Paul Havinga

EMAIL: [email protected]
TEL: +31653161099


Pervasive Systems are systems composed of a network of collaborative sensing, computational, and reasoning components that are highly embedded in and actively – yet unobtrusively – interact with the environment. Embedding millions of networked smart sensing objects into an environment creates a digital skin which senses its immediate space. Such distributed networks of smart objects cooperate to support an application as unobtrusively as possible (transparency), making efficient use of scarce resources independent of growth (scalability), in such a way that the system adapts to a dynamically changing environment (evolvability), and that operates and gives results that can be relied upon (trust). Mainly due to resource constraints, devices and connections are inherently unreliable, yet the system should be able to provide reliable services (quality). The context of this research is smart sensor systems, Internet of Things (IoT), cyber physical systems, wireless sensor networks, and smart objects (e.g. wearable, smart phones).​

The research themes are focused on the design and analysis of the following topics and their interaction:

  • Sensing: Collaborative embedded and opportunistic sensing
  • Networking: Wireless and opportunistic networking
  • Sensor data analytics: Spatio-temporal sensor data analytics

Most important enabling technologies that have emerged to make pervasive computing and the Internet of Things vision a reality are: wireless networking, localization, distributed systems, mobile computing, smart networked sensors, embedded platforms, sensor data analytics and reasoning, etc. They have to deal with ever-changing user requirements, environmental situations and system resources. They have to be privacy aware and secure to encourage wide use and to provide the most optimal services.

Situated at the core of the Internet of Things, my research has high societal and economic impacts in various applications in the area of Smart Urban, Smart Life, and Smart Industry. The common theme in these areas, within which my main research focus lies, is on the development of large-scale, heterogeneous, wireless, distributed systems. Research questions cover architectures, protocols, programming paradigms, algorithms, and applications. Our system-oriented research is inspired by real problems, which makes multi-disciplinary collaboration natural.

In this context, my research contributes closely to the TNO roadmaps on ‘Fast and open infrastructures’, ‘Data sharing, ‘​Trusted ICT’ and ‘Embedded Systems Innovation’.


In 2001, I initiated the first European project on wireless sensor networks, leading to a large body of further research on different aspects of wireless sensor networks and IoT, ranging from environmental monitoring, underwater systems, industrial, body area networks, and crowd sensing, all in various application domains.

Currently, I am involved as project leader in several nationally and internationally funded projects, all dealing with various aspects of pervasive computing. Within the theme of Smart Industry, we have a strong focus on predictive maintenance, for example in large industrial plants (together with Tata), for road maintenance (using crowd sourcing with mobile phones), or bridges. Within the theme of Smart Logistics, I coordinate two large projects, in which distributed smart objects are executing business logic. Important aspects are positioning, distributed processing, security and trust. Environmental monitoring is another important area of research. In particular we execute a project in South Africa on anti-poaching of Rhinos, and two projects in the Netherlands to monitor health and performance of horses. In the healthcare domain we focus (within 3 projects) on unobtrusive sensing methods for elderly people, dementia, and diabetes.

My research has resulted in over 500 scientific publications in journals and conferences, and 9 patents.

In 2020 Major results have been achieved in activity recognition, data sharing, and security​


  • N. Anbalagan MSc (Sabari) (NWO)
  • R.H. Bemthuis MSc (Rob) (NWO)
  • Stephan Bosch (Industry)
  • Darbandi MSc (Hamed) (EFRO)
  • J. Klein Brinke MSc (Jeroen) (EFRO)
  • Mijushkovikj MSc (Adriana) EFRO)
  • T.N. Nguyen MSc (Duong) (Industry)
  • I.M. Parmentier MSc (Jeanne) (EFRO)
  • R. Rathikumar MSc (Jansi) (EU)
  • Sadeghi MSc (Sam) (NWO)
  • Sharma (Nikita) (EU)
  • C.V. Tran MSc (Cao Vinh) (Industry)
  • I. Ullah MSc (Ikram) (EFRO)
  • Wang MSc (Wei) (NWO)
  • Frans Jonkman (Industry)
  • Etto Salomons (Government)
  • Bram Ton (NWO)
  • Prachi Bagave (NWO)


  • Le, D. V. , Meratnia, N. , & Havinga, P. J. M. “Unsupervised Deep Feature Learning to Reduce the Collection of Fingerprints for Indoor Localization Using Deep Belief Networks”. In IPIN 2018 - 9th International Conference on Indoor Positioning and Indoor Navigation (pp. 1-7).
  • Bosch, S., Serra Bragança, F. , Marin-Perianu, M. , Marin-Perianu, R. , van der Zwaag, B. J., Voskamp, J. , Havinga, P. “Equimoves: A wireless networked inertial measurement system for objective examination of horse gait”. Sensors (Switserland), 18(3), 2018.
  • Seraj, F. , Meratnia, N. , & Havinga, P. J. M. “RoVi: Continuous transport infrastructure monitoring framework for preventive maintenance”. In 2017 IEEE International Conference on Pervasive Computing and Communications, PerCom 2017 (pp. 217-226). IEEE.
  • M Shoaib, S Bosch, O Incel, H Scholten, P Havinga, “Complex human activity recognition using smartphone and wrist-worn motion sensors”, Sensors 16 (4), 2017



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