The LAB4DTE innovation lab supports the prototypical implementation and testing of digital innovations and solutions in the areas of Business Intelligence & Machine Learning, Internet of Things & Mobile Services, 3D Sensors, Cloud Computing & Distributed Architectures, as well as Automation & Robotics. The basic approach is to provide suitable hardware and software frameworks that allow prototypical implementation and demonstration of innovative solutions and product ideas. For this purpose, the LAB4DTE builds on already existing hardware and software equipment of the RWU and extends and supplements it in order to achieve the greatest possible degree of flexibility and coverage of different solution approaches and techniques.
In addition, LAB4DTE supports students and potential founders in the implementation of their ideas with specific know-how in the above topics. The LAB4DTE is supported by the Institute for Digital Transformation, which covers all of the above topics and relevant application areas such as industry & commerce, people & leisure (especially tourism) and healthcare & social work.
3D cameras and 3D scanners are key technologies in new markets in the fields of machine vision, autonomous navigation, and robotics and automation technology.
In addition, 3D digitalization forms the basis for innovative business models in areas where the capture of complex three-dimensional geometries is required, such as 3D scanning of individual body features for optimal fit in the fashion and sports sector and body scanning with subsequent 3D printing of detailed sculptures.
The goal of the 3D sensor technology section within LAB4DTE is to collect and generate three-dimensional data of complex geometries, especially of humans and animals. These 3D data are generated by 3D scanners, which vary depending on the requirements in terms of physical principle, resolution, detection range and cost. The 3D data can be used to create customized objects adapted to bodies, such as clothes, shoes, saddles for horses, and so on. However, the advantages and disadvantages as well as the differences between the variety of scanner technologies and the processing of 3D data are usually understood only by experts. The LAB4DTE would like to provide knowledge transfer through lectures and trainings, as well as to give interested founders the opportunity to deal with the different 3D technologies - their ideas should be practically tested and further developed.
The following two use cases are examples of the possible applications of 3D technologies in LAB4DTE and demonstrate feasible innovations and business ideas:
Shoe selection for the sports and outdoor sector of the future.
This use case consists of the following sub-steps for the shoe selection:
• Step 1 Foot scanning: the customer's feet are scanned three-dimensionally.
• Step 2 Matching: In order to find the optimal shoe for the digitized feet, the shoe geometries must also be available as digital data.
If the shoe model data is not available the inner shoe geometries must be recorded.
Shoe matching ensures that the right shoe is found for the foot.
This use case involves the creation of detailed 3D sculptures of living people and animals and consists of the following sub-steps:
• Step 1: body scanning: the person, the pet is scanned three-dimensionally.
• Step 2: the 3D data is prepared for the subsequent 3D printing process.
• Step 3: 3D printing of the digitalized person/animal.
AI & Robotics
LEARNING INTELLIGENT SERVICE ROBOTS
Service robots (SR) are specifically developed to support humans in everyday life. For localization and object recognition, good practicable algorithms exist today that are already superior to humans for certain tasks. In the last decade, AI has achieved great success, especially in object recognition using Deep Learning. Other tasks, such as grasping objects in arbitrary situations, are still major challenges for research and development and offer good entry opportunities for innovative founders.
Today, SRs are already partially capable of learning. This means that the SR no longer needs to be reprogrammed for certain tasks, but can learn from a human trainer. Using learning by demonstration, the robot can be trained by a human demonstrating the task. As a result, SRs can not only perform the tasks pre-installed at the time of purchase, but also learn new tasks in practice.
PREVIOUS ACTIVITIES IN THIS AREA
The Institute for Artificial Intelligence (IKI), which is associated with IDW, has been conducting successful research in the field of machine learning and intelligent autonomous systems for years. In addition to the "Marvin" and "Kate" platforms developed in-house as part of various research projects, a commercial platform called "Kurt" (Tiago Steel Edition Manufacturer: PAL Robotics) has also been available since the beginning of 2019. The IKI's service robotics lab is state of the art and offers workstations specifically designed for the development of SR applications, in addition to various platforms, robot arms and sensor technology with a total value of over €300,000.
In addition to supporting founders in the field of service robotics, a model scenario for LAB4DTE events is to be developed in close cooperation with the various active research groups at the IKI in order to motivate potential founders. This networking of active cutting-edge research and start-up culture creates sustainable added value on both sides.
SR can be used in any application due to their general orientation. Some use cases are outlined below as examples:
• Gastronomy: SR delivers drinks / takes orders
• Hotel industry: SR takes over parts of the room service / serves as contact person for guests
• Tourism: SR acts as a tour guide with local knowledge / encourages group activities / games
• Warehouse / Production: SR assists people in production by fetching / bringing products / tools, etc.
