Details
| Original language | English |
|---|---|
| Title of host publication | EnviroInfo 2022 - Short-/Work in Progress-Papers |
| Editors | Volker Wohlgemuth, Stefan Naumann, Hans-Knud Arndt, Grit Behrens, Maximilian Hob |
| Publisher | Gesellschaft fur Informatik (GI) |
| Pages | 167-176 |
| Number of pages | 10 |
| ISBN (electronic) | 9783885797227 |
| Publication status | Published - 2022 |
| Event | 36th International Conference on Informatics for Environmental Protection: Environmental Information and Communication Technologies, EnviroInfo 2022 - Hamburg, Germany Duration: 26 Sept 2022 → 28 Sept 2022 |
Publication series
| Name | Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI) |
|---|---|
| Volume | P-328 |
| ISSN (Print) | 1617-5468 |
Abstract
In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.
Keywords
- image recognition, process modeling, waste properties, waste-to-energy
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
Sustainable Development Goals
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EnviroInfo 2022 - Short-/Work in Progress-Papers. ed. / Volker Wohlgemuth; Stefan Naumann; Hans-Knud Arndt; Grit Behrens; Maximilian Hob. Gesellschaft fur Informatik (GI), 2022. p. 167-176 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-328).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - The application of image recognition methods to improve the performance of waste-to-energy plants
AU - Schwark, Fenja
AU - Garmatter, Henriette
AU - Davila, Maria
AU - Dawel, Lisa
AU - Pehlken, Alexandra
AU - Cyris, Fabian
AU - Scharf, Roland
N1 - Funding Information: This work is supported by the Federal Ministry for Economic Affairs and Climate Action on the basis of a decision by the German Bundestag (FKZ 03EE5038).
PY - 2022
Y1 - 2022
N2 - In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.
AB - In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.
KW - image recognition
KW - process modeling
KW - waste properties
KW - waste-to-energy
UR - http://www.scopus.com/inward/record.url?scp=85139833817&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85139833817
T3 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
SP - 167
EP - 176
BT - EnviroInfo 2022 - Short-/Work in Progress-Papers
A2 - Wohlgemuth, Volker
A2 - Naumann, Stefan
A2 - Arndt, Hans-Knud
A2 - Behrens, Grit
A2 - Hob, Maximilian
PB - Gesellschaft fur Informatik (GI)
T2 - 36th International Conference on Informatics for Environmental Protection: Environmental Information and Communication Technologies, EnviroInfo 2022
Y2 - 26 September 2022 through 28 September 2022
ER -