Automated building plan approval system
Our client is the partner company of local building authorities, which belong to German Federal municipalities.
An AI-based solution to manage the health of the car fleet and convert vehicle data into valuable insights to predict and prevent failures. It allows to estimate of the Remaining Useful Life (RUL) of components and provides early detection of malfunctions and performance degradation.
Modern vehicles are costly to fix and maintain. For example, warranty claims, maintenance, and vehicle downtime costs affect the car fleet and influence customer satisfaction. To identify and settle these costs, vehicle health management systems, or VHM systems, use sensors and software to monitor vehicle performance, detect and predict problems, and recommend needed maintenance.
Today, most VHM systems rely on diagnostic trouble codes. These codes identify an issue only after it has already occurred. Besides, they provide a piece of limited information only. It adds extra work for technicians to identify the cause of the problem.
Modern vehicles use telematics to send diagnostic trouble codes and additional information to the cloud. Still, telematics data is too general and limited. As an effective alternative to the current solutions, our client created an AI-powered solution to monitor the health of vehicles effectively, processing thousands of different signals in real-time.
One of the project’s main goals was to create a possibility for users to compare and evaluate different anomaly detection models on unsupervised data.
Modern vehicles are complex machines that are costly to fix and maintain. For instance, warranty claims, recalls, maintenance, and vehicle downtime costs reduce commercial fleet and customer satisfaction. To face and address them, vehicle health management systems, or VHM systems, use sensors and software to monitor vehicle performance, detect and predict problems, and recommend needed maintenance.
Using Deep Learning technologies, the client’s solution can determine the vehicle's health conditions and then flag any deviations from the expected behavior. This VHM solution can also predict when a vehicle's health condition could lead to failure and help identify the cause of the problem.
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As you know, Data Scientists analyze a massive amount of data for different actionable insights on a project. Working on the VHM system, I have tasks to identify the data-analytics problems that offer the best opportunities, collect large sets of structured and unstructured data from disparate sources, and analyze and interpret the data to discover solutions and options. What motivates me is working on a valuable product and using my skills and expertise to improve the client's initial solution.
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