Since 2012 TUM, Europe's leading center for innovation and business creation UnternehmerTUM and the Zeidler Research Foundation present the TUM IdeAward. The prize is intended to motivate scientists to develop their inventions and discoveries into marketable products. The winning teams receive cash prizes totaling 37,500 Euros from the Zeidler Research Foundation and coaching sessions with TUM´s start-up advising and UnternehmerTUM.
The TUM IdeAward 2019 was presented on November 21st. First place went to the startup Dymium, second to modular robotics and third to Daniel Maier for his technology for heat detection in cows. More information: Press release TUM IdeAward 2019
Video: IdeAward 2019
Participating teams 2019
Out of the total of 112 original applications, ten start-up ideas had made it to the final round. These ten nominees had the opportunity to present their idea live to the audience on November 21, 2019.
Radioisotope therapies have proven over the last years to be successful approaches to treat a variety of tumor types. Conventionally, the necessary dose is calculated using simplified models that use few data of the patient. Moreover, the radioactivity is applied without any chance for correction during or after the treatment.
DeepDoSys enables personalized treatment ensuring a safe and efficient intervention by enabling personalized dosimetry and closing the feedback loop with real-time imaging. This enables the clinician to react dynamically during the intervention. Also, we minimize the radiation burden in healthy tissue while achieving an adequate dosage in the tumor by considering biokinetic parameters of the patient, further personalizing the treatment.
All of our functionalities will be wrapped in an intuitive and easy to use software and hardware, that will save our end user time and will be easy to integrate into the intervention workflow.
The current growth of organic farmland world-wide – 20 percent growth just between the years 2016 and 2017 – demands new ways for the certification and monitoring process of organic agriculture. The classical methods that are applied today strongly depend on in-situ measurements to monitor the compliance to the standards of organic agriculture.
With the abundance of freely available high-quality satellite imagery, we want to build a processing system that allows the remote monitoring of organic fields to reduce the required manpower and target the in-situ checks more efficiently. To achieve this, we are applying state-of-the-art machine learning algorithms embedded in a fully automated processing system that continuously monitors the farmlands and detects problems early, e.g. the use of banned fertilizers.
This method has not yet been applied on a large-scale basis and will significantly improve the efficiency of the certification and monitoring process to keep up with the continuous growth of organic agriculture.
CAPACITI started as an IMPACT business-plan project for the Executive-MBA in Innovation and Business Creation, at the Technical University of Munich. CAPACITI was originally conceived to have an impact on wider adoption of electro-mobility, by overcoming range-angst. Battery-range and recharge-time are components affecting range-angst.
CAPACITI focuses on battery recharge-time – specifically, battery-cell power density. Understanding the electrical requirement and the material function of a battery-cell, to bring the characteristics of a capacitor and battery together in a new hybrid battery-cell. While there is a lot of focus on enhancing battery-cell energy density (i.e., affecting battery range), there is less activity on battery-cell power density (i.e., affecting recharging time). CAPACITI seeks funding for proof-of-concept.
modular robotics offers a modular system for industrial robots. From only few robot modules, a large variety of different industrial robots can be assembled. Through innovative algorithms, the robots’ control and collision detection is programmed automatically and the robots are instantaneously usable.
Through this newly acquired flexibility, modular robotics enable small and medium businesses to harness the vast potentials of industrial automation.
Dymium brings a radical innovation in the field of Urological MedTech to the market, which dramatically reduces the recurrence rate of kidney stones.
The necessity is high: from around 400.000 annual kidney stone removal surgeries in Germany, kidney stones recurre in 50% of those cases within five years after the first surgery due to leftover fragments. This is due to current surgical procedures, which cannot ensure the complete removal of all kidney stone fragments. The remaining fragments may lead to the formation of a new kidney stone which again leads to pain and a surgery under general anesthesia.
Dymium has developed a new solution which guarantees the extraction of all fragments during the surgery, which leads to a reduction of the recurrence rate from 50% to just <1%.
Localization became a key technology in many fields of the industry. Especially, systems based on the ultra-wideband technology are highly used.
I developed methods to improve the precision and accuracy, for the most common systems based on this technology. Another important aspect of my idea, is the fusion between augmented reality and ultra-wideband. The user of my system, is able to see the other users even through walls.
In firefighting operations this feature could make the difference between life and death.
Automatic heat detection for cattle - Smarter than ever
Agricultural plants will become bigger and bigger in the future. Therefore the need for automated heat detection for cattle will increase further. Present heat detection systems are costly, non-durable and high-maintenance.
We will change this rapidly through our innovative data transfer solution.
We want everyone to have a chance at avoiding life-threatening illnesses by providing a routine test that uncovers early molecular signatures of diseases.
We do this by looking beyond genetics, which mainly gives risk scores, and measuring hundreds of metabolites like vitamins, hormones, amino acids, and sugars that reflect the current and actual health status of the body. We perform the measurements in saliva, an easy-to-collect fluid, and use cutting edge Artificial Intelligence (AI) methods to find molecular patterns that can indicate early signs of diseases.
This is in contrast to common laboratory tests where only one or a handful of health parameters in blood, urine, or, to a lesser extent, saliva is measured and manually interpreted.
elixon - smart traffic
Urbanisation and increasing individual traffic present cities with the great challenge of optimising traffic flow to avoiding emission-intensive congestion.
An essential influence is the timing of the traffic control systems. elixon has found a solution to optimize the timing of traffic control systems cost-effectively and without costly structural measures. Moreover, several additional fields of application are being developed that conventional solutions cannot cover.
elixon combines intelligent data processing with modern sensor technology. With the help of artificial intelligence, elixon recognizes and classifies various road users, anticipates the traffic flow and determines the optimal timing of the traffic control systems. elixon reacts immediately to changes in the flow of traffic. Thanks to the innovative data processing, the field of application of our system is not limited to traffic optimization: accidents, for example, can also be identified as such and automatically forwarded to the responsible emergency responder.
With elixon, traffic management is being rethought - cities and municipalities are to be provided with an intelligent solution to shape the smart cities of the future.
Angsa develops a system for autonomous trash removal on green spaces.
Currently, small garbage on grass and gravel cannot be efficiently removed from the environment: unlike on the road, no sweeping machines can be used on green spaces. The completely manual collection of trash causes high costs for festival organizers and public parc administrations.
Angsa solves this problem by using an autonomous garbage collection robot, which detects small objects using a camera and the machine learning algorithm developed by Angsa. These can then be targeted and sucked in. The used neural network architecture is trained on large datasets and can be adapted for the detection of any trash object.
The robot is especially suitable for all surfaces where conventional cleaning machines can not be used: parcs, outdoor pools, campsites and festival venues.
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