The demonstrator shows that our in-network computing-based pICA method can effectively address the challenges for transmission and computing latency of IIoT applications. By interacting with the demonstrator, the audience can better understand the concept of in-network computing and see how, together with the proposed audio data processing method, it can achieve the low-latency requirements of anomaly detection in smart factories.
- Open the URL of pICA-demo.
- pICA and FastICA can be run, paused, and reloaded on-demand in the web application.
If you like our repository, please cite our papers.
- Computing design (pICA):
@INPROCEEDINGS{Wu2112:Network, AUTHOR="Huanzhuo Wu and Yunbin Shen and Xun Xiao and Artur Hecker and Frank H.P. Fitzek", TITLE="{In-Network} Processing Acoustic Data for Anomaly Detection in Smart Factory", BOOKTITLE="2021 IEEE Global Communications Conference: IoT and Sensor Networks (Globecom2021 IoTSN)", ADDRESS="Madrid, Spain", DAYS=6, MONTH=dec, YEAR=2021 } - Network design (stateful transport):
@article{wu2022picaextension, title = "Accelerating Industrial IoT Acoustic Data-Based Anomaly Detection with In-Network Processing", author = "Huanzhuo Wu and Yunbin Shen and Xun Xiao and Giang T. Nguyen and Artur Hecker and Frank H.-P. Fitzek", journal={IEEE Internet of Things Journal}, year={}, note = "(submitted, 2021)", pages={1--14} } - pICA-demo paper:
@inproceedings{Wu2201:Demonstration, AUTHOR={Huanzhuo Wu and Yunbin Shen and M{\'a}t{\'e} {T{\"o}m{\"o}sk{\"o}zi} and Giang T. Nguyen and Frank H.P. Fitzek}, TITLE="Demonstration of {In-Network} Audio Processing for {Low-Latency} Anomaly Detection in Smart Factories", BOOKTITLE="2022 IEEE 19th Annual Consumer Communications \& Networking Conference (CCNC) (CCNC 2022)", ADDRESS="Las Vegas, USA", MONTH=jan, YEAR=2022, KEYWORDS="audio processing; in-network computing; network softwarization; Internet of Things", note = "(submitted, 2021)" }
We are researchers at the Deutsche Telekom Chair of Communication Networks (ComNets) at TU Dresden, Germany. Our focus is on in-network computing.
- Huanzhuo Wu - huanzhuo.wu@tu-dresden.de or wuhuanzhuo@gmail.com
- Yunbin Shen - yunbin.shen@mailbox.tu-dresden.de or shenyunbin@outlook.com
This project is licensed under the MIT license.