Artificial Intelligence and Robotics Commons^™

The Virtual Wunderkammer: Integrating Neuroinclusive Design And Ai-Augmented Technologies For Immersive Museum Experiences, Piper Hutson, James Hutson

Faculty Scholarship

The Virtual Wunderkammer represents an innovative paradigm in museum exhibition design, integrating neuroinclusive principles with artificial intelligence (AI)-augmented technologies to foster immersive and cognitively accessible visitor experiences. Historically, the Wunderkammer, or "cabinet of curiosities," served as a precursor to modern museums, offering eclectic collections that stimulated intellectual curiosity and sensory engagement. The contemporary reimagining of this concept utilizes emerging technologies such as augmented reality (AR), virtual reality (VR), haptic feedback, and olfactory-enhanced digital environments to create personalized, adaptive museum experiences. This study explores the critical intersection of neuroaesthetics, cognitive science, and AI-driven interactivity in digital exhibitions, emphasizing their potential to …

Smart Highway Construction Site Monitoring Using Artificial Intelligence, Mehran Mazari, Yahaira Nava-Gonzalez, Ly Jacky N. Nhiayi, Mohamad H. Saleh

Mineta Transportation Institute

Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. …

Collaborative Ai: Oer Materials For Exploring Ai As A Partner Rather Than A Tool, David Smith

Open Educational Resources

The Collaborative AI Open Educational Resource (OER) explores how artificial intelligence can act as a creative and analytical collaborator rather than a tool. Centered on the Balanced Blended Space (BBS) framework and the philosophy of the Center for Holistic Integration (CHI), the OER includes curriculum materials, theoretical models, and live research environments. It offers an interesting approach to blending physical, virtual, and conceptual spaces through shared human–AI agency and invites ongoing participation in interdisciplinary meta-projects.

Real-Time Prediction Of Dynamical Systems Using A Hybrid Analog Computer: Network Traffic Modeling, Majd Zuhair Tahat

Doctoral Dissertations

As the number of online users grows exponentially, the number and severity of cyber threats escalate, urgently requiring advancements in real-time network modeling and response. Swiftly predicting and analyzing network traffic is crucial for effective network monitoring and control, preventing cyber breaches, and maintaining healthy network functionality. This research presents a novel approach to real-time modeling based on analyzing evolving properties and patterns in a dynamical network system using a hybrid analog-digital computer. An analog computer was utilized as a co-processor to compute differential equations that model the Transmission Control Protocol (TCP) window size. A comparative analysis was conducted between …

Learning Without Labels: A Self-Supervised Learning Approach For Anomaly Detection In Control Systmes, Barbara Gladney

Shelby Hall Graduate Research Forum Posters

Oil pipelines, water plant systems, and other critical infrastructure are managed and operated by industrial control systems (ICS). These systems safeguard the operations of critical infrastructures, requiring minimal disruption from cyberattacks or malfunctions. The use of anomaly detection methods in control systems (ICS) can reduce system interruptions. However, anomaly detection methods often require annotated data, which may not be available for the control system. Additionally, the datasets used for the control systems do not include sensor outputs and environmental data, resulting in a restricted view of the system. This research investigates how SSL models can be applied to different control …

Preserving Privacy In Senior Care At Home Monitoring Systems, Sam Russel, Ryan Benton, Amy Campbell, Scott Sittig

Shelby Hall Graduate Research Forum Posters

Many seniors prefer to live at home which necessitates research into the application of technologies to provide a safer environment with less caregiver resources. However, the application of home health care (HHC) monitoring for seniors is still in an evolutionary stage. Present HHC systems are produced by private companies with general regulatory guidelines lacking specific care of the elderly. As such, each company that produces such a system claims to have better safety, privacy, and security that their competitors. A pressing issues is devising and applying a general framework for the application of technologies that delivers safety while preserving privacy. …

Adversarial Attacks And Defense Methods In Robotic Systems, Thanh D. Le

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Why Ai’S Role In Advancing Sustainability Is Underestimated, Lipika Bhattacharya

CCX Research

AI has quietly, but powerfully, woven itself into the fabric of our everyday lives. Yet, AI's potential impact on creating a more sustainable world is undervalued. The author examined artificial intelligence's (AI) role in advancing sustainability. She outlined how AI can be applied in various domains such as agriculture, water management, industry, urban planning, and biodiversity conservation for transformative effects.

