Collaborative Wireless Sensor Networks in Industrial and Business Processes

Mihai Marin-Perianu

Research output: ThesisPhD Thesis - Research UT, graduation UT

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Personal computers, mobile telephony and the Internet made the vision of everyone being networked real, at such a level of quality and speed that people could only dream of, one hundred years ago. Nowadays, another dream starts to become reality: the dream of networking everything. The limits of this everything are set only by our imagination: containers, trucks, robots, coffee cups, zebras, corals, firefighters, energy meters, etc. Wireless Sensor Networks (WSNs) created the technological basis for all these applications by embedding sensing, processing and communication in one tiny device (the sensor node) and by executing tasks in a distributed, collaborative manner within the network. Through collaboration WSNs can organize efficiently, prolong system lifetime, handle dynamics, detect and correct errors, all with the final goal of eventually executing reliably the user application. WSNs stimulated a long list of applications from various domains, ranging from environmental monitoring to industrial processes, and even further to cognitive robotic systems or space exploration. This thesis focuses on WSN integration in industrial and business processes, and explores collaborative techniques to make WSNs more reliable, intelligent, effective and easy-to use. The specific contributions are: (1) analysis of the market potential and requirements, (2) service-oriented WSN architecture, (3) reliable multicast data dissemination protocol, (4) rule-based inference for event detection, (5) fuzzy logic distributed activity recognition and (6) mobile sensor-actuator team coordination.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
  • Smit, G.J.M., Supervisor
  • Havinga, Paul J.M., Co-Supervisor
Award date6 Nov 2008
Place of PublicationEnschede, the Netherlands
Print ISBNs978-90-365-2746-0
Publication statusPublished - 6 Nov 2008


  • EC Grant Agreement nr.: FP7/215923


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