TY - GEN
T1 - A graph-based big data model for wireless multimedia sensor networks
AU - Küçükkeçeci, Cihan
AU - Yazıcı, Adnan
N1 - Funding Information:
This work is supported in part by a research Grant from TÜBİTAK with Grant No. 114R082. We thank to each of the researchers of CEng Multimedia Database Lab. for their very valuable contributions. The first author would also like to thank AYESAŞ for providing financial support.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Wireless multimedia sensor networks are of interest to researchers from different disciplines and many studies have been proposed in a wide variety of application domains, such as military surveillance systems, environmental monitoring, fault monitoring and distributed smart cameras in the last decade. In a wireless sensor network, a large number of sensors can be deployed to monitor target areas and autonomously collect sensor data. This produces a large amount of raw data that needs to be stored, processed, and analyzed. In this paper, we propose a graph-based big data model for simulating multimedia wireless sensor networks. The big sensor data is stored in a graph database for the purpose of advanced analytics like statistics, data mining, and prediction. A prototype implementation of the proposed model has been developed and a number of experiments have been done for measuring the accuracy and efficiency of our solution. In addition, we present a case study using the military surveillance domain with a number of complex experimental queries by using our prototype. The experimental results show that our proposed multimedia wireless sensor network model is efficient and applicable in large-scale real life applications.
AB - Wireless multimedia sensor networks are of interest to researchers from different disciplines and many studies have been proposed in a wide variety of application domains, such as military surveillance systems, environmental monitoring, fault monitoring and distributed smart cameras in the last decade. In a wireless sensor network, a large number of sensors can be deployed to monitor target areas and autonomously collect sensor data. This produces a large amount of raw data that needs to be stored, processed, and analyzed. In this paper, we propose a graph-based big data model for simulating multimedia wireless sensor networks. The big sensor data is stored in a graph database for the purpose of advanced analytics like statistics, data mining, and prediction. A prototype implementation of the proposed model has been developed and a number of experiments have been done for measuring the accuracy and efficiency of our solution. In addition, we present a case study using the military surveillance domain with a number of complex experimental queries by using our prototype. The experimental results show that our proposed multimedia wireless sensor network model is efficient and applicable in large-scale real life applications.
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U2 - 10.1007/978-3-319-47898-2_22
DO - 10.1007/978-3-319-47898-2_22
M3 - Conference contribution
AN - SCOPUS:84994495876
SN - 9783319478975
T3 - Advances in Intelligent Systems and Computing
SP - 205
EP - 215
BT - Advances in Big Data - Proceedings of the 2nd INNS Conference on Big Data, 2016
A2 - Roy, Asim
A2 - Vellasco, Marley
A2 - Manolopoulos, Yannis
A2 - Iliadis, Lazaros
A2 - Angelov, Plamen
PB - Springer Verlag
T2 - 2nd International Neural Network Society Conference on Big Data, INNS 2016
Y2 - 23 October 2016 through 25 October 2016
ER -