Browsing by Author "Erden, F."

Now showing 1 - 11 of 11

Open Access
Contact-free measurement of respiratory rate using infrared and vibration sensors
(Elsevier BV, 2015) Erden, F.; Alkar, A. Z.; Çetin, A. Enis
Respiratory rate is an essential parameter in many practical applications such as apnea detection, patient monitoring, and elderly people monitoring. In this paper, we describe a novel method and a contact-free multi-modal system which is capable of detecting human breathing activity. The multimodal system, which uses both differential pyro-electric infrared (PIR) and vibration sensors, can also estimate the respiratory rate. Vibration sensors pick up small vibrations due to the breathing activity. Similarly, PIR sensors pick up the thoracic movements. Sensor signals are sampled using a microprocessor board and analyzed on a laptop computer. Sensor signals are processed using wavelet analysis and empirical mode decomposition (EMD). Since breathing is almost periodic, a new multi-modal average magnitude difference function (AMDF) is used to detect the periodicity and the period in the processed signals. By fusing the data of two different types of sensors we achieve a more robust and reliable contact-free human breathing activity detection system compared to systems using only one specific type of sensors.
Open Access
Diferansiyel PIR algılayıcılarla dalgacık tabanlı alev tespiti
(IEEE, 2012-04) Erden, F.; Töreyin, B. U.; Soyer, E. B.; İnaç, İ.; Günay, O.; Köse, K.; Çetin, A. Enis
Bu makalede, diferansiyel kızılberisi algılayıcı (PIR) kullanılarak geliştirilen bir alev tespit sistemi önerilmektedir. Diferansiyel kızılberisi algılayıcılar, yalnızca görüş alanlarındaki ani sıcaklık değişikliklerine duyarlıdır ve zamanla değişen sinyaller üretir. Algılayıcı sinyaline ait dalgacık dönüşümü, öznitelik çıkarmak için kullanılır ve bu öznitelik vektörü hızlı titreşen kontrolsüz bir ateşin alevi ve bir kişinin yürümesi olaylarıyla eğitilmiş Markov modellerine sokulur. En yüksek olasılıkla sonuçlanan modele karar verilir. Karşılaştırmalı sonuçlar, sistemin geniş odalarda ateş tespiti için kullanılabileceğini düşündürmektedir.
Open Access
Disk scheduling with shortest cumulative access time first algorithms
(TÜBITAK, 2017) Akar, Nail; Tunç, Ç.; Gaertner, M.; Erden, F.
A new class of scheduling algorithms is proposed for disk drive scheduling. As opposed to choosing the request with the shortest access time in conventional shortest access time first (SATF) algorithms, we choose an ordered sequence of pending I/O requests at the scheduling instant with the shortest cumulative access time. Additionally, we introduce flexibility for forthcoming requests to alter the chosen sequence. Simulation results are provided to validate the effectiveness of the proposed disk scheduler. Throughput gains of 3% and above are shown to be attainable, although this occurs at the expense of increased computational complexity.
Open Access
Distributed Control of PEV Charging Based on Energy Demand Forecast
(IEEE Computer Society, 2018) Kisacikoglu, M. C.; Erden, F.; Erdogan, N.
This paper presents a new distributed smart charging strategy for grid integration of plug-in electric vehicles (PEVs). The main goal is to smooth the daily grid load profile while ensuring that each PEV has a desired state of charge level at the time of departure. Communication and computational overhead, and PEV user privacy are also considered during the development of the proposed strategy. It consists of two stages: 1) an offline process to estimate a reference operating power level based on the forecasted mobility energy demand and base loading profile, and 2) a real-time process to determine the charging power for each PEV so that the aggregated load tracks the reference loading level. Tests are carried out both on primary and secondary distribution networks for different heuristic charging scenarios and PEV penetration levels. Results are compared to that of the optimal solution and other state-of-the-art techniques in terms of variance and peak values, and shown to be competitive. Finally, a real vehicle test implementation is done using a commercial-of-the-shelf charging station and an electric vehicle.
Open Access
A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system
(Springer Heidelberg, 2018) Erdogan, N.; Erden, F.; Kisacikoglu, M.
This study focuses on the potential role of plug-in electric vehicles (PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid (V2G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2G process is first formulated as an optimal control problem. Then, a two-stage V2G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm.
Open Access
Hand gesture based remote control system using infrared sensors and a camera
(Institute of Electrical and Electronics Engineers, 2014) Erden, F.; Çetin, A.
In this paper, a multimodal hand gesture detection and recognition system using differential Pyroelectric Infrared (PIR) sensors and a regular camera is described. Any movement within the viewing range of the differential PIR sensors are first detected by the sensors and then checked if it is due to a hand gesture or not by video analysis. If the movement is due to a hand, one-dimensional continuous-time signals extracted from the PIR sensors are used to classify/recognize the hand movements in real-time. Classification of different hand gestures by using the differential PIR sensors is carried out by a new winner-takeall (WTA) hash based recognition method. Jaccard distance is used to compare the WTA hash codes extracted from 1-D differential infrared sensor signals. It is experimentally shown that the multimodal system achieves higher recognition rates than the system based on only the on/off decisions of the analog circuitry of the PIR sensors.
