Search Results for author: Ian Marius Peters

Found 8 papers, 5 papers with code

Introducing flexible perovskites to the IoT world using photovoltaic-powered wireless tags

no code implementations1 Jul 2022 Sai Nithin Reddy Kantareddy, Rahul Bhattacharya, Sanjay E. Sarma, Ian Mathews, Janak Thapa, Liu Zhe, Shijing Sun, Ian Marius Peters, Tonio Buonassisi

Our evaluation of the prototypes suggests that: i) flexible PV cells are durable up to a bending radius of 5 mm with only a 20 % drop in relative efficiency; ii) RFID communication range increased by 5x, and meets the energy needs (10-350 microwatt) to enable self-powered wireless sensors; iii) perovskite powered wireless sensors enable many battery-less sensing applications (e. g., perishable good monitoring, warehouse automation)

Georeferencing of Photovoltaic Modules from Aerial Infrared Videos using Structure-from-Motion

2 code implementations6 Apr 2022 Lukas Bommes, Claudia Buerhop-Lutz, Tobias Pickel, Jens Hauch, Christoph Brabec, Ian Marius Peters

Comparison with an accurate orthophoto of one of the large-scale plants yields a root mean square error of the estimated module geocoordinates of 5. 87 m and a relative error within each plant row of 0. 22 m to 0. 82 m. Finally, we use the module geocoordinates and extracted IR images to visualize distributions of module temperatures and anomaly predictions of a deep learning classifier on a map.

Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning

2 code implementations6 Dec 2021 Lukas Bommes, Mathis Hoffmann, Claudia Buerhop-Lutz, Tobias Pickel, Jens Hauch, Christoph Brabec, Andreas Maier, Ian Marius Peters

Instead, we frame fault detection as more realistic unsupervised domain adaptation problem where we train on labelled data of one source PV plant and make predictions on another target plant.

Anomaly Detection Contrastive Learning +2

Module-Power Prediction from PL Measurements using Deep Learning

no code implementations31 Aug 2021 Mathis Hoffmann, Johannes Hepp, Bernd Doll, Claudia Buerhop-Lutz, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein

While these areas can be easily identified from electroluminescense (EL) images, this is much harder for photoluminescence (PL) images.


Computer Vision Tool for Detection, Mapping and Fault Classification of PV Modules in Aerial IR Videos

2 code implementations14 Jun 2021 Lukas Bommes, Tobias Pickel, Claudia Buerhop-Lutz, Jens Hauch, Christoph Brabec, Ian Marius Peters

In this work, we develop a computer vision tool for the semi-automatic extraction of PV modules from thermographic UAV videos.

Deep Learning-based Pipeline for Module Power Prediction from EL Measurements

1 code implementation30 Sep 2020 Mathis Hoffmann, Claudia Buerhop-Lutz, Luca Reeb, Tobias Pickel, Thilo Winkler, Bernd Doll, Tobias Würfl, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein

However, knowledge of the power at maximum power point is important as well, since drops in the power of a single module can affect the performance of an entire string.

Bridging the gap between photovoltaics R&D and manufacturing with data-driven optimization

1 code implementation28 Apr 2020 Felipe Oviedo, Zekun Ren, Xue Hansong, Siyu Isaac Parker Tian, Kaicheng Zhang, Mariya Layurova, Thomas Heumueller, Ning li, Erik Birgersson, Shijing Sun, Benji Mayurama, Ian Marius Peters, Christoph J. Brabec, John Fisher III, Tonio Buonassisi

Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost.

Applied Physics

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