2021
|
| [NSDI'21] |
Bootstrapping Battery-free Wireless Networks: Efficient Neighbor Discovery and Synchronization in the Face of Intermittency Conference
Kai Geissdoerfer, Marco Zimmerling
Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2021.
Paper | Website | BibTeX
@conference{Geissdoerfer2021,
title = {Bootstrapping Battery-free Wireless Networks: Efficient Neighbor Discovery and Synchronization in the Face of Intermittency},
author = {Kai Geissdoerfer and Marco Zimmerling},
year = {2021},
date = {2021-04-13},
booktitle = {Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
| [PerCom'21] |
SolAR: Energy Positive Human Activity Recognition using Solar Cells Conference
Muhammad Moid Sandhu, Sara Khalifa, Kai Geissdoerfer, Raja Jurdak, Marius Portmann
2021 IEEE International Conference on Pervasive Computing and Communications (PerCom), 2021.
Paper | BibTeX
@conference{Sandhu2021,
title = {SolAR: Energy Positive Human Activity Recognition using Solar Cells},
author = {Muhammad Moid Sandhu and Sara Khalifa and Kai Geissdoerfer and Raja Jurdak and Marius Portmann},
year = {2021},
date = {2021-03-23},
booktitle = {2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
| [GetMobile'21] |
Taking a Deep Dive Into The Batteryless Internet of Things With Shepherd Journal Article
Kai Geissdoerfer, Mikołaj Chwalisz, Marco Zimmerling
ACM GetMobile: Mobile Computing and Communications, 2021.
Paper | BibTeX
@article{Geissdoerfer2021a,
title = {Taking a Deep Dive Into The Batteryless Internet of Things With Shepherd},
author = {Kai Geissdoerfer and Mikołaj Chwalisz and Marco Zimmerling},
year = {2021},
date = {2021-01-22},
journal = {ACM GetMobile: Mobile Computing and Communications},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
2020
|
| [IPSN'20] |
Demo: Bootstrapping Batteryless Networks Using Fluorescent Light Properties Presentation
Kai Geissdoerfer, Friedrich Schmidt, Brano Kusy, Marco Zimmerling
21.04.2020.
Paper | BibTeX
@misc{Geissdoerfer_2020a,
title = {Demo: Bootstrapping Batteryless Networks Using Fluorescent Light Properties},
author = {Kai Geissdoerfer and Friedrich Schmidt and Brano Kusy and Marco Zimmerling},
year = {2020},
date = {2020-04-21},
booktitle = {Proceedings of the 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
|
| [PerCom'20] |
Towards Energy Positive Sensing using Kinetic Energy Harvesters Conference
Muhammad Moid Sandhu, Kai Geissdoerfer, Sara Khalifa, Raja Jurdak, Marius Portmann, Brano Kusy
2020 IEEE International Conference on Pervasive Computing and Communications (PerCom), 2020.
Paper | Abstract | BibTeX
@conference{Sandhu2020,
title = {Towards Energy Positive Sensing using Kinetic Energy Harvesters},
author = {Muhammad Moid Sandhu and Kai Geissdoerfer and Sara Khalifa and Raja Jurdak and Marius Portmann and Brano Kusy},
year = {2020},
date = {2020-03-23},
booktitle = {2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)},
abstract = {Conventional systems for motion context detection rely on batteries to provide the energy required for sampling a motion sensor. Batteries, however, have limited capacity and, once depleted, have to be replaced or recharged. Kinetic Energy Harvesting (KEH) allows to convert ambient motion and vibration into usable electricity and can enable batteryless, maintenance free operation of motion sensors. The signal from a KEH transducer correlates with the underlying motion and may thus directly be used for context detection, saving space, cost and energy by omitting the accelerometer. Previous work uses the open circuit or the capacitor voltage for sensing without using the harvested energy to power a load. In this paper, we propose to use other sensing points in the KEH circuit that offer information-rich sensing signals while the energy from the harvester is used to power a load. We systematically analyze multiple sensing signals available in different KEH architectures and compare their performance in a transport mode detection case study. To this end, we develop four hardware prototypes, conduct an extensive measurement campaign and use the data to train and evaluate different classifiers. We show that sensing the harvesting current signal from a transducer can be energy positive, delivering up to ten times as much power as it consumes for signal acquisition, while offering comparable detection accuracy to the accelerometer signal for most of the considered transport modes.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Conventional systems for motion context detection rely on batteries to provide the energy required for sampling a motion sensor. Batteries, however, have limited capacity and, once depleted, have to be replaced or recharged. Kinetic Energy Harvesting (KEH) allows to convert ambient motion and vibration into usable electricity and can enable batteryless, maintenance free operation of motion sensors. The signal from a KEH transducer correlates with the underlying motion and may thus directly be used for context detection, saving space, cost and energy by omitting the accelerometer. Previous work uses the open circuit or the capacitor voltage for sensing without using the harvested energy to power a load. In this paper, we propose to use other sensing points in the KEH circuit that offer information-rich sensing signals while the energy from the harvester is used to power a load. We systematically analyze multiple sensing signals available in different KEH architectures and compare their performance in a transport mode detection case study. To this end, we develop four hardware prototypes, conduct an extensive measurement campaign and use the data to train and evaluate different classifiers. We show that sensing the harvesting current signal from a transducer can be energy positive, delivering up to ten times as much power as it consumes for signal acquisition, while offering comparable detection accuracy to the accelerometer signal for most of the considered transport modes.
