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Abstract—Periods of unique economic distress such as the COVID-19 pandemic can be quite difficult for small businesses. Challenges acquiring the supplies necessary to adhere to safety regulations created in the wake of such events can introduce stress on these businesses. This is further exacerbated when supply chains have slowed down, leading to global shortages from most large suppliers. This paper proposes a platform to aid such businesses in procuring COVID-19 related supplies such as Personal Protective Equipment (PPE) from one another, leveraging advanced data acquisition, integration, and Natural Language Processing (NLP) methods. With the pandemic end in sight, the platform described in this paper can be reused for other emergencies such as hurricanes, floods, among others. The proposed platform supports business transactions within a Buyer’s Club (BC), keyword-based sourcing of new businesses to join the platform, and matching products to relevant regulations using greater-than-word length encoding, helping businesses comply with the ever-changing regulatory landscape. Index Terms—COVID-19, Disaster, Natural Language Processing, Data Acquisition, Data Retrieval, User Interfaces 

Immersive Learning Environments (ILEs) developed in Virtual and Augmented Reality (VR/AR) are a novel pro- fessional training platform. An ILE can facilitate an Adaptive Learning System (ALS), which has proven beneficial to the learning process. However, there is no existing AI-ready ILE that facilitates collecting multimedia multimodal data from the environment and users for training AI models, nor allows for the learning contents and complex learning process to be dynamically adapted by an ALS. This paper proposes a novel multimedia system in VR/AR to dynamically build ILEs for a wide range of use-cases, based on a description language for the generalizable ILE structure. It will detail users’ paths and conditions for completing learning activities, and a content adaptation algorithm to update the ILE at runtime. Human and AI systems can customize the environment based on user learning metrics. Results show that this framework is efficient and low- overhead, suggesting a path to simplifying and democratizing the ILE development without introducing bloat. Index Terms—virtual reality, augmented reality, content generation, immersive learning, 3D environments 

Advancements in Artificial Intelligence (AI), Information Technology, Augmented Reality (AR) and Virtual Reality (VR), and Robotic Automation is transforming jobs in the Architecture, Engineering and Construction (AEC) industries. However, it is also expected that these technologies will lead to job displacement, alter skill profiles for existing jobs, and change how people work. Therefore, preparing the workforce for an economy defined by these technologies is imperative. This ongoing research focuses on developing an immersive learning training curriculum to prepare the future workforce of the building industry. In this paper we are demonstrating a prototype of a mobile AR application to deliver lessons for training in robotic automation for construction industry workers. The application allows a user to interact with a virtual robot manipulator to learn its basic operations. The goal is to evaluate the effectiveness of the AR application by gauging participants' performance using pre and post surveys.