisis response and recommend future improvements.6 0Item Restricted IoT-Enhanced Vehicular Networks: Simulation Frameworks for Energy Efficiency and Cyber-Security in Smart Cities(Newcastle University, 2025-05) Almutairi, Reham; Graham, Morgan; Giacomo, BergamiThe Internet of Things (IoT) has rapidly evolved over the past two decades, transforming the way we interact with the environment through a network of interconnected devices. The purpose of this thesis is to explore the integration of IoT with Vehicular Ad-Hoc Net- works (VANETs) in order to enhance intelligent transportation systems (ITS) and smart city infrastructure through the use of IoT. VANETs, characterized by high mobility and dynamic topology, play a crucial role in enhancing traffic safety, efficiency, and vehicu- lar services. They improve traffic safety by enabling real-time communication between vehicles and roadside infrastructure, allowing the sharing of critical information such as accident warnings and road conditions to prevent collisions and enhance emergency re- sponse times. VANETs boost traffic efficiency through intelligent traffic management, optimizing signal timings and route planning based on real-time data to reduce con- gestion and travel times. Additionally, they provide enhanced vehicular services such as infotainment, navigation assistance, and maintenance alerts, thereby improving the overall driving experience and vehicle performance monitoring. This research addresses the significant challenges of simulating VANET environments, particularly the high mobility of vehicles and the need for realistic traffic scenarios. Ex- isting VANET simulators, while advanced, often lack support for new technologies and comprehensive security systems, highlighting the necessity for more comprehensive sim- ulation frameworks. The primary aim of this PhD thesis is to integrate IoT and traffic simulations to accurately evaluate vehicular energy efficiency and overall network perfor- mance. Therefore, this thesis presents multilateral research towards optimization, mod- eling, and simulation of VANET and IoT environments. Several tools and algorithms have been proposed, implemented, and evaluated, considering various environments and applications.15 0Item Restricted The Application of IoT in Predictive Maintenance for Railway Systems: A Systematic Literature Review(University of Nottingham, 2024-09) Alghefari, Abdulrahman; Chesney, ThomasThis research explores the implementation of IoT-based predictive maintenance within railway systems, focusing on the technologies, cost implications, reliability, safety, and barriers identified in the literature. The study systematically reviews 30 peer-reviewed journals to assess the current state of IoT applications in the railway sector. Critical IoT technologies such as sensors, wireless sensor systems, and edge processing are examined in their role in enhancing predictive maintenance practices. The research highlights significant long-term cost savings associated with IoT adoption, despite high initial implementation costs. Furthermore, the study evaluates how IoT technologies contribute to improved reliability and safety by enabling real-time monitoring and predictive analysis. However, several barriers to widespread adoption are identified, including technical integration challenges, financial constraints, regulatory hurdles, and organisational resistance. The findings underscore the need for a strategic approach that will help tackle all obstacles by realising the benefits of IoT-predictive maintenance in the railway sector. This study offers significant insights for stakeholders, offering a deep understanding of the challenges of IoT-based predictive maintenance in railways. Future research directions are suggested, emphasising the importance of long-term studies, holistic approaches, and the integration of emerging technologies to address the identified barriers.21 0Item Restricted Simplifying IoT Application Deployment in Edge Computing Environment(newcastle university, 2019) Daghistan, iIsmail; Ranjan, RajivCurrently, deploying IoT Application in Edge Computing Environment is facing many challenges. For instance, the limited capabilities of Edge device alongside distributed nature of its Environment where all Edge devices needs to be programmed separately. As a result, edge Environment deployment tools needs to be lightweight and able to orchestrate the deployment effectively. Therefore. I decided to deploy Edge Computing Environment by using docker. Docker proved to be the most suitable tool. This is because Docker is lightweight and ability to run on the Edge . Then, I decided to simplify the deployment by using scripting, to allow the deployment to take place in on device rather than programming several devices. Finally, I will use REST api to capture the user’s requirements to generate and run a script based the that requirements. This will the user to deploy the Edge Environment with a single URL request.10 0Item Restricted A Simulation Framework for Evaluating the Performance of Blockchain-based IoT Ecosystems(Newcastle University, 2024-09-05) Albshri, Adel; Solaiman, EllisRecently, it has been appealing to integrate Blockchain with IoT in several domains, such as healthcare and smart cities. This integration facilitates the decentralized processing of IoT data, enhancing cybersecurity by ensuring data integrity, preventing tampering, and strengthening privacy through decentralized trust mechanisms and resilient security measures. These features create a secure and reliable environment, mitigating potential cyber threats while ensuring non-repudiation and higher availability. However, Blockchain performance is questionable when handling massive data sets generated by complex and heterogeneous IoT applications. Thus, whether the Blockchain performance meets expectations will significantly influence the overall viability of integration. Therefore, it is crucial to evaluate the feasibility of integrating IoT and Blockchain and examine the technology readiness level before the production