Browsing by Subject "Monitoring"

Now showing 1 - 10 of 10

Open Access
AoII-optimum sampling of CTMC information sources under sampling rate constraints
(IEEE, 2024) Cosanda, Ismail; Akar, Nail; Ulukus, Sennur
We consider a sensor that samples an $N-\mathbf{state}$ continuous-time Markov chain (CTMC)-based information source process, and transmits the observed state of the source, to a remote monitor tasked with timely tracking of the source process. The mismatch between the source and monitor processes is quantified by age of incorrect information (AoII), which penalizes the mismatch as it stays longer, and our objective is to minimize the average AoII under an average sampling rate constraint. We assume a perfect reverse channel and hence the sensor has information of the estimate while initiating a transmission or preempting an ongoing transmission. First, by modeling the problem as an average cost constrained semi-Markov decision process (CSMDP), we show that the structure of the problem gives rise to an optimum threshold policy for which the sensor initiates a transmission once the AoII exceeds a threshold depending on the instantaneous values of both the source and monitor processes. However, due to the high complexity of obtaining the optimum policy in this general setting, we consider a relaxed problem where the thresholds are allowed to be dependent only on the estimate. We show that this relaxed problem can be solved with a novel CSMDP formulation based on the theory of absorbing MCs, with a computational complexity of $\mathcal{O}(N^{4})$, allowing one to obtain optimum policies for general CTMCs with over a hundred states.
Open Access
Fire detection and 3D fire propagation estimation for the protection of cultural heritage areas
(Copernicus GmbH, 2010) Dimitropoulos, K.; Köse, Kıvanç; Grammalidis, N.; Çetin, A. Enis
Beyond taking precautionary measures to avoid a forest fire, early warning and immediate response to a fire breakout are the only ways to avoid great losses and environmental and cultural heritage damages. To this end, this paper aims to present a computer vision based algorithm for wildfire detection and a 3D fire propagation estimation system. The main detection algorithm is composed of four sub-algorithms detecting (i) slow moving objects, (ii) smoke-coloured regions, (iii) rising regions, and (iv) shadow regions. After detecting a wildfire, the main focus should be the estimation of its propagation direction and speed. If the model of the vegetation and other important parameters like wind speed, slope, aspect of the ground surface, etc. are known; the propagation of fire can be estimated. This propagation can then be visualized in any 3D-GIS environment that supports KML files.
Open Access
Implantable microelectromechanical sensors for diagnostic monitoring and post-surgical prediction of bone fracture healing
(John Wiley and Sons Inc., 2015) McGilvray, K. C.; Ünal, E.; Troyer, K. L.; Santoni, B. G.; Palmer, R. H.; Easley, J. T.; Demir, Hilmi Volkan; Puttlitz, C. M.
The relationship between modern clinical diagnostic data, such as from radiographs or computed tomography, and the temporal biomechanical integrity of bone fracture healing has not been well-established. A diagnostic tool that could quantitatively describe the biomechanical stability of the fracture site in order to predict the course of healing would represent a paradigm shift in the way fracture healing is evaluated. This paper describes the development and evaluation of a wireless, biocompatible, implantable, microelectromechanical system (bioMEMS) sensor, and its implementation in a large animal (ovine) model, that utilized both normal and delayed healing variants. The in vivo data indicated that the bioMEMS sensor was capable of detecting statistically significant differences (p-value <0.04) between the two fracture healing groups as early as 21 days post-fracture. In addition, post-sacrifice micro-computed tomography, and histology data demonstrated that the two model variants represented significantly different fracture healing outcomes, providing explicit supporting evidence that the sensor has the ability to predict differential healing cascades. These data verify that the bioMEMS sensor can be used as a diagnostic tool for detecting the in vivo course of fracture healing in the acute post-treatment period. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
Open Access
Keyframe labeling technique for surveillance event classification
(S P I E - International Society for Optical Engineering, 2010) Şaykol, E.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür
The huge amount of video data generated by surveillance systems necessitates the use of automatic tools for their efficient analysis, indexing, and retrieval. Automated access to the semantic content of surveillance videos to detect anomalous events is among the basic tasks; however, due to the high variability of the audio-visual features and large size of the video input, it still remains a challenging task, though a considerable amount of research dealing with automated access to video surveillance has appeared in the literature. We propose a keyframe labeling technique, especially for indoor environments, which assigns labels to keyframes extracted by a keyframe detection algorithm, and hence transforms the input video to an event-sequence representation. This representation is used to detect unusual behaviors, such as crossover, deposit, and pickup, with the help of three separate mechanisms based on finite state automata. The keyframes are detected based on a grid-based motion representation of the moving regions, called the motion appearance mask. It has been shown through performance experiments that the keyframe labeling algorithm significantly reduces the storage requirements and yields reasonable event detection and classification performance. © 2010 Society of Photo-Optical Instrumentation Engineers.
Open Access
Monitoring progress toward fulfilling rights in early childhood under the convention on the rights of the child to improve outcomes for children and families
(Oxford University Press, 2013) Hertzman, C.; Vaghri, Z.; Arkadas-Thibert, A.
