Browsing by Author "Erden, Fatih"

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Open Access
Breathing detection based on the topological features of IR sensor and accelerometer signals
(IEEE, 2017) Erden, Fatih; Çetin, A. Enis
This paper describes a non-contact breathing detection system using a pyro-electric infrared (PIR) sensor and an accelerometer. The multi-sensor system can be used to detect the respiratory disorders. A PIR sensor is placed onto a stand near a bed and an accelerometer is placed on the mattress. We recently developed a PIR sensor which is capable of producing 1-D time-varying signals corresponding to the motions in its field of view. The PIR sensor signal due to the thoracic movements turns out to be an almost periodic signal. Similarly, the accelerometer produces an almost periodic signal in response to vibrations in bed. Sensor signals are processed using a topological approach. Point clouds are constructed from the delay-coordinate embedding of the time series sensor data first. Then, periodic structures in the point clouds are detected using persistent homology. The sensors, with the proposed method, complement each other to produce more accurate decisions in different lying positions.
Open Access
Development of a DC fast charging station model for use with EV infrastructure projection tool
(Institute of Electrical and Electronics Engineers, 2018) Ucer, E. Y.; Kisacikoglu, M. C.; Erden, Fatih; Meintz, A.; Rames, C.
The deployment of public charging infrastructure networks has been a major factor in enabling electric vehicle (EV) technology transition, and must continue to support the adoption of this technology. DC fast charging (DCFC) increases customer convenience by lowering charging time, enables long-distance EV travel, and could allow the electrification of high-mileage fleets. Yet, high capital costs and uneven power demand have been major challenges to the widespread deployment of DCFC stations. There is a need to better understand DCFC stations' loading, utilization, and customer service quality (i.e. queuing time, charging duration, and queue length). This study aims to analyze these aspects using one million vehicle-days of travel data within the Columbus, OH, region. Monte Carlo analysis is carried out in three types of areas - urban, suburban, and rural- to quantify the effect of uncertain parameters on DCFC station loading and service quality.
Open Access
Flame detection for video-based early fire warning for the protection of cultural heritage
(2012-10-11) Dimitropoulos, K.; Günay, Osman; Köse, Kıvanç; Erden, Fatih; Chaabene, F.; Tsalakanidou, F.; Grammalidis, N.; Çetin, Enis
Cultural heritage and archaeological sites are exposed to the risk of fire and early warning is the only way to avoid losses and damages. The use of terrestrial systems, typically based on video cameras, is currently the most promising solution for advanced automatic wildfire surveillance and monitoring. Video cameras are sensitive in visible spectra and can be used either for flame or smoke detection. This paper presents and compares three video-based flame detection techniques, which were developed within the FIRESENSE EU research project. © 2012 Springer-Verlag Berlin Heidelberg.
Open Access
iki diferansiyel PIR algılayıcı ve bir kamera yardımıyla el hareketlerinin sınıflandırılması
(IEEE, 2014-04) Erden, Fatih; Bingol, A. S.; Çetin, A. Enis
Bu makalede, iki diferansiyel kızılberisi algılayıcı (PIR) ve bir kamera kullanılarak geliştirilen el jestleri algılama ve sınıflandırma sistemi tanıtılmaktadır. İzlenen alanda diferansiyel PIR algılayıcı dizisi ile hareket varlığı araştırılır. Bir hareket algılanması durumunda kamera yardımıyla söz konusu hareketin el olup olmadığına, el ise çok modlu sistem verilerinin birlikte değerlendirilmesiyle hareketin hangi tanımlı sınıfa ait olduğuna karar verilir. Kamera ile el jestleri algılama ve hareketleri sınıflandırma aşamasında ten algılama ve dışbükey zarf-gedik hesaplama yöntemleri kullanılır. Farklı el hareketlerinin PIR algılayıcı verileri yardımıyla sınıflandırılması Winner-Take-All (WTA) imza metoduyla gerçekleştirilir. Bu makalenin temel katkısı, WTA imza kodlarının tek boyutlu sinyallerin sınıflandırılmasında kullanılabileceğini ve çoklu algılayıcı tümleştirmesiyle jestleri tanıma sonuçlarının geliştirilebileceğini göstermektir.
Open Access
Respiratory rate monitoring using infrared sensors
(IEEE, 2016) Erden, Fatih; Çetin, A. Enis
Respiratory rate is an essential parameter in many practical applications such as patient and elderly people monitoring. In this paper, a novel contact-free system is introduced to detect the human breathing activity. The system, which consists of two pyro-electric infrared (PIR) sensors, is capable of estimating the respiratory rate and detecting the sleep apnea. Sensors' signals corresponding to the thoracic movements of a human being are sampled using a microprocessor and analyzed on a general-purpose computer. Sampled signals are processed using empirical mode decomposition (EMD) and a new average magnitude difference function (AMDF) is used to detect the periodicity and the period of the processed signals. The resulting period, by using the fact that breathing is almost a periodic activity, is monitored as the respiratory rate. The new AMDF provides a way to fuse the data from the multiple sensors and generate a more reliable estimation of the respiratory rate.
Open Access
VOC gas leak detection using pyro-electric infrared sensors
(IEEE, 2010) Erden, Fatih; Soyer, E. B.; Toreyin, B. U.; Çetin, A. Enis
In this paper, we propose a novel method for detecting and monitoring Volatile Organic Compounds (VOC) gas leaks by using a Pyro-electric (or Passive) Infrared (PIR) sensor whose spectral range intersects with the absorption bands of VOC gases. A continuous time analog signal is obtained from the PIR sensor. This signal is discretized and analyzed in real time. Feature parameters are extracted in wavelet domain and classified using a Markov Model (MM) based classifier. Experimental results are presented. ©2010 IEEE.
Open Access
Volatile organic compounds (VOC) gas leak detection by using infrared sensors
(2009) Erden, Fatih
Advances in technology and industry leads to a rise in the living standards of people. However, this has also introduced a variety of serious problems, such as the undesired release of combustible and toxic gases which have become an essential part of domestic and industrial life. Therefore, detection and monitoring of VOC gases have become a major problem in recent years. In this thesis, we propose novel methods for detection and monitoring VOC gas leaks by using a Pyro-electric (or Passive) Infrared (PIR) sensor and a thermopile sensor. A continuous time analog signal is obtained for both of the sensors and sent to a PC for signal processing. While using the PIR sensor, we have Hidden Markov Models (HMM) for each type of event to be classified. Then, by using a probabilistic approach we determine which class any test signal belongs to. In the case of a thermopile sensor, in addition to Hidden Markov Modeling method, we also use a method based on the period of the sensor signal. The frequency of the output signal of the thermopile sensor increases with the presence of VOC gas leak. By using this fact, we control whether the period of a test signal is below a predefined threshold or not. If it is, our system triggers an alarm. Moreover, we present different methods to find the periods of a given signal.