stage. This thesis addresses this matter by extensively investigating approaches to the performance evaluation of Blockchain-based IoT solutions. Firstly, it systematically reviews existing Blockchain simulators and identifies their strengths and limitations. Secondly, due to the lack of existing blockchain simulators specifically tailored for IoT, this thesis contributes a novel blockchain-based IoT simulator which enables investigation of blockchain performance based on adaptable design configuration choices of IoT infrastructure. The simulator benefits from lessons learnt about the strengths and limitations of existing works and considers various design requirements and views collected through questioners and focus groups of domain experts. Third, the thesis recognises the shortcomings of blockchain simulators, such as support for smart contracts. Therefore, it contributes a middleware that leverages IoT simulators to benchmark real blockchain platforms' performance, namely Hyperledger Fabric. It resolves challenges related to integrating distinctive environments: simulated IoT models with real Blockchain ecosystems. Lastly, this thesis employs Machine Learning (ML) techniques for predicting blockchain performance based on predetermined configurations. Contrariwise, it also utilises ML techniques to recommend the optimal configurations for achieving the desired level of blockchain performance.69 0Item Restricted Acceptance of Internet of Things-based Innovations for Improving Healthcare in Saudi Arabia(Saudi Digital Library, 2023-09-27) Masmali, Feisal; Miah, ShahThe rapid evolution of Information Systems (IS) has ushered in a new era of digital transformation, with the Internet of Things (IoT) at the forefront. This research delves into the acceptance and integration of IoT-oriented IS applications in the healthcare sector of Saudi Arabia. With the primary objective of understanding the factors influencing the acceptance of IoT innovations in healthcare, this study offers a comprehensive analysis to capture the influence in terms of the potential benefits, challenges, and implications of integrating IoT into healthcare service delivery. Impact of IoT in IS, a paradigm shift in technology, enables essential objects equipped with sensors and software systems to communicate and exchange data over the Internet. This capability has revolutionized various industries, with healthcare being a notable beneficiary. The global healthcare sector has witnessed a surge in the acceptance of IoT innovations, particularly in remote public-healthcare atmospheres where patient monitoring and management are of paramount task. Thus, studying the impact of IoT may bring new insights for both researchers and practitioners that could contribute to create new knowledge in the target body of IS literature. In the country context of Saudi Arabia, the integration of IoT in healthcare systems presents a plethora of opportunities. The Saudi Arabian government has been proactive in endorsing the adoption of IoT technologies, establishing regulations, and fostering public-private partnerships to drive innovation. With the country's robust Internet infrastructure and government-backed initiatives like electronic health records and telehealth services, the potential for the IoT influence in relation to acceptance and integration in healthcare systems practices is immense, however existing studies are limited in this sub-field. A comprehensive study towards full-scale of IoT oriented system adoption in healthcare holds a lot of emerging challenges. This is related to data protection, privacy, infrastructure limitations, compliances and cybersecurity are of critical elements for further exploration. Additionally, issues like interoperability, financial constraints, and talent shortages need to be addressed to ensure seamless integration. Thus, it is imperative to develop new systematic empirical study in this subfield. This research adopts a mixed-methods approach, combining qualitative interviews with quantitative surveys, to investigate the aspects through a holistic viewpoint for developing new understanding to fill the significant knowledge gap in the IS literature. The qualitative phase, conducted with key stakeholders in Saudi Arabia's healthcare sector, offers in-depth insights into the current landscape and potential future trajectories. These findings then inform the quantitative phase, which aims to capture broader trends of IoT acceptance within the sector. These findings are consistent with a combined aspect of the Technology Acceptance Model (TAM) and the Diffusion of Innovation Model (DOI), which suggest that successful adoption and integration of IoT into healthcare systems requires knowledge, familiarity, and recognition of the usage of IoT. The PhD thesis is based on the combined theoretical underpinnings of Information Systems (IS) design, technology acceptance, and diffusion of innovations. In terms of technology acceptance, our study concentrates on the acceptance of Internet of Things-oriented IS applications and various service provisions, especially innovative ones, that practitioners in the healthcare sector can deploy and in terms of the diffusion of innovations it brings the practitioners view on the cutting-edge application of IoT in the aspect of IS design. That is why, the study's theoretical foundation is rooted in the combined framework of the Technology Acceptance Model (TAM) and the Diffusion of Innovation (DOI). This integrated model offers a comprehensive perspective on the multifaceted nature of technology acceptance, encompassing both individual perceptions and broader organizational influences. Key findings from the research highlight the pivotal role of knowledge and awareness in the successful implementation of IoT. The perceived benefits of IoT, such as enhanced patient care, improved communication, and streamlined processes, act as strong motivators for adoption. However, challenges related to system compatibility, training requirements, and financial constraints emerge as potential barriers. The thesis