Mimic: Ai And Ar-Enhanced Multi-Modal, Immersive, Relative Instruction Comprehension, Dhanuja Wanniarachchi, Archan Misra

Research Collection School Of Computing and Information Systems

We present a multimodal instruction comprehension framework, called MImIC, that utilizes visual sensing (including LIDAR and 2D RGB sensing) & AI spatial reasoning capabilities to support more seamless and immersive interaction between humans and AI-driven situated assistive agents. MImIC's key new capability is to support disambiguation of a wider set of relative spatial references that users naturally employ while issuing spatially-situated instructions. To support enhanced visual grounding via a combination of both fully-qualified and relative attribute references, MImIC uses (a) a fine-tuned transformer-based language translation DNN to accurately convert natural verbal commands into a structured set of machine understandable constraints …

Performing Requirements Specification And Analysis Through Open Generative Pre-Trained Transformers, Harvey J. Hurst

Theses and Dissertations

Every acquisition program begins with a requirement, and for those programs to succeed, robust requirements engineering (RE) must be implemented. RE encompasses eliciting, analyzing, specifying, and validating requirements—a critical process throughout a program's lifecycle. Despite its importance, RE faces challenges such as scope creep, ambiguity, redundancy, and inadequate automation support, often exacerbated by reliance on historical data. To address these issues, this thesis leverages advancements in Generative Technology, particularly large language models (LLMs) such as Generative Pre-Trained Transformers (GPTs). This research developed two GPT-based tools: the Single Requirement Analysis Tool and the Set of Requirements Analysis Tool. These tools were …

Early-Phase Cost Estimation For Department Of Defense Construction Projects Via Artificial Neural Networks: Implications And Policy Recommendations For Artificial Intelligence Integration, Kobe T. Thompson

Theses and Dissertations

The Department of Defense lost over 500 million dollars between 2016 and 2024, partially due to poor early cost estimates resulting in cost overruns. practice for cost estimation relied on parametric techniques that incorporate historical data, subject matter experts in cost estimating, and predictive software applications. The main motivation for this study was to assess the viability of artificial neural networks as a means of providing a more accurate cost estimate in the early design phases of a construction project. The dataset initially contained approximately 48,000 data points from a database of various Air Force projects, including maintenance, repair, minor …

Learning: Human Versus Machine, Sanjay Sarma

Asian Management Insights

Outdated education paradigms must be revamped to reclaim the all-important human quality: agency.

Sanjay Sarma, CEO, President, and Dean of the Asia School of Business, Kuala Lumpur, Malaysia and the Fred Fort Flowers (1941) and Daniel Fort Flowers (1941) Professor in Mechanical Engineering at the Massachusetts Institute of Technology (MIT), shares insights on the artificial intelligence (AI)-agency revolution and how the human brain works.

The Ethics Of Ai Nudges: How Ai Influences Decision-Making, Seema Chokshi

Asian Management Insights

And why decision-makers should care about it. Artificial intelligence (AI) systems, through mechanisms like nudges and choice architecture, actively, yet often subtly, shape human decision-making in everyday life and professional settings. AI systems can prioritise profit or efficiency at the expense of human agency, fairness, and well-being, highlighting the need to balance AI’s capabilities with ethical considerations. The EU AI Act is a landmark framework designed to curb manipulative AI practices, emphasising the protection of human autonomy and accountability in decision-making.

