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prof.dr. P.J.M. Havinga (Paul)

Full professor Pervasive Systems

About Me

Prof.dr.ing Paul J.M. Havinga is full professor in the Computer Science department at the University of Twente in the Netherlands, and Director Science at TNO - ICT. He received his PhD at the University of Twente on the thesis entitled “Mobile Multimedia Systems” in 2000. He is also a guest professor Smart IoT systems at the Nanchang University in China.

Paul Havinga has a broad background in various aspects of communication systems: on wireless communication, on chip-area network architectures for handheld devices, mobile multimedia systems, QoS over wireless networks, reconfigurable computing, and on interconnection architectures for multiprocessor systems.

Currently his research themes have focussed on: wireless sensor networks, Internet of Things, distributed networked systems, and energy-efficient wireless communication. The common theme in these areas is on the development of large-scale, heterogeneous, wireless, distributed systems. Research questions cover architectures, protocols, programming paradigms, algorithms, and applications. This research has resulted in over 500 scientific publications in journals and conferences, and 8 patents. He is regularly invited for keynote presentations on this work.

He has a significant experience as project manager in several international research projects on wireless sensor networks. In 2001 he initiated the first European project on wireless sensor networks (2001 – 2004). Many research projects on sensor networks followed, all addressing different aspects of wireless sensor networks and IoT. He was initiator and project coordinator of several large European projects, and coordinator of many national projects.

He is co-founder of several high-tech companies all resulting from the research on wireless sensor networking. In 2004 he founded the company Ambient Systems B.V. as one of the pioneering companies in that domain. In 2008 he co-founded Inertia Technology, on wireless motion sensing. TerraTeq, founded in 2014, is developing wireless sensing systems for environmental and animal monitoring. In 2015 he founded Locus Positioning which develops indoor positioning technologies that provides the possibility to track assets and people and provide navigation in (indoor) environments.

In May 2007 he received the ICT Innovation Award for the successful transfer of knowledge from university to industrial use. In June 2007 he received the “Van den Kroonenberg award” for being a successful innovative entrepreneur.

Expertise

Engineering & Materials Science
# Animals
# Internet Of Things
# Monitoring
# Network Protocols
# Sensor Nodes
# Sensors
# Smartphones
# Wireless Sensor Networks

Organisations

Ancillary Activities

  • Inertia Technology
    scientific advisor
  • Stichting Twente47
    vice president

