Internet-of-Things sample application: Connected pinball machine

Internet-of-Things sample application: Connected pinball machine

Internet-of-Things sample application: Connected pinball machine

Expert: Michael Scharpf

Industry: Other

Area: Marketing & Sales

A pinball machine from the 80s becomes a networked high-tech device: Find out how our Connected Pinball became a unique example project thanks to the Internet of Things and Machine Learning.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

In our internal project, we had a special challenge: to network an old, ur-analogue product, a pinball machine from 1987, with modern technology and thus make the concept of the Internet of Things (IoT) tangible. The goal was to collect data and develop predictive models for the game.

[Solution]

To overcome the challenge, we opted for a solution based on the use of Raspberry Pis, camera and machine learning algorithms. By using two Raspberry Pis, the pinball machine could be networked with various sensors and actuators to collect data in real time. A camera was added to capture unstructured image data showing the current game state. Machine learning was then used to develop predictive models and create customised D3 visualisations to analyse and display game play.

[Result]

The result was impressive: the game on the pinball machine was visualised in real time on two monitors and a pattern recognition system identified the current score based on the recorded image data. This gave the team a new opportunity to explore the Internet of Things with modern technology and to apply data analysis methods. The project illustrates how artificial intelligence and machine learning can be used to develop innovative applications even on supposedly old-fashioned devices.

To implement the project, we used Python as the programming language and TensorFlow as the machine learning framework. The combination of these technologies allowed us to effectively process the pinball machine data and develop predictive models.

Overall, the project shows how innovative technologies such as IoT and Artificial Intelligence can be used to open up new possibilities for data analysis and support companies in their growth.

This example shows how the concept of the Internet of Things can be made tangible through collaboration with our company. The combination of Raspberry Pis, Machine Learning algorithms and D3 visualisations allowed us to develop predictive models and collect data in real time. The result is an innovative application that shows how Artificial Intelligence and Machine Learning can be used on old devices like a pinball machine.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

Visualisation of real estate in a GeoMap application

Visualisation of real estate in a GeoMap application

Visualisation of real estate in a GeoMap application

Expert: Linh Nguyen

Industry: Other

Area: Finance & Controlling

Experience your real estate in a new dimension: Discover the advantages of visualising real estate in our innovative GeoMap application.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

A large real estate company had a challenge in analysing locations and key figures of their properties. The process was manual and time-consuming as the data was only available in reporting and no comparative analysis could be done. In addition, the data was only available on a limited mobile basis, which affected the efficiency of the real estate agents.

[Solution]

Our company provided a solution to this challenge by implementing geodata in SAP BO. All information and key figures relevant for a property were displayed on the map and there was the possibility to filter according to different criteria. The mobile version of the tool included GeoMaps, which enabled an optimal display of the data on mobile devices.

Our team used their expertise in data analytics and artificial intelligence to develop a solution tailored to the client's needs. We integrated the data into SAP BO to enable seamless interaction between the various metrics and the map. This allowed the real estate agents to quickly and easily analyse the data and make decisions based on data.

[Result]

The interactive GeoMap application for iPad that our company developed provided real estate agents with an easy and quick way to access key metrics associated with the real estate properties under management. Our solution significantly increased the efficiency and accuracy of data analysis and helped real estate agents make more informed decisions.

Thanks to the solution we developed, the company was able to carry out comparative analyses, which contributed to improved decision-making. The data was available on mobile, which facilitated the work of the real estate agents and increased the efficiency of the company.

By implementing the interactive GeoMap application, the company was able to achieve higher customer satisfaction and increase its turnover. Our solution helped the company remain competitive and expand its market presence.

In addition to the benefits already mentioned, it is important to mention that the visualisation of the data in the interactive GeoMap app is very appealing and easy to understand. The presentation of property locations and key figures on the map provides a quick overview of the most important information, which facilitates decision-making.

As experts in data analytics and artificial intelligence, we always strive to provide our clients with innovative and customised solutions. We believe we can help businesses make the most of their data and make informed decisions. If you are looking for a similar solution, feel free to contact us to find out how we can support you.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Linh Nguyen - Key Account Manager

Your expert

Linh Nguyen | Principal Key Account Manager | Alexander Thamm GmbH

Customer journey analysis and visualisation

Customer journey analysis and visualisation

Customer journey analysis and visualisation

Expert: Michael Scharpf

Industry: Other

Area: Marketing & Sales

Experience the difference in your customer journey. Use our customer journey analysis and visualisation for optimal data evaluation.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

Our telecommunications client had difficulties in identifying user journeys and sources of error in the registration process. It was also important for him to calculate and visualise key figures from the registration process. The client needed a comprehensive data analysis tool that could help them optimise the registration process and carry out future projects independently.

