INTELLIGENT TRACKING AND NAVIGATING MOVING OBJECTS IN A SMART ENVIRONMENT USING IOT NETWORK
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Abstract
Internet of things (IoT) constitutes the combinations of sensors, controllers, actuators, connectivity. Tracking and navigating moving objects are crucial tasks for security as well as a secure and smart environment. By using the sensory data, location of objects can be identified then that sensory data will be transferred to controllers for the further processes. One pivot role of the system is to identify the trajectory and location of the object using the speed, velocity, acceleration, maps etc and this can be done by machine learning programs. Analyzing service required, prediction of the trajectory and real-world knowledge of maps or locations, service request parameters are adjusted to discover relevant virtual objects dynamically to overcome the loop-carry dependency. This paper proposes an architecture that supports tracking down and allocating relevant virtual objects based on a self-aware environment technology in IoT to track moving objects.
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Internet of things, self aware environment, loop-carry dependency, machine learning, object identification, sensory data.
[2] M. G. Kibria, S. M. M. Fattah, K. Jeong, I. Chong and Y. K. Jeong, “A User-Centric Knowledge Creation Model in a Web of Objects Enabled IoT Environment”, Sensors 2015, 15(9), pp. 24054-24086.
[3] Z. U. Shamszaman, S. S. Ara, I. Chong and Y. K. Jeong, "Web of Objects (WoO) Based Context-Aware Emergency Fire Management Systems for the Internet of Things", Sensors 2014, 14, 2944–2966.
[4] X. H. Wang, D. Q. Zhang, T. Gu and H. K. Pung, "Ontology-Based Context Modeling and Reasoning using OWL", In proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops (PERCOMW'04), FL, USA, 14–17 March 2004; pp. 18–22.
[5] S. Staab, R. Studer, H. P. Schnurr, Y. Sure, “Knowledge Processes and Ontologies”, IEEE Intelligent Systems, Jan 2001, Vol. 16(1), pp. 26-34.
[6] I. Cohen and G´. Medioni, “Detecting and Tracking Moving Objects for Video Surveillance”, IEEE Proc. Computer Vision and Pattern Recognition, CA, USA, Jun 1999, pp. 319-325.
[7] B. Karasulu and S. Korukoglu, “Performance Evaluation Software, Chapter 2: Moving Object Detection and Tracking in Videos”, SpringerBriefs in Com. Science, 2013, pp. 7-30.