|
| [PerIoT'20] |
Towards Optimal Kinetic Energy Harvesting for the Batteryless IoT Workshop
Muhammad Moid Sandhu, Kai Geissdoerfer, Sara Khalifa, Raja Jurdak, Marius Portmann, Brano Kusy
2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2020.
Paper | BibTeX
@workshop{Sandhu2020a,
title = {Towards Optimal Kinetic Energy Harvesting for the Batteryless IoT},
author = {Muhammad Moid Sandhu and Kai Geissdoerfer and Sara Khalifa and Raja Jurdak and Marius Portmann and Brano Kusy},
year = {2020},
date = {2020-03-23},
booktitle = {2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)},
keywords = {},
pubstate = {published},
tppubtype = {workshop}
}
|
2019
|
| [SenSys'19] |
Detailed Recording and Emulation of Spatio-temporal Energy Environments with Shepherd Demo
Kai Geissdoerfer, Mikolaj Chwalisz, Marco Zimmerling
New York (NY, USA), 13.11.2019.
Abstract | BibTeX
@misc{Geissdoerfer2019b,
title = {Detailed Recording and Emulation of Spatio-temporal Energy Environments with Shepherd},
author = {Kai Geissdoerfer and Mikolaj Chwalisz and Marco Zimmerling},
url = {http://localhost:8081/wp-content/uploads/2019/11/geissdoerfer19shepherd2.pdf, Paper},
year = {2019},
date = {2019-11-13},
address = {New York (NY, USA)},
organization = { In Proceedings of the 17th ACM Conference on Embedded Networked Sensor Systems (SenSys)},
abstract = {Collaboration of batteryless nodes is essential to their success inreplacing traditional battery-based systems. This abstract describesa demonstration of the recently proposedShepherdtestbed thatallows to record and reproduce spatio-temporal characteristics ofreal energy environments. It consists of a number of spatially dis-tributedShepherdnodes that are tightly time-synchronized witheach other and record synchronized energy traces with a resolutionof3μAand50μVat a rate of100 kHz. Additionally,Shepherdcanfaithfully replay these traces to any number of nodes to study theirbehavior, both individually and as an ensemble.Shepherdworkswith various sources of energy harvesting, such as kinetic or solar,is based on a modular design and provides a generic interface forsensor nodes allowing users to experiment with new platforms.},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Collaboration of batteryless nodes is essential to their success inreplacing traditional battery-based systems. This abstract describesa demonstration of the recently proposedShepherdtestbed thatallows to record and reproduce spatio-temporal characteristics ofreal energy environments. It consists of a number of spatially dis-tributedShepherdnodes that are tightly time-synchronized witheach other and record synchronized energy traces with a resolutionof3μAand50μVat a rate of100 kHz. Additionally,Shepherdcanfaithfully replay these traces to any number of nodes to study theirbehavior, both individually and as an ensemble.Shepherdworkswith various sources of energy harvesting, such as kinetic or solar,is based on a modular design and provides a generic interface forsensor nodes allowing users to experiment with new platforms.
|
| [SenSys'19] |
Shepherd: A Portable Testbed for the Batteryless IoT Conference
Kai Geissdoerfer, Mikolaj Chwalisz, Marco Zimmerling
In Proceedings of the 17th ACM Conference on Embedded Networked Sensor Systems New York (NY, USA), 2019.
