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Bio-waste (also called organic waste or green waste) can be used as a sustainable feedstock for the production of biogas: an alternative energy source. However, In order to be efficient, a biogas plant must process large amounts of organic material. Currently, Entsorgung + Recycling Zürich (ERZ) processes bio-waste from households that is stored in special green containers and collected weekly with compactor trucks. This material then gets converted into biogas (or compost) at the fermentation plant.
As each green bin serves numerous households and is quite deep (approximately 1.5m), liquids seep down and pool at the bottom, while other particles may stick to the container walls. When ERZ arrives on site, the containers are emptied into the trucks and later placed back to their original location, but without cleaning them. Cleaning is either left to the landlord or done with a specialized vehicle, but is rare, and the containers may become less appealing to use over time.
- Engineering and Technology
- Master Thesis
| This project aims to develop interpretable machine learning algorithms to understand the relationship between physical and psychological aspects of pain, through the identification of reliable biomarkers that consider pain in all its multidimensional aspects, towards an optimal diagnosis and personalized therapies.
Chronic Pain patients will be monitored during at-home multiday experimental protocol. During this time, they will be asked to wear a wearable device collecting multiple physiological data and to complete comprehensive assessments through psychological and life-quality questionnaires. Machine Learning models will be applied to disentangle the physical and emotional components and to correlate pain perception with sleep quality and medications.
- Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Neurosciences
- Master Thesis
| This project aims to evaluate how emotional and cognitive contributions, introduced using different virtual reality scenarios, change the subjective pain perception. We aim to conduct a study comprising Transcutaneous Electrical Nerve Stimulation (TENS) and Virtual Reality (VR). TENS will be used to induce short painful stimuli while VR will be used to modulate the cognitive and emotional inputs by presenting different inputs (e.g., fire/electricity vs water stimuli on the virtual limb). Several physiological measures (EEG and multisensory wearable) will be collected together with the subjective pain perception. Machine Learning will be applied to physiological data, to disentangle the physical reaction to pain with respect to psychological components. - Biomedical Engineering, Neurosciences
- Master Thesis, Semester Project
| In the city of Zurich, the locations of the recycling collection points (RCP) are not digitally recorded and there is no geo-information system in which the locations are recorded. In certain areas (e.g. Höngg) there is also an undersupply and the affected residents do not have easy access to the RCP (e.g. not within walking distance). Entsorgung + Recycling Zürich (ERZ) would like to remedy the existing undersupply and to show the existing RCP in a digitalized and possibly interactive map.
At the same time, the city of Zurich is growing and new housing developments are constantly being added, triggering additional demand for RCP. Due to other urban developments, it may also happen that existing RCP have to be deconstructed. Currently, no planning model exists to identify or predict optimal RCP locations.
- Engineering and Technology
- Master Thesis
| Entsorgung + Recycling Zürich (ERZ) provides a variety of waste collection services for the citizens and companies of Zurich; one of the services is an on-demand collection of bulky waste by compactor trucks. The trucks are equipped with a weighing system for standardized containers, which can be handled by the container tipping mechanism. Unfortunately, single pieces of furniture (e.g. sofas, tables, etc.) cannot be weighed. Thus, ERZ is forced to charge the customers by loading time instead of weight of the collected material.
In order to implement a more suitable calculation of costs, ERZ is interested in finding a method to weigh single pieces with the same scale used for the weighing of the containers.
- Engineering and Technology
- Master Thesis
| Entsorgung + Recycling Zürich (ERZ) manages more than 4100 public waste bins of different designs throughout the city of Zurich. Considering the large number of waste containers that get emptied every day, efficient workflows are extremely important. In the case of the public waste bins, the removal of full bags and the replacement of new bags in the waste receptacles is time-consuming and inefficient. While the full bag can be removed rather easily, the placing of the new bag can be a cumbersome process. ERZ strives to continuously improve ergonomics and optimize the workflows. Therefore, it is investigating better solutions for the bag replacement cycle. - Engineering and Technology
- Master Thesis
| In this project the student will attempt to embed relevant physics priors in graph neural networks (GNNs) with the goal of developing an inverse modeling framework for the prediction of the underlying material model of a system, given the labeled input (load/excitation) and the output (mechanical response) data. - Engineering and Technology
- Master Thesis, Semester Project
| Kimberly-Clark has partnered with Global Health Engineering (GHE) at ETH Zurich and Green Corridors to conduct a hands-on study to pilot the safe disposal of absorbent hygiene product (AHP) waste in low income /informal communities in Durban, South Africa. Through evidence-based research findings, Kimberly-Clark aims to contribute towards addressing growing concerns globally around AHP in the environment and towards a circular economy for single-use AHPs in South Africa. Responding to this call, a multi-disciplinary team from Green Corridors and ETH Zurich, has been selected to design and pilot an AHP collection system in two different low-income, informal communities within Durban, at a workable scale. The intervention will be guided through innovative and appropriate research methodologies from psychology, geography, and engineering disciplines, which will generate research findings that can inform scaled up implementation of the system in comparable contexts within South Africa. - Engineering and Technology
- Master Thesis
| This project explores new techniques to enhance Optical Flow Estimation in the context of Event-Based Vision. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| This project focuses on utilizing multi-purpose vision models in the realm of Event-Based Vision. - Computer Vision
- Master Thesis
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