Abolition By Algorithm, Peter N. Salib

Michigan Law Review

In one sense, America’s newest abolitionist movement—advocating the elimination of policing and prison—has been a success. Following the 2020 Black Lives Matter protests, a small group of self-described radicals convinced a wide swath of ordinary liberals to accept a sweeping claim: Mere reforms cannot meaningfully reduce prison and policing’s serious harms. Only elimination can. On the other hand, abolitionists have failed to secure lasting policy change. The difficulty is crime. In 2021, following a nationwide uptick in homicides, liberal support for abolitionist proposals collapsed. Despite being newly “abolition curious,” left-leaning voters consistently rejected concrete abolitionist policies. Faced with the difficult …

Reimagining Education: Keeping The Human In The Loop, Pradeep Varakantham, Sidney Tio

Asian Management Insights

How educators can work with generative artificial intelligence models to improve learning. Artificial intelligence (AI) helps break the mould of one-size-fits-all education by creating personalised learning paths that adapt to each student’s pace and style. By combining human expertise with AI capabilities, educators can create learning experiences that are both structured and flexible, thus getting the best of both worlds. While promising, AI used in educational contexts must carefully navigate privacy concerns, ensure fairness across all student groups, and support appropriate learning progression.

Understanding Individual Agent Importance In Multi-Agent System Via Counterfactual Reasoning, Jianming Chen, Yawen Wang, Junjie Wang, Xiaofei Xie, Jun Hu, Qing Wang, Fanjiang Xu

Research Collection School Of Computing and Information Systems

Explaining multi-agent systems (MAS) is urgent as these systems become increasingly prevalent in various applications. Previous work has provided explanations for the actions or states of agents, yet falls short in understanding the black-boxed agent's importance within a MAS and the overall team strategy. To bridge this gap, we propose EMAI, a novel agent-level explanation approach that evaluates the individual agent's importance. Inspired by counterfactual reasoning, a larger change in reward caused by the randomized action of agent indicates its higher importance. We model it as a MARL problem to capture interactions across agents. Utilizing counterfactual reasoning, EMAI learns the …

Exploring Intelligent Manufacturing: How Artificial Intelligence Affects Productivity And Labor Demand At The Enterprise Level, Jie Gu

Dissertations and Theses Collection (Open Access)

Manufacturing is a cornerstone of national economic health and social stability, yet it faces challenges such as declining profits, rising labor costs, and an aging workforce. In China, the manufacturing sector is undergoing a critical transformation, driven by technological advancements like artificial intelligence (AI) and the push for intelligent manufacturing. This study explores how AI revitalizes the manufacturing sector by enhancing enterprise productivity and reshaping labor demand, with a focus on quality inspection processes. Using a leading bearing factory as a case study, the research employs econometric models, A/B testing, and interviews to quantify AI’s impact on production efficiency, costs, …

Advances In Natural Fiber Polymer And Pla Composites Through Artificial Intelligence And Machine Learning Integration, Md Helal Uddin, Mohammed Huzaifa Mulla, Tarek Abedin, Abreeza Manap, Boon Kar Yap, Reji Kumar Rajamony, Kiran Shahapurkar, T. M.Yunus Khan, Manzoore Elahi M. Soudagar, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Natural Fibre Polymer (NFP) and Polylactic Acid (PLA) composites have received a lot of interest in a variety of sectors because they are environmentally friendly, renewable, and sustainable. Over the last decade, researchers have investigated the aspects of NFP/PLA composite development and optimization for a wide range of applications, including packaging materials, automotive components, construction materials, textile and apparel, biomedical devices, agricultural and horticultural applications, electronics, and consumer electronics. Furthermore, using Artificial Intelligence (AI) and Machine Learning (ML) methodologies has increased these polymer materials and associated technologies in their search for new potential ways to further progress in NFP and …

Identifying Human Factor Causes Of Remotely Piloted Aircraft System Safety Occurrences In Australia, John Murray, Steven Richardson, Keith Joiner, Graham Wild

Research outputs 2022 to 2026

Remotely piloted aircraft are a fast-emerging sector of the aviation industry. Although technical failures have been the largest cause of accident occurrences for Remotely Piloted Aircraft Systems (RPASs), if they are to follow the path of conventionally crewed aviation, Human Factors (HFs) will increasingly contribute to accidents as the technology of RPASs improves. Examining an RPAS accident database from 2008–2019 for HF-caused accidents and coding to the Human Factors Analysis and Classification System (HFACS) taxonomy, an exploration of RPAS HFs is carried out and the predominant HF issues for RPAS pilots identified. The majority of HF accidents were coded to …