[Solution]

We provided the client with a comprehensive solution by developing a data model for extracting the log data from the Hadoop infrastructure. We used Hive to implement the ETL process. We also mapped out the metrics and user journeys, and conducted pair programming as a team with a member of the client's staff. Furthermore, we coached one of the client's employees during the data science project so that he can carry out similar projects independently in the future.

[Result]

The result was a Tableau dashboard that visualises the key figures and user journeys and is available for detailed analysis. The client was able to optimise their customer journey analysis and better plan future projects. By training the employee, the client was also able to independently carry out similar projects and gain valuable insights from their data. The project was a complete success and helped our client to take their business to the next level.

As data analytics experts, we are proud to have helped our client successfully meet their data analytics requirements. We specialise in the implementation of data analysis projects and rely on state-of-the-art technologies such as Hadoop, Hive and Tableau. If you too would like to implement a successful customer journey analysis, don't hesitate to choose us as a partner for your next project. We are the right partner for you and offer comprehensive solutions tailored to your individual requirements. Contact us today to find out more!

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

Development of a predictive maintenance use case for a federal authority

Development of a predictive maintenance use case for a federal authority

Development of a predictive maintenance use case for a federal authority

The possibility of meeting spare parts requirements for vehicles in the field is to be analysed with regard to Optimisation of warehousing.

Evaluation of the available data basis with regard to predictive maintenance projects

Recommendations regarding data availability to successfully implement predictive maintenance projects

Challenge

A federal agency experiences a large discrepancy betweenbetween actual demand and the stock of spare parts.for their vehicles in decentralised spare parts centres.store. A feasibility analysis is to be carried out to find out whether the need for spare parts through the use of predictive Maintenance predicted and stockpiling thereby can be optimised.

Solution

Development of a data model of the available datasources in close consultation with experts.Integration of external data sources such as weather and landdata, and interpolation of this data in order to apply it to the The system is also capable of transmitting the geo-positions of the vehicles.Development of simple statistical models on a PoC basis, to predict parts failures.

Result

In the federal agency, awareness was raised for the Requirement for data files and their availability achieved for the implementation of data science projects.Exemplary results of the statistical models can be be used to further advance the use case internally.drive.

Are you interested in your own use cases?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.

Our Case Studies

- Get even more detailed insights into our customer projects -

Smart cooking with Thermomix

Smart cooking with the Thermomix

Download
Case Study AI at Munich Re

Data Operations at Munich Re

Download

Data & AI Knowledge

Creating added value from data & AI together

Blog

Discover professional articles on Data & AI as well as the latest industry news.

Webinars

Dive into our Best Practices and Industry Exchanges. Discover new dates and recordings of past webinars.

Whitepaper

Learn more about the use of Data & AI in your industry with our white papers, case studies and research.

Smart Factory consulting in mechanical engineering

Smart Factory consulting in mechanical engineering

Smart Factory consulting in mechanical engineering

In the project, a vision & mission for Industry 4.0 was developed for a medium-sized machine manufacturer, concrete application potentials were identified and a strategic roadmap for the development of a smart factory was created.
/
Clear understanding of the success factors of a smart factory
Involving and informing all relevant stakeholders (incl. the board of directors) and naming the central responsibilities on the way to the smart factory.
+
Identification of concrete potentials in the form of Smart Factory Use Cases
w

Agile project approach in the context of interviews and various workshop formats using design thinking methods

Challenge

  • Lack of vision for the successful implementation of Industry 4.0 in the production of a medium-sized manufacturer of electric actuators
  • Stakeholder management in medium-sized companies requires strategic intuition
  • On the way to a smart factory, fundamental organisational decisions must be made and the course set

Solution

  • Developing a basic understanding of the Smart Factory and its building blocks with key stakeholders / core team
  • Assessment of the entire production process landscape divided into the areas of logistics, machining, assembly and test benches
  • Potential analysis in the dimensions of organisational structure, processes, roles, governance and system landscape
  • Creation of a common goal and definition of the roadmap for the implementation of a Smart Factory

Result

  • Presentation of the strategic vision in a Smart Factory target image
  • Defined roadmap for achieving the target image based on prioritised use cases

Are you interested in your own use cases?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.