Wireless Big Data Augmented Smart Industry

Project Details

Description

In manufacturing environments, human workers interact with increasingly autonomous machinery.
To ensure workspace safety and production efficiency during human-robot (HR) cooperation (HRC), continuous and accurate tracking and perception of workers' activities is the key.
Examples are reactive collision-prevention, active recognition of workers' intention, as well as accurate tracking of human-robot interactions.
The project moves forward the state-of-the-art in advanced sensing and perception for next generation manufacturing workspace.
We explore passive radio sensing to track, recognize and analyse HRC without requiring workers to wear devices, and without the need for privacy-intrusive video, while ensuring workers' safety and privacy.
RadioSense leverages real-time collection and processing of heterogeneous radio signal streams (e.g., 4G/5G and WiFi connections) and multiple Channel State Information (CSI) between different links/antennas.
Short titleRadioSense
AcronymRadioSense
StatusActive
Effective start/end date01/01/201928/02/2022
  • Motion pattern recognition in 4D point clouds

    Salami, D., Palipana, S., Kodali, M. & Sigg, S., Sep 2020, Proceedings of the 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing, MLSP 2020. IEEE, 6 p. 9231569. (IEEE International Workshop on Machine Learning for Signal Processing).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    File
    2 Citations (Scopus)
    32 Downloads (Pure)
  • Extracting Human Context Through Receiver-End Beamforming

    Palipana, S. & Sigg, S., 2019, In: IEEE Access. 7, p. 154535-154545 11 p., 8856202.

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
    File
    2 Citations (Scopus)
    21 Downloads (Pure)
  • Receiver-side beamforming to isolate channel perturbations from a human target in a device-free setting

    Palipana, S. & Sigg, S., 10 Nov 2019, DFHS 2019 - Proceedings of the 1st ACM Workshop on Device-Free Human Sensing. ACM, p. 6-9 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review