underscores the need for targeted interventions, strategic planning, and resource allocation to overcome these challenges. In summary, the acceptance of IoT in Saudi Arabia's healthcare sector holds the promise of transformative change. While the benefits are manifold, a strategic approach, underpinned by a deep understanding of the challenges, is crucial. This research contributes significantly to the literature on IoT adoption in healthcare, offering valuable insights of new knowledge that may be used as recommendations for policymakers, healthcare professionals, and researchers. The findings serve as a beacon for future endeavours aimed at harnessing the power of IoT for a healthier and more efficient healthcare system design in Saudi Arabia.76 0Item Restricted Enhancing Security Measures for Internet of Things (IoT) Devices in the Cyber Space(Saudi Digital Library, 2023-09-15) Alahmadi, Toufiq; Adda, MoThe expansion of Internet-connected devices and systems, commonly known as the Internet of Things (IoT), brings convenience but also raises cybersecurity threats. Insecure IoT devices are a weak point in a network's defence that hackers might use to acquire private user data and penetrate networks. However, improving protections remains challenging due to consumer knowledge gaps, cost limits, and usability difficulties with many existing methods. This dissertation examines the opportunities and challenges involved with enhancing security for consumer-grade IoT devices via the viewpoints and behaviours of end users.150 customers participated in an online survey both closed- and open-ended survey questions were used to determine their knowledge, opinions, and pain points about the security of IoT devices. The main areas of focus were risk perceptions, current practices, difficulties with execution, and views about responsibility. The findings showed that although consumers understand the significance of security best practices, they still want clear instructions and tools in order to consistently use them. The top challenges were managing many devices and a lack of technical knowledge. However, respondents also indicated that they would be open to adopting stronger measures.41 0Item Restricted IoT Smart Building System Development for Indoor Air Quality(2023-12-06) Almusaybih, Yazeed; Pozdniakov, KonstantinA system that reads PM2.5 and Co2 then react to the dangerous sensors levels to maintain the air quality indoor by opening either the window or the air conditioner based on the outdoor weather quality, is the aim of this project. Development of an IoT based Air quality system requires a group of investigations to fulfil all the aspects. System design illustrated the both the overall structural design of the system, and the hardware integration classifications. While some UML addressed, the focus on a behavioural model such as the activity model added value to the system testing plan, which it had an execution path based on this model to test the system. Integration between IoT architecture and software based on LAMP stack has brough a list of possible technical challenges, and research to be put in the plan. Further security implementation has been taken in account to minimise the risk of possible attack vectors, such as SQL Injection. Moreover, this security layer was the pavement to API development to serve both the dashboard and the MQTT broker event. With all the previous diverse of integration, system development has been achieved in steady steps, due to the management of agile mythology applied on the Trello tool. Likewise, code changes and updates has been handled by Github. Finally, plus all the inputs of hard work and determine to achieve the aim of this project, a fully reliable products in beta stage can be seen in the video demonstration.22 0Item Restricted Artificial Immune Systems for Detecting Unknown Malware in the IoT(Queen Mary University of London, 2023-01-27) Alrubayyi, Hadeel; Goteng, Gokop; Jaber, MonaWith the expansion of the digital world, the number of the Internet of Things (IoT) devices is evolving dramatically. IoT devices have limited computational power and small memory. Also, they are not part of traditional computer networks. Consequently, existing and often complex security methods are unsuitable for malware detection in IoT networks. This has become a significant concern in the advent of increasingly unpredictable and innovative cyber-attacks. In this context, artificial immune systems (AIS) have emerged as effective IoT malware detection mechanisms with low computational requirements. In this research, we present a critical analysis to highlight the limitations of the AIS state-of-the-art solutions and identify promising research directions. Next, we propose Negative-Positive-Selection (NPS) method, which is an AIS-based for malware detection. The NPS is suitable for IoT's computation restrictions and security challenges. The NPS performance is benchmarked against the state-of-the-art using multiple real-time datasets. The simulation results show a 21% improvement in malware detection and a 65% reduction in the number of detectors. Then, we examine AIS solutions' potential gains and limitations under realistic implementation scenarios. We design a framework to mimic real-life IoT systems. The objective is to evaluate the method's lightweight, fault tolerance, and detection performance with regard to the system constraints. We demonstrate that AIS solutions successfully detect unknown malware in the most challenging IoT environment in terms of memory capacity and processing power. Furthermore, the systemic results with different system architectures reveal the AIS solutions' ability to transfer learning between IoT devices. Transfer learning is a critical feature in the presence of highly constrained devices in the network. More importantly, we highlight that the simulation environment cannot be taken at face value. In reality, AIS malware detection accuracy for IoT systems is likely to be close to 10% worse than simulation results, as indicated by the study results.74 0