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Discover a selection of our IoT & data science clients and projects
Record Evolution Platform
Pilot Project with Continental AG
Optimizing brake systems with the Record Evolution Platform
Together with the HBS R&D division at Continental, we developed a pilot project for identifying brake squeal noises using Big Data and AI approaches on IoT data collected from test vehicles.
Using the Record Evolution platform for end-to-end IoT development, we implemented IoT data collection strategies, Big Data analytics & AI solutions in mobile IoT scenarios. The goal was to improve Noise, Vibration and Harshness (NVH) measurements to better evaluate the circumstances under which brake squeal noise occurs.
We developed an end-to-end process starting with data collection from test vehicles, transferring the data to an on-premises cloud environment, data processing in the cloud, and the creation of a database of structured and harmonized high-quality data. We then collaborated on the creation of diverse analytical insights into the data and created a custom AI algorithm for our edge devices to classify NVH events with high accuracy in near real-time.
To collect raw IoT data, we developed a measurement device based on Raspberry Pi and enhanced it with professional measuring electronics. Devices were installed in multiple test vehicles and were connected to the platform. With the help of the Record Evolution Reflasher, platform users can now easily add new vehicles to their test fleet with just a few clicks and so enrich the existing data pool.
The IoT apps developed on the Record Evolution Platform send data directly to the Continental cloud where the platform is installed on-premises. From there, the platform securely and reliably manages all IoT devices that operate outside of the company network.
The outcome: Using our collaborative platform for IoT and data science, we have built a comprehensive system for IoT data collection and analysis. This system can serve as a foundation for the development of multiple use cases. For example, we can develop apps for NVH detection and real-time NVH prediction based on the identification of patterns that arise prior to an NVH event.
Modern Industrial UI for Optical Metrology
User-centric UI for the intuitive and seamless operation of optical distance and thickness measurements
Working with end users, we developed a new customer-centric UI that is so simple and intuitive that you do not need to read any operations manual.
Precitec manufactures sensors for optical distance and thickness measurement. A sensor consists of an optical probe head and a spectrometer. Our goal was to develop an elegant, easy-to-use, and human-centered user interface that allows users to configure the spectrometer fast and visualise the measurement data in an appealing and simple manner.
Record Evolution used state-of-the-art UX paradigms and the latest web technologies to develop a new modern UI.
With the help of Design Thinking and the definition of dedicated end-user personas, we created three user journeys for different kinds of usage of the applications. Depending on the expert level, the user can see less or more complex configuration options; the expert mode with a command-line interface allows for full control over the device. The setup and configuration process of new measurement devices was simplified with guided wizards and preset smart values.
This user-friendly software helps customers to distribute “ready-to-use” devices that the end user can use directly without further training, which reduces support time. The attractive clean look helps sales representatives during demonstrations of the devices to customers and during trade shows.
Networked Mobility: New Approaches to Human-machine Interaction in Industrial UI
An integrated cockpit display for a new driving experience in future mobility scenarios
Collaborating with different departments at Continental, we co-developed a cockpit demonstrator. The interactive display solution covering the entire width of a vehicle’s cockpit offers an experience of full connectivity, paving the way towards safer and stress-free driving.
Record Evolution worked on the development of a human-machine interface (HMI) using state-of-the-art connectivity technologies and modern web architectures. We established real-time connections between a multitude of functional components in the car such as self-shading windows, an AI assistant, door sensors, interior lighting, autonomous driving controls and more.
All these components were gesture-controlled by mobile phone or tablet as well as a large touch-sensitive dashboard HMI containing apps for many different use cases.
Our developers created a framework for the integration of various apps and implemented a video player, a music application, navigation, email and weather services in addition to the essential driving controls such as rear-view mirror video, speedometer and fuel/fuel gauge. The implemented connectivity solutions and modular app structure contributed to the display’s unique look & feel.
The display demonstrator operates in two modes: In automated driving mode, the display extends to its fullest capacity to serve as a customizable infotainment hub for both driver and passengers. In manual driving mode, half of the screen disappears into the cockpit and all apps smoothly adapt to the new screen format so that the driver can focus on the driving experience.
The integrated cockpit display was one of Continental’s highlight exhibits during the Frankfurt Motor Show IAA 2019, allowing visitors to board the cockpit and freely interact with the innovative solution within a driving simulator.
Big Data & IoT
Big Data & IoT in Product Development
Noise detection for the determination of interference signals
In this project with a large automotive supplier, conclusions about the causes of certain product properties were to be determined on the basis of large quantities of measurement data using statistical methods.
One focus was the automated and reliable detection of specific noises (vibrations) from sound tracks/vibration pickups, which had a large number of interfering signals.
Another focus was the root cause analysis and prediction of these noises based on the additionally detected more than 40 sensor tracks. In order to provide the necessary data volumes, this project developed and implemented a prototypical IoT architecture for the collection of real-time sensor data from vehicles in a cloud-based data store. Only open-source technologies were used.
A Platform for Risk Analysis
Integration of source data systems for efficient evaluation
In one of our projects, we set up a comprehensive risk analysis platform for approximately 1,100 German Volksbanken and Raiffeisenbanken in parcIT GmbH.
Several source data systems were integrated and cleaned up for efficient evaluation. In addition, various classes of analyses were prepared, including calibration and selectivity of classification procedures, default correlation and migration analyses.
We have successfully used open-source software and customized hardware as our technical basis.
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