As part of the Co-Innovation Lab (CIL) at the Munich University of Applied Sciences, two students have provided an introduction to artificial intelligence for the company klarx. The project team consisted of Tobias Hetfleisch, Marc Gehring as well as Prof. Dr. Holger Günzel from Munich University of Applied Sciences, and Moritz Schmidt and Camille Raiser from the company klarx.
A success story for all involved
During the summer semester 2020, the company klarx and students of the Munich University of Applied Sciences worked on the development and implementation of several machine learning models. The two student consultants were able to sustainably optimize the sales process of the construction machinery brokerage klarx within a very short time. Furthermore, a concept was developed by which these algorithms can be implemented in the daily business of the customer.
The consulting team analyzed the business data of the past five years so that a prototype could be developed for the customer in a very short time. This was further adapted to the customer’s individual requirements using several optimization loops. The goal of the consulting team was to differentiate itself from the previous tech giants by setting up and implementing individual solution approaches and not to offer a “one size fits all” solution.
According to Moritz Schmidt (klarx – Financial Management), the project result “represents the first step into the new and important field of artificial intelligence” and could not have been implemented in the foreseeable future without this project.
Students at Munich University of Applied Sciences are paving the way for digitization in municipal used clothing collection and enabling plannable recycling with the help of the Internet of Things and artificial intelligence.
As part of a student consulting project of the Co-Innovation Lab at the Munich University of Applied Sciences, an interdisciplinary team of students developed a holistic concept for emptying used clothing containers at the Abfallwirtschaftsbetrieb München (AWM) in line with demand. The aim was to optimize the previously rigid emptying schedule, which takes into account the respective emptying requirements of the containers, and thus to improve the quality of the clothing and make more efficient use of existing resources. The focus was thus on moving toward digitization with the help of the Internet of Things (IoT), thereby creating data-based, demand-driven planability with a digital planning tool.
The team consisted of students from three degree programs at Munich University of Applied Sciences and was divided into a consulting team consisting of Mahboob Elahi Noor, Gilbert Muhumuza and Marlene Piper and a development team consisting of industrial engineering students Agnesa Xhemaili, Majlinda Sllamniku and Stefan An. Prof. Dr. Holger Günzel and Prof. Dr. Olav Hinz assisted the team as coaches.
The client Rudolph Schmid (department head of bulky waste and depot container collection AWM) was impressed by the solution that was finally presented: “From the department’s point of view, all requirements for the project, which was presented in an exciting presentation, were exceeded.”