• Logistics: SR delivers packages / acts as courier between companies / private persons
Business Inteligence & Machine Learning
Gartner (see Mike Walker, “2018 Hype Cycles, Riding the Innovation Wave.”) identifies the field of artificial intelligence (or machine learning) as one of the most disruptive technologies of 2018. Especially the area of Deep Neural Networks ranks high in the 2018 Hype Cycle for Emerging Technologies. This technology is especially suitable for recognizing patterns in images, texts, voice recordings or videos and is also a driver of many other IDW topics such as Smart Factory etc. An important aspect of artificial intelligence (AI) is its interdisciplinarity. For example, AI is used in medicine, industry or leisure. The variety of resulting application domains offers a wide range of decision-making possibilities for future company founders dealing with this topic. In this context, the setup of a machine learning or rather extended business intelligence (BI) division within the LAB4DTE is considered to be especially important. The disruptive character of AI together with its as yet unexploited potential and the multitude of possible fields of application holds unique opportunities for future start-ups.
Previous activities in this area
For several years now, the information systems program at RWU has been working intensively on creating a library of methods and data sets, especially in the field of business intelligence, data mining and machine learning. For example, student papers in this area are continuously processed and made available for future research. Following the same principle, data is collected from various platforms at regular intervals, with the goal of generating an extensive body of information that can be used to validate ideas or generate new knowledge. In addition to the library of methods, recommended actions and datasets, a BI server is in use, which is equipped with many important frameworks and development environments.
This approach will be consistently pursued and expanded. The existing offers are to be successively broadened and so transformed into an incubator of innovative ideas. On the one hand, this will provide students with practical use cases and demonstrate the possibilities of the field at an early stage of their studies. On the other hand, the BI section of the LAB4DTE will enable the prototypical implementation of potential start-up ideas.
A concrete use case that can be implemented with the listed hardware and software is, for example, the development of a Deep Learning application for skin cancer diagnosis. By means of the provided Deep Learning hardware and software environment, available data sets as well as provided know-how, an immediate prototypical implementation and testing of the business idea is possible, especially regarding the necessary precision and reliability of the cancer diagnosis or the cost efficiency due to the required processing power.
INTERNET OF THINGS & MOBILE APPLICATION
The Internet of Things (IoT) describes the networking of objects with the Internet. These communicate independently with each other via a network or the Internet. IoT devices can range from very small devices (such as remote-controlled LED lamps, thermostats, smartwatches) to large devices in smart factories that operate autonomously and communicate with each other.
Mobile applications are also indispensable these days. Many people use them on their smartphones every day, for example to check train connections, check e-mails, or in the business sector to interact with and control IoT systems.
PREVIOUS ACTIVITIES IN THIS AREA
At the RWU, IoT devices and mobile applications are used in various areas. Student projects in the area of mobile application development as well as projects with embedded systems and corresponding applications for control are regularly implemented. Setup of an IoT lab has begun and a basic set of hardware and associated software frameworks is in place.
In order to enable potential founders to implement innovative ideas in the field of IoT or mobile applications, an IoT section will be set up in LAB4DTE and equipped with the necessary hardware. This includes, for example, beginner-friendly hardware frameworks for the playful implementation and testing of typical application scenarios, such as Lego Mindstorms or Fischertechnik IoT. These frameworks can be used to playfully learn and demonstrate how to use IoT devices. For founders or students already experienced in the field of IoT, a comprehensive selection of relevant microcontrollers and sensors is purchased (e.g. various Arduino microcontrollers, thermal or optical sensors, ...). This enables the prototypical implementation of innovative IoT application scenarios directly in the lab, e.g. camera- or voice-controlled IoT devices (smart assistants) or newly developed gadgets used to support or automate simple household tasks (e.g. an automatic watering system for potted plants).
The development of mobile applications or applications for controlling the IoT devices is enabled in LAB4DTE by provided development devices. These are iOS devices, such as iMacs, Macbooks, iPads and iPhones, and Windows or Android devices (Windows computers, Android smartphones and Android tablets). This removes limitations in the choice of the system that founders want to develop on and allows easy testing at existing end devices. The use of 3D printers gives founders the chance to design and manufacture parts or cases needed for their prototypes themselves. These can be simple hardware that will later be used in the product, or complex structures for the design of the hardware. This is especially important in the early stages of a project, because it allows the usability to be tested from the beginning, but also to make initial assessments regarding usability and design.
A use case based on a combination of IoT device and mobile application which can be used in the social sector could be, for example, a device for monitoring patients who are being treated at home. In this case, an IoT device could take over the vital function monitoring of the patient and forward this information to the treating physician in regular time intervals. The physician can also be informed directly if the patient's vital signs change abruptly (e.g., when a patient falls) or if they behave irregularly over a longer period of time. Various technical solutions for the application can be implemented and tested using sensors, cameras and mobile devices.
Contact & People
Contact & People
General contact details
RWU Hochschule Ravensburg-Weingarten
University of Applied Sciences
LAB4DTE Innovation Lab
Postfach 30 22
D 88216 Weingarten