Prompt Engineering: Decision Support Tool
Developed AI-Powered Decision Support Tool that leverages a combination of technologies to enhance the U.S. Army handbooks, planning publications, and decision support tools. The tool incorporates a specialized data analysis component for generating insights from raw data, which are then presented in an easy-to-understand manner using a large language model like GPT-3 or 4. The tool also features a user-friendly interface, developed using established UX/UI design principles, to ensure accessibility and ease of use for relevant personnel. Hosted on a secure, web-based platform, the tool is designed to be easily accessible and compatible with existing systems. To address potential obstacles such as data quality, user acceptance, and security, the solution includes careful planning, regular testing and review, and ongoing training and support for users. This comprehensive tool aims to improve the creation, accessibility, and effectiveness of military engineering resources and tools, thereby supporting the demonstration of developed tools and conducting protection assessments of facilities.
Segway Robotics: Artificial Intelligence meets Segway
Remote monitoring for aging in place is very important as many elderly live alone at home. Many of them have chronic conditions that need to be managed. CMAT intends to use the Segway Robotic platform to improve the quality of care, reduce social economic costs, and reassure family members enabled by:
Directly collect healthcare information by establishing connections between healthcare related sensors and the robot; Assess the elderly’s health condition automatically and regularly
Provide reminder services for drug compliance and preventive interventions
Generate comprehensive and timely health report as a part of total health management solution with combined inputs of at home data and in-hospital data.
Live video conferencing with doctors caretakers etc
Automated reordering of medication
Machine Learning for Master Data Governance
The rise of Machine Learning (ML) has the potential to dramatically impact methodologies for Data Governance. Part of the standardization processes, specifically data matching, could be automated by making a Machine Learning model ‘learn’ and predict the matches routinely. ML models can start learning from the new data that is being submitted for standardization. The more data supplied to the model, the better the ML algorithm can perform and deliver accurate results. Therefore, ML is more scalable compared to traditional approaches. CMAT is developing machine learning models to work with SAP master data objects. Removing the human in the logic during the creation and sustainment of master data can help with the quality of information used in the ERP systems and reduce data errors in the enterprise. Data is an asset and should be treated as such to support the enterprise.
NFC Ring is a Wearable Technology. Near Field Communication (NFC) is a set of short-range wireless technologies, typically requiring a distance of 4cm or less to initiate a connection. NFC allows you to share small amounts of information between an NFC tag and mobile device with an NFC reader. We are experimenting with new ways to use this technology from password storage, to unlocking doors, to user authentication, to paying for items at retail stores. As CM Advanced Technologies continues to explore Wearable Technologies we hope to develop new solutions using this technology to make everyday life simpler.