Can the United Nations Convention on the Rights of the Child (UN-CRC), to which 193 countries are signatory, be used as a tool to support developmental health in the early years? Improving early childhood development (ECD) requires finding ways for social determinants and child rights approaches to work together, which, to date, has not occurred. However, in 2005, the UN-CRC Monitoring Committee issued General Comment 7: Implementing Rights in Early Childhood (GC7) in response to the observation that children under the age of 8 were often overlooked in countries' reporting of progress toward implementing UN-CRC. This chapter shows how a commitment from the UN-CRC Monitoring Committee and key relevant international agencies (WHO, UNICEF) to a long-term program of monitoring compliance with GC7, in conjunction with monitoring of ECD developmental outcomes in all signatory countries, could help move global society toward equity in developmental health from the start of life. © Oxford University Press, 2014.
Open Access
A multi-sensor network for the protection of cultural heritage
(IEEE, 2011) Grammalidis, N.; Çetin, A. Enis; Dimitropoulos, K.; Tsalakanidou F.; Köse, Kıvanç; Günay, Osman; Gouverneur, B.; Torri, D.; Kuruoglu, E.; Tozzi, S.; Benazza, A.; Chaabane F.; Kosucu, B.; Ersoy, C.
The paper presents a novel automatic early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire. Since these areas have been treasured and tended for very long periods of time, they are usually surrounded by old and valuable vegetation or situated close to forest regions, which exposes them to an increased risk of fire. The proposed system takes advantage of recent advances in multi-sensor surveillance technologies, using optical and infrared cameras, wireless sensor networks capable of monitoring different modalities (e.g. temperature and humidity) as well as local weather stations on the deployment site. The signals collected from these sensors are transmitted to a monitoring centre, which employs intelligent computer vision and pattern recognition algorithms as well as data fusion techniques to automatically analyze sensor information. The system is capable of generating automatic warning signals for local authorities whenever a dangerous situation arises, as well as estimating the propagation of the fire based on the fuel model of the area and other important parameters such as wind speed, slope, and aspect of the ground surface. © 2011 EURASIP.
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
SLIM: A scalable location-sensitive information monitoring service
(IEEE, 2013) Bamba, B.; Wu, K.-L.; Gedik, Buğra; Liu L.
Location-sensitive information monitoring services are a centerpiece of the technology for disseminating content-rich information from massive data streams to mobile users. The key challenges for such monitoring services are characterized by the combination of spatial and non-spatial attributes being monitored and the wide spectrum of update rates. A typical example of such services is "alert me when the gas price at a gas station within 5 miles of my current location drops to $4 per gallon". Such a service needs to monitor the gas price changes in conjunction with the highly dynamic nature of location information. Scalability of such location sensitive and content rich information monitoring services in the presence of different update rates and monitoring thresholds poses a big technical challenge. In this paper, we present SLIM, a scalable location sensitive information monitoring service framework with two unique features. First, we make intelligent use of the correlation between spatial and non-spatial attributes involved in the information monitoring service requests to devise a highly scalable distributed spatial trigger evaluation engine. Second, we introduce single and multi-dimensional safe value containment techniques to efficiently perform selective distributed processing of spatial triggers to reduce the amount of unnecessary trigger evaluations. Through extensive experiments, we show that SLIM offers high scalability for location-sensitive, content-rich information monitoring services in terms of the number of information sources being monitored, number of users and monitoring requests. © 2013 IEEE.
Open Access
Timely monitoring of Markov chains under sampling rate constraints
(IEEE, 2024) Akar, Nail; Ulukus, Sennur
We study a pull-based monitoring system in which a common remote monitor queries the states of a collection of heterogeneous finite-state irreducible continuous time Markov chain (CTMC) based information sources, according to a Poisson process with different per-source sampling rates, in order to maintain remote estimates of the states. Three information freshness models are considered to quantify the accuracy of the remote estimates: fresh when equal (FWE), fresh when sampled (FWS) and fresh when close (FWC). For each of these freshness models, closed-form expressions are derived for mean information freshness for each source, as a function of the sampling rate. Using these expressions, optimum sampling rates for all sources are obtained using water-filling based optimization for maximizing the weighted sum freshness of the monitoring system, under an overall sampling rate constraint. Numerical examples are presented to validate the effectiveness of the proposed method by comparing it to several baseline sampling policies.
Open Access
What do depositors know about risk?
(Izdatel'skii Dom Natsional'nogo Issledovatel'skogo Universiteta "Vysshaya Shkola Ekonomiki", 2013) Caner, S.; Özyıldırım, S.; Ungan, A. E.
The limited success of bank supervision can be better understood by taking into consideration the country conditions and market-based measures that are effective in constraining bank risk. In the case of Russian Federation and Turkey, regulators' incentive to oversight can be further complicated and hence, it can be argued that depositors compel to select sound banks if they continue to fund intermediation by banks in two countries. In this paper, depositors' sensitivity to risk using change in deposits and the level of interest rates on deposits are tested to understand whether they can effectively limit risk-taking behavior of banks. Comparing depositors' reaction in two countries, we find differentiated reaction by depositors to bank risks. In the Russian Federation, it seems that depositors respond weakly to increased bank risks only with the possibility of withdrawing funds. However, in Turkey depositors exercise both quantity and price discipline on the banks which facilitates in identifying risky banks. Moreover, market development, effectiveness of supervisory agencies, types of banks and types of depositors are found to affect depositors' reaction against banks. The findings of this study suggest that the experiences of depositors in both countries seem to play important role in reliance to market discipline in the future.