Combining fog computing with sensor mote machine learning for industrial IoT M Lavassani, S Forsström, U Jennehag, T Zhang Sensors 18 (5), 1532, 2018 | 77 | 2018 |
Future Industrial Networks in Process Automation: Goals, Challenges, and Future Directions J Åkerberg, J Furunäs Åkesson, J Gade, M Vahabi, M Björkman, ... Applied Sciences 11 (8), 3345, 2021 | 19 | 2021 |
Sensor time series association rule discovery based on modified discretization method R Xue, T Zhang, D Chen, J Le, M Lavassani 2016 First IEEE International Conference on Computer Communication and the …, 2016 | 9 | 2016 |
From brown-field to future industrial networks, a case study M Lavassani, J Åkerberg, M Björkman Applied Sciences 11 (7), 3231, 2021 | 6 | 2021 |
Modeling and profiling of aggregated industrial network traffic M Lavassani, J Åkerberg, M Björkman Applied Sciences 12 (2), 667, 2022 | 5 | 2022 |
Reliable information exchange in IIoT: Investigation into the role of data and data-driven modelling M Lavassani Mid Sweden University, 2018 | 2 | 2018 |
Pixvid: Capturing temporal correlated changes in time series Y Lin, M Lavassani, J Li, T Zhang 2017 Fifth International Conference on Advanced Cloud and Big Data (CBD …, 2017 | 2 | 2017 |
Data-driven Method for In-band Network Telemetry Monitoring of Aggregated Traffic M Lavassani, J Åkerberg, M Björkman 2022 IEEE 21st International Symposium on Network Computing and Applications …, 2022 | 1 | 2022 |
Handling event-triggered traffic of safety and closed-loop control systems in WSANs M Lavassani, F Barać, M Gidlund, T Zhang 2016 IEEE 14th International Conference on Industrial Informatics (INDIN …, 2016 | 1 | 2016 |
Evolving Industrial Networks: Data-Driven Network Traffic Modelling and Monitoring M Lavassani PQDT-Global, 2023 | | 2023 |
A Deterministic MAC Protocol to Handle Emergency Traffic in IWSN M Lavassani | | 2015 |