Open Access
Period estimation of an almost periodic signal using persistent homology with application to respiratory rate measurement
(Institute of Electrical and Electronics Engineers Inc., 2017) Erden, F.; Çetin, A. Enis
Time-frequency techniques have difficulties in yielding efficient online algorithms for almost periodic signals. We describe a new topological method to find the period of signals that have an almost periodic waveform. Proposed method is applied to signals received from a pyro-electric infrared sensor array for the online estimation of the respiratory rate (RR) of a person. Timevarying analog signals captured from the sensors exhibit an almost periodic behavior due to repetitive nature of breathing activity. Sensor signals are transformed into two-dimensional point clouds with a technique that allows preserving the period information. Features, which represent the harmonic structures in the sensor signals, are detected by applying persistent homology and the RR is estimated based on the persistence barcode of the first Betti number. Experiments have been carried out to show that our method makes reliable estimates of the RR.
Open Access
A robust system for counting people using an infrared sensor and a camera
(Elsevier BV, 2015) Erden, F.; Alkar, A. Z.; Çetin, A. Enis
In this paper, a multi-modal solution to the people counting problem in a given area is described. The multi-modal system consists of a differential pyro-electric infrared (PIR) sensor and a camera. Faces in the surveillance area are detected by the camera with the aim of counting people using cascaded AdaBoost classifiers. Due to the imprecise results produced by the camera-only system, an additional differential PIR sensor is integrated to the camera. Two types of human motion: (i) entry to and exit from the surveillance area and (ii) ordinary activities in that area are distinguished by the PIR sensor using a Markovian decision algorithm. The wavelet transform of the continuous-time real-valued signal received from the PIR sensor circuit is used for feature extraction from the sensor signal. Wavelet parameters are then fed to a set of Markov models representing the two motion classes. The affiliation of a test signal is decided as the class of the model yielding higher probability. People counting results produced by the camera are then corrected by utilizing the additional information obtained from the PIR sensor signal analysis. With the proof of concept built, it is shown that the multi-modal system can reduce false alarms of the camera-only system and determines the number of people watching a TV set in a more robust manner.
Open Access
Sensors in assisted living: a survey of signal and image processing methods
(Institute of Electrical and Electronics Engineers, 2016-03) Erden, F.; Velipasalar, S.; Alkar, A. Z.; Çetin, A. Enis
Our society will face a notable demographic shift in the near future. According to a United Nations report, the ratio of the elderly population (aged 60 years or older) to the overall population increased from 9.2% in 1990 to 11.7% in 2013 and is expected to reach 21.1% by 2050 [1]. According to the same report, 40% of older people live independently in their own homes. This ratio is about 75% in the developed countries. These facts will result in many societal challenges as well as changes in the health-care system, such as an increase in diseases and health-care costs, a shortage of caregivers, and a rise in the number of individuals unable to live independently [2]. Thus, it is imperative to develop ambient intelligence-based assisted living (AL) tools that help elderly people live independently in their homes. The recent developments in sensor technology and decreasing sensor costs have made the deployment of various sensors in various combinations viable, including static setups as well as wearable sensors. This article presents a survey that concentrates on the signal processing methods employed with different types of sensors. The types of sensors covered are pyro-electric infrared (PIR) and vibration sensors, accelerometers, cameras, depth sensors, and microphones.
Open Access
Video-Based FLame detection for the protection of cultural heritage
(SAGE, 2013) Dimitropoulos, K.; Gunay, O.; Kose, K.; Erden, F.; Chaabane, F.; Tsalakanidou, F.; Grammalidis, N.; Çetin, A. Enis
The majority of cultural heritage and archaeological sites, especiallyin the Mediterranean region, are covered with vegetation, whichincreases the risk of fires. These fires may also break out and spreadtowards nearby forests and other wooded land, or conversely start innearby forests and spread to archaeological sites. Beyond takingprecautionary measures to avoid a forest fire, early warning andimmediate response to a fire breakout are the only ways to avoidgreat losses and environmental and cultural heritage damages. Theuse of terrestrial systems, typically based on video cameras, iscurrently the most promising solution for advanced automatic wildfiresurveillance and monitoring due to its low cost and short responsetime. Early and accurate detection and localization of flame is anessential requirement of these systems, however, it remains achallenging issue due to the fact that many natural objects havesimilar characteristics with fire. This paper presents and comparesthree video-based flame detection techniques, which weredeveloped within the FIRESENSE EU research project, taking intoaccount the chaotic and complex nature of the fire phenomenonand the large variations of flame appearance in video. Experimentalresults show that the proposed methods provide high fire detectionrates with reasonable false alarm ratios.
Open Access
Wavelet based flickering flame detector using differential PIR sensors
(Elsevier, 2012-07-06) Erden, F.; Toreyin, B. U.; Soyer, E. B.; Inac, I.; Gunay, O.; Kose, K.; Çetin, A. Enis
A Pyro-electric Infrared (PIR) sensor based flame detection system is proposed using a Markovian decision algorithm. A differential PIR sensor is only sensitive to sudden temperature variations within its viewing range and it produces a time-varying signal. The wavelet transform of the PIR sensor signal is used for feature extraction from sensor signal and wavelet parameters are fed to a set of Markov models corresponding to the flame flicker process of an uncontrolled fire, ordinary activity of human beings and other objects. The final decision is reached based on the model yielding the highest probability among others. Comparative results show that the system can be used for fire detection in large rooms.