Publications

Recent
Sharma, N. , Le, D. V. , & Havinga, P. J. M. (2023). Exploring the Impact of Locations and Activities in Person-Wise Data Mismatch in CSI-based HAR. In 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 232-239) https://doi.org/10.1109/DCOSS-IoT58021.2023.00048
Boot, M. , Ulak, B. , Geurs, K. , & Havinga, P. (2023). Using body sensors in evaluations of the impact of smart cycling technologies on cycling experience. In A. Komninos, C. Santoro, D. Gavalas, J. Schoening, M. Matera, & L. A. Leiva (Eds.), MobileHCI '23 Companion: Proceedings of the 25th International Conference on Mobile Human-Computer Interaction (pp. 1-4). Article 43 https://doi.org/10.1145/3565066.3609736
Zia, K. , Chiumento, A. , Havinga, P. J. M., Riggio, R. , & Huang, Y. (2023). QoS Aware Slice Resource Management Using Deep Reinforcement Learning in IoT Networks. In QoS Aware Slice Resource Management Using Deep Reinforcement Learning in IoT Networks (pp. 150-154). ( 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)). https://doi.org/10.1109/DCOSS-IoT58021.2023.00035
Amur, S. H. , Zia, K. , Chiumento, A. , & Havinga, P. J. M. (2023). Autonomous Network Slicing and Resource Management for Diverse QoS in IoT Networks. In 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 160-165). IEEE. https://doi.org/10.1109/PerComWorkshops56833.2023.10150306
Nguyen, S. , Le, D. V. , & Havinga, P. J. M. (2023). Learning the world from its words: Anchor-agnostic Transformers for Fingerprint-based Indoor Localization. In 2023 IEEE International Conference on Pervasive Computing and Communications (PerCom) (pp. 150-159) https://doi.org/10.1109/PERCOM56429.2023.10099376
Klein Brinke, J. , Chiumento, A. , & Havinga, P. J. M. (2023). Channel State Information for Human Activity Recognition with Low Sampling Rates. In UMUM 2023: Second Workshop on Ubiquitous and Multi-domain User Modeling (pp. 614-620)
Darbandi, H., Braganca, F. S. , van der Zwaag, B. J. , & Havinga, P. (2022). Accurate Horse Gait Event Estimation Using an Inertial Sensor Mounted on Different Body Locations. In Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022 (pp. 329-335). (Proceedings IEEE International Conference on Smart Computing, SMARTCOMP; Vol. 2022). IEEE. https://doi.org/10.1109/SMARTCOMP55677.2022.00076
Klein Brinke, J. , Chiumento, A. , & Havinga, P. J. M. (Accepted/In press). Joint Communication and Sensing for Human Activity Recognition in Wi-Fi 6E. 1-5. Poster session presented at 5th IFIP International Internet of Things Conference, IoT 2022, Amsterdam, Netherlands.
Darbandi, H., Serra Bragança, F. M. , van der Zwaag, B. J., Rhodin, M., Hernlund, E., Hobbs, S. J., Clayton, H. M. , & Havinga, P. J. M. (2022). Estimation of hoof-on/off moments using inertial sensors and deep learning. Comparative Exercise Physiology, 18(Suppl. 1), S54-S54. https://doi.org/10.3920/cep2022.s1
Tran, Q. C. V. , Le, D. V. , Yntema, D. R. , & Havinga, P. J. M. (Accepted/In press). Self-diagnostic PVC pipes for capturing threats in un-derground water pipelines. 1-5. Poster session presented at 5th IFIP International Internet of Things Conference, IoT 2022, Amsterdam, Netherlands.
Tran, Q. C. V. , Nguyen, D. T. N. , Le, D. V. , Yntema, D. R. , & Havinga, P. J. M. (Accepted/In press). Efficient talking in underground water pipelines. 1-5. Poster session presented at 5th IFIP International Internet of Things Conference, IoT 2022, Amsterdam, Netherlands.
Tran, Q. C. V. , Le, D. V. , Yntema, D. R. , & Havinga, P. J. M. (Accepted/In press). Testbed Hardware Design to Collect Data for Underground PVC Water Pipe Crack Detection: Challenges and Solutions. 1-5. Paper presented at 5th International SenSys/BuildSys Workshop on Data, DATA 2022, Boston, Massachusetts, United States. https://doi.org/10.4121/21340608.v1, https://doi.org/10.1145/3560905.3567765
Zia, K. , Chiumento, A. , & Havinga, P. J. M. (2022). AI-Enabled Reliable QoS in Multi-RAT Wireless IoT Networks: Prospects, Challenges, and Future Directions. IEEE Open Journal of the Communications Society, 3(2022), 1906 - 1929. Article 9924256. Advance online publication. https://doi.org/10.1109/OJCOMS.2022.3215731
Parmentier, J. I. M. , Zwaag, B. J. V. D., Weishaupt, M. A., Gmel, A. I. , Havinga, P. J. M., van Weeren, P. R., & Serra Bragança, F. M. (2022). Prediction of kinetic parameters from body mounted IMU data using recurrent neural networks. Comparative Exercise Physiology, 18(Suppl. 1), S45-S45. https://doi.org/10.3920/cep2022.s1
Bosch, S. (2022). Pushing the limits of inertial motion sensing. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036554350
Darbandi, H. , & Havinga, P. J. M. (2022). A Machine Learning Approach to Analyze Rider’s Effects on Horse Gait Using On-Body Inertial Sensors. 20th International Conference on Pervasive Computing and Communications, PerCom 2022, Pisa, Italy. https://www.bing.com/videos/search?q=A+Machine+Learning+Approach+to+Analyze+Rider%e2%80%99s+Effects+on+Horse+Gait+Using+On-Body+Inertial+Sensors&qpvt=A+Machine+Learning+Approach+to+Analyze+Rider%e2%80%99s+Effects+on+Horse+Gait+Using+On-Body+Inertial+Sensors&view=detail&mid=2D9C40DCF18A660190782D9C40DCF18A66019078&&FORM=VRDGAR&ru=%2Fvideos%2Fsearch%3Fq%3DA%2BMachine%2BLearning%2BApproach%2Bto%2BAnalyze%2BRider%25e2%2580%2599s%2BEffects%2Bon%2BHorse%2BGait%2BUsing%2BOn-Body%2BInertial%2BSensors%26qpvt%3DA%2BMachine%2BLearning%2BApproach%2Bto%2BAnalyze%2BRider%25e2%2580%2599s%2BEffects%2Bon%2BHorse%2BGait%2BUsing%2BOn-Body%2BInertial%2BSensors%26FORM%3DVDRE
Tran, Q. C. V. , Le, D. V. , Yntema, D. R. , & Havinga, P. J. M. (2022). A Review of Inspection Methods for Continuously Monitoring PVC Drinking Water Mains. IEEE Internet of Things Journal, 9(16), 14336-14354. Article 2327-4662 . Advance online publication. https://doi.org/10.1109/JIOT.2021.3077246
Wang, W. (2021). Seeing with the sound: Sound-based human-context recognition using machine learning. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036552936

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Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11), room 5001
Hallenweg 19
7522NH  Enschede
The Netherlands

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University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling  5001
P.O. Box 217
7500 AE Enschede
The Netherlands

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