Journal of Technology and Systems

Global Positioning System Signal Verification through Correlation Function Distortion and Received Power Tracking

Moses Michael Meitivyeki — 2024-04-27

Purpose: This study proposes a significantly improved method for detecting, classifying, and isolating Global Navigation Satellite System (GNSS) signals using the relationship between the measured power and the distortion of the correlation function to achieve the signal verification required for Global Positioning System (GPS) civil applications such as safe civil aircraft navigation.

Methodology: The suggested approach uses power and distortion measurements in the received signal to identify it as jammed, multipath, spoofing, or no-interference. By adding an isolator scaling factor to the detector, the signal patterns will be induced with a unique temporary factor that will set it apart from the rest and make it possible to easily position each signal in its own zone. The detector divides the four signal types into distinct zones for verification.

Findings: The sufficient signal data is analyzed and the extensive simulation conducted indicates that about 94% detection accuracy is achieved which is relatively high.

Unique contribution to theory, practice and policy: This study is implemented through the development of relevant detection software tools with a user-friendly interface for GNSS signal detection, validation and analysis.

Risk Management in Agile Al/Ml Projects: Identifying and Mitigating Data and Model Risks

Ankur Tak — 2024-04-24

Purpose: This study addresses the crucial challenge of managing risks associated with data and models in Agile Artificial Intelligence (AI) and Machine Learning (ML) projects. It aims to develop a systematic framework for effective risk control utilizing agile methodologies.

Methodology: The research is grounded in an interpretivist approach and utilizes a deductive method. It constructs a comprehensive framework for identifying and mitigating risks, integrating risk management seamlessly into Agile processes for AI and ML development.

Findings: The study introduces four technological themes critical for risk mitigation: dynamic distribution of resources, model robustness, risk integration, and quality assessment of information. These themes provide actionable strategies for reducing risks throughout the Agile AI/ML development lifecycle, ensuring that risk assessment and mitigation are integral to project planning and execution.

Unique contribution to theory, practice, and policy: The study contributes to both theory and practice by offering a detailed, actionable framework for risk management in Agile AI/ML projects. It advocates for the adoption of adaptive technologies and tools, continuous stakeholder engagement, and adherence to ethical standards. Recommendations include validation of the framework through empirical research and ongoing longitudinal evaluations to adapt and refine risk management practices. This approach aims to enhance the reliability and efficiency of project outputs in dynamic environments, providing a significant foundation for policy development in technology project management.

Development of Digital Twins for Urban Water Systems

Siva Sathyanarayana Movva — 2024-04-27

Purpose: This paper provides an overview of the emerging concept of digital twins (DTs) for urban water systems (UWS), drawing from literature review, stakeholder interviews, and analysis of ongoing DT implementation at the utility company VCS Denmark (VCS).

Methodology: Within the realm of UWS, DTs are situated across various levels, including component, unit process/operation, hydraulic structure, treatment plant, system, city, and societal levels. A UWS DT is described as a structured virtual representation of the physical system's elements and dynamics, organized in a star-structure format with interconnected features linked by data connections conforming to open data standards.

Findings:This modular structure facilitates the breakdown of overall functionality into smaller units (features), fostering the emergence of microservices that communicate through data links, primarily facilitated by application programming interfaces (APIs). Integration with the physical system is achieved through simulation models and advanced analytics.

Unique Contribution to theory, practice and policy: The paper suggests distinguishing between living and prototyping DTs, where "living" DTs entail coupling real-time observations from a dynamic physical twin with a simulation model through data links, while prototyping DTs represent system scenarios without direct real-time observation coupling, often used for design or planning purposes. Recognizing the existence of different types of DTs enables the identification of value creation across utility organizations and beyond. Analysis of the DT workflow at VCS underscores the importance of multifunctionality, upgradability, and adaptability in supporting potential value creation throughout the utility company. This study clarifies essential DT terminology for UWS and outlines steps for DT creation by leveraging digital ecosystems (DEs) and adhering to open data standards.