Paper | Website | BibTeX
@conference{Geissdoerfer2019c,
title = {Shepherd: A Portable Testbed for the Batteryless IoT},
author = {Kai Geissdoerfer and Mikolaj Chwalisz and Marco Zimmerling},
year = {2019},
date = {2019-11-01},
address = {New York (NY, USA)},
organization = { In Proceedings of the 17th ACM Conference on Embedded Networked Sensor Systems},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
| [IEEE TMC'19] |
Energy- and Mobility-Aware Scheduling for Perpetual Trajectory Tracking Journal Article
Philipp Sommer, Kai Geissdoerfer, R Jurdak, B Kusy, J Liu, K Zhao, A Mckeown, D Westcott
IEEE Transactions on Mobile Computing, pp. 1-1, 2019, ISSN: 2161-9875.
Paper | BibTeX
@article{8634931,
title = {Energy- and Mobility-Aware Scheduling for Perpetual Trajectory Tracking},
author = {Philipp Sommer and Kai Geissdoerfer and R Jurdak and B Kusy and J Liu and K Zhao and A Mckeown and D Westcott},
doi = {10.1109/TMC.2019.2895336},
issn = {2161-9875},
year = {2019},
date = {2019-05-02},
journal = {IEEE Transactions on Mobile Computing},
pages = {1-1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
| [IPSN'19] |
Getting More Out of Energy-harvesting Systems: Energy Management under Time-varying Utility with PREAcT Conference
Kai Geissdoerfer, Brano Kusy, Raja Jurdak, Marco Zimmerling
In Proceedings of the 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Montreal (Canada), 2019.
Paper | BibTeX
@conference{Geissdoerfer2019Apr,
title = {Getting More Out of Energy-harvesting Systems: Energy Management under Time-varying Utility with PREAcT},
author = {Kai Geissdoerfer and Brano Kusy and Raja Jurdak and Marco Zimmerling},
year = {2019},
date = {2019-04-01},
journal = {2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)},
address = {Montreal (Canada)},
organization = {In Proceedings of the 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
| [CNERT'19] |
Walker: DevOps Inspired Workflow for Experimentation Workshop
Mikołaj Chwalisz, Kai Geissdoerfer, Adam Wolisz
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops 2019.
Paper | BibTeX
@workshop{8845199,
title = {Walker: DevOps Inspired Workflow for Experimentation},
author = {Mikołaj Chwalisz and Kai Geissdoerfer and Adam Wolisz},
doi = {10.1109/INFCOMW.2019.8845199},
year = {2019},
date = {2019-04-01},
pages = {277-282},
organization = {IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops},
keywords = {},
pubstate = {published},
tppubtype = {workshop}
}
|
2018
|
| [IPSN'18] |
Long-term Energy-neutral Operation of SolarEnergy-harvesting Sensor Nodes under Time-varying Utility Poster Abstract
Kai Geissdoerfer, Raja Jurdak, Brano Kusy
11.04.2018.
Paper | BibTeX
@misc{Geissdoerfer2018,
title = {Long-term Energy-neutral Operation of SolarEnergy-harvesting Sensor Nodes under Time-varying Utility},
author = {Kai Geissdoerfer and Raja Jurdak and Brano Kusy},
year = {2018},
date = {2018-04-11},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
|
2017
|
| [Sensors'17] |
A fast multimodal ectopic beat detection method applied for blood pressure estimation based on pulse wave velocity measurements in wearable sensors Journal Article
Maik Pflugradt, Kai Geissdoerfer, Matthias Goernig, Reinhold Orglmeister
Sensors (Basel), 2017.
Paper | BibTeX
@article{Pflugradt2017,
title = {A fast multimodal ectopic beat detection method applied for blood pressure estimation based on pulse wave velocity measurements in wearable sensors},
author = {Maik Pflugradt and Kai Geissdoerfer and Matthias Goernig and Reinhold Orglmeister},
doi = {10.3390/s17010158},
year = {2017},
date = {2017-01-17},
journal = {Sensors (Basel)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
