Computer software for visualization and implementation of engineering analysis of structure usingArtificial Intelligence & Machine Learning Application

Computer software for visualization and implementation of engineering analysis of structure against applied loads, strain, cracks, tilt measurement, and corrosion Our company is a structure health monitoring company that provides services to many different types of structure via health monitoring systems wirelessly sensors installed,analyzed and reported to the stakeholders. We want to leverage the latest technology in the market to create advantage for our stakeholders so they can take decisions real time with real time data. Applications of this technology include recommendation algorithms, and predictive analytics like lifetime value and classifications of the infrasturcture data.  About the project : It is an web app computer software for visualization and implementation of engineering analysis of structure against applied loads, strain, cracks, tilt measurement, and corrosion. The tool allows the client to visually understand the measuring variables causing any long-term or short-term effect on the structural integrity. The downloadable user-friendly reports allows the stakeholders to make informed decisions based on the real-time data input from sensors being directed on the portal.  We would like to collaborate with students in their Grad year, Master or PhD students to apply the latest engineering research in their field of experience computer systems, civil engineering or electrical engineering. They may also add their experience using artificial intelligence (AI) and machine learning (ML) techniques to our existing dataset. Students could also develop an AI / ML model related to  engineering analysis of structure against applied loads, strain, cracks, tilt measurement, and corrosion The Grad year, Master or PhD student will get to work with real-time problems and real-time data to understand the behaviour of structures. They will also learn and understand the practical use and delivery methods of the data for the stakeholders. The student will also get to work with 5-6 different types of sensor data and help classify and filtrate for the most optimal visualization of the data and its representation to the stakeholder/client. This will involve several different steps for the students, including: Conducting background research on our existing products and the dataset. Analyzing our current dataset. Researching the latest AI / ML techniques and how they could be applied to our data. Developing an AI / ML model that provides unique outcomes or insights into our data.(Optional )  Providing multiple solutions that can be applied to solve the same problem. Working alongside a team consisting of - a product manager, and computer software/developers.  Get access to and first-hand experience in different types of structural sensor data  Consider introducing different software or analytical methods that can be added to the platform. Classification and filtration of infrastructure data coming from 6-7 different type of sensors