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Article Citation - WoS: 33Citation - Scopus: 41Visual and Auditory Data Fusion for Energy-Efficient and Improved Object Recognition in Wireless Multimedia Sensor Networks(Ieee-inst Electrical Electronics Engineers inc, 2019) Koyuncu, Murat; Yazici, Adnan; Civelek, Muhsin; Cosar, Ahmet; Sert, MustafaAutomatic threat classification without human intervention is a popular research topic in wireless multimedia sensor networks (WMSNs) especially within the context of surveillance applications. This paper explores the effect of fusing audio-visual multimedia and scalar data collected by the sensor nodes in a WMSN for the purpose of energy-efficient and accurate object detection and classification. In order to do that, we implemented a wireless multimedia sensor node with video and audio capturing and processing capabilities in addition to traditional/ordinary scalar sensors. The multimedia sensors are kept in sleep mode in order to save energy until they are activated by the scalar sensors which are always active. The object recognition results obtained from video and audio applications are fused to increase the object recognition performance of the sensor node. Final results are forwarded to the sink in text format, and this greatly reduces the size of data transmitted in network. Performance test results of the implemented prototype system show that the fusing audio data with visual data improves automatic object recognition capability of a sensor node significantly. Since auditory data requires less processing power compared to visual data, the overhead of processing the auditory data is not high, and it helps to extend network lifetime of WMSNs.Article Citation - WoS: 30Citation - Scopus: 48A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications(Ieee-inst Electrical Electronics Engineers inc, 2019) Yazici, Adnan; Koyuncu, Murat; Sert, Seyyit Alper; Yilmaz, TurgayMultimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framework explores three main issues: 1) the design of a wireless multimedia sensor (WMS) node to detect objects using machine learning techniques; 2) a method for increasing the accuracy while reducing the amount of information transmitted by the WMS nodes to the base station, and; 3) a new cluster-based routing algorithm for the WMSNs that consumes less power than the currently used algorithms. In this context, a WMS node is designed and implemented using commercially available components. In order to reduce the amount of information to be transmitted to the base station and thereby extend the lifetime of a WMSN, a method for detecting and classifying objects on three different layers has been developed. A new energy-efficient cluster-based routing algorithm is developed to transfer the collected information/data to the sink. The proposed framework and the cluster-based routing algorithm are applied to our WMS nodes and tested experimentally. The results of the experiments clearly demonstrate the feasibility of the proposed WMSN architecture in the real-world surveillance applications.Article Citation - WoS: 9Citation - Scopus: 11Food Index: a Multidimensional Index Structure for Similarity-Based Fuzzy Object Oriented Database Models(Ieee-inst Electrical Electronics Engineers inc, 2008) Yazici, Adnan; Ince, Cagri; Koyuncu, MuratA fuzzy object-oriented data model is a fuzzy logic-based extension to an object-oriented database model that permits uncertain data to be explicitly represented. The fuzzy object-oriented database (FOOD) model is one of the proposed models in the literature to handle uncertainty in object-oriented databases. Several kinds of fuzziness are dealt with in the FOOD model, including fuzziness at attribute level and between object and class and between class and superclass relations. The traditional index structures do not allow efficient access to both crisp and fuzzy objects for fuzzy object-oriented databases since they are not efficient enough in processing both crisp and fuzzy queries. In this study, we propose a new index structure, namely a FOOD index (FI), to deal with different kinds of fuzziness in fuzzy object-oriented databases and to support multidimensional indexing. In this paper, we describe this proposed index structure and show how it supports various types of flexible queries, and evaluate its performance for exact, range, and fuzzy queries.Article Citation - WoS: 23Citation - Scopus: 34Does Domain-Driven Design Lead To Finding the Optimal Modularity of a Microservice?(Ieee-inst Electrical Electronics Engineers inc, 2021) Vural, Hulya; Koyuncu, MuratInformation systems are moving into the cloud. The new requirements enforced by cloud standards are high availability, high scalability, and a reduced mean time to recovery. Due to these new requirements, information system architecture styles are also evolving. Microservice architecture is becoming the de facto standard for developing highly modular cloud information systems. Since microservices were introduced, there has been an ongoing debate concerning how to choose the granularity of a microservice. In this study, the optimal point of granularity for microservices is examined based on coupling and cohesion values. The present study is based on two design examples generated in previous studies that applied domain-driven design in proposing microservices. Both examples are modified to generate more and less granular microservices. The coupling and cohesion values of the original examples are compared to those of the more and less granular microservices. We observe that domain-driven design has delivered a good end result for finding modular microservices.
