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Urban environmental monitoring, which provides crucial environmental information, is of great importance in various fields of urban research. The rising popularity of smart-phones and vehicles equipped with onboard sensors points out an ubiquitous computing mode for city-scale environmental monitoring, namely “crowdsensing”. This paper studies the problem that how to promote the ability of crowdsensing...
We consider sensing for cognitive network users, in particular focusing on a scenario where a primary user (PU) and a secondary user (SU) operate on the same frequency band. The SU is interested in identifying transmission opportunities when the PU is silent. We investigate how this sensing performed by the SU can be improved through modeling the PU transmission pattern with increasing accuracy. In...
Compressed sensing (CS) is a signal acquisition paradigm that utilises the finding that a small number of linear projections of a sparse signal have enough information for stable recovery. This paper develops a Bayesian CS algorithm to simultaneously recover multiple signals that follow the Type-3 joint sparse model [1], [2], where signals share a non-sparse common component and have distinct sparse...
We propose an ultra low power wideband spectrum sensing architecture by utilizing a one-bit quantization at the cognitive radio (CR) receiver. A window-based autocorrelation is utilized to provide the power spectral density of the quantized signal. Closed-form expressions are derived for the 1-bit quantized correlation. It is shown that the introduced method can still provide full information about...
This work considers a system with two energy harvesting (EH) nodes transmitting to a common destination over a random access channel. The amount of harvested energy is assumed to be random and independent over time, but correlated among the nodes possibly with respect to their relative position. A threshold-based transmission policy is developed for the maximization of the expected aggregate network...
With some recent developments in the field of wireless communication at rapid pace, users are getting a number of applications which require the precious bandwidth to work on. As the bandwidth is limited, the available spectrum is being congested day by day. Cognitive Radio System (CRS) plays an important role in such scenario. It dynamically adapts its parameters and protocols to provide unused spaces...
Precise understanding of the sea bottom characteristics and accurate identification of objects on the seabed are critical in many underwater applications. The severe multi-path along with the time varying and random reflections from the surface and the bottom of shallow waters, present an interesting and complex signal processing problem. A thin line hydrophone array, deployed from small Autonomous...
GPS and vision position sensing are complementary. Under open sky environments, GPS sensing is superior due to unimpeded strong signal reception while vision sensing suffers from the lack of unique features. In urban settings, however, vision sensing becomes superior with the abundance of unique characterizing vision features while the GPS sensing performance is hindered by obstruction and multipath...
Autonomous underwater vehicles have proven their roles as useful tools for scientific exploration and data gathering. The current state of the art in commercial vehicles involves a statical mission planning phase which does not take into account any energy or time limits. This work proposes the use of a mixed integer quadratic programming solution that maximises the utility of data gathering missions...
A novel source localization algorithm that combines the time difference of arrival (TDOA) method and a technique for the de-embedding of the propagation transfer function for non-line-of-sight (NLOS) propagation is proposed, in order to achieve accurate source localization under NLOS conditions. An iterative implementation of the method is given, and results are shown for a simple case of a single...
The information on energy expenditure of people playing various types of sports can be exploited for diagnosing their physical conditions, which helps the avoidance of their diseases and injuries during sports activities. The energy expenditure can be calculated from oxygen consumption (VO2) that can be directly measured by a VO2 meter, however, it is not reasonable for people playing sports to wear...
Spectrum sensing is the key mechanism of cognitive radios to enable spectrum awareness for improving spectrum utilization. However, the performance of the spectrum sensing is often compromised due to effects of interfering channels, multipath fading, shadowing, and receiver uncertainty issues. For improved detection, the limitation is commonly addressed by the use of cooperation in spectrum sensing,...
Copious amounts of people around the globe currently suffer from ailments in moving, which range from neurodegenerative diseases to colossal accidents. In this study, oxygenated hemoglobin of the brain is monitored using a functional near infrared spectroscopy coupled with a smart watch to detect kinetic activity. It was seen that as participants flipped their left or right hands, at different speeds,...
Embedded and invisible computing resources are paving the way to a new paradigm known as ubiquitous computing. In this paradigm, more attention needs to be paid to the development of context aware applications. Several proposals for the development of these applications are based on a context awareness loop with four phases. First, monitoring context information (Collect). Second, analyzing the collected...
Automatic food intake monitoring using wearable systems is a promising research direction in the fight against obesity and eating disorders. Previous work has indicated progress towards automatic food intake monitoring using acoustic sensors for detecting periods of food intake, swallowing and chewing detection, and discriminating between solid and liquid food intake. However, little effort has been...
Recent experimental evidence and theoretical results challenge the belief that ultra high-density EEG sensing will not yield higher spatial resolutions. It raises the exciting possibility that source-localization accuracy can be improved substantially with ultra high-density systems; however, these systems are hindered by implementation constraints in circuit volume and energy consumption. Recently,...
In this paper, we propose a low-complexity sensing algorithm based on the generalized likelihood ratio test that satisfy the complexity-performance compromise. The proposed algorithm can significantly reduce the complexity computation of the eigenvalues and enhance outstandingly the detection performance compared to the existing GLRT algorithm. Besides, the cooperative spectrum sensing has proved...
Sharing data among applications is a growing phenomenon. With the IoT, this phenomenon becomes more significant. As already studied in social networks, data sharing has the drawback of privacy risks. Authorization protocols and cryptographic systems may not be enough to ensure that user data and metadata are not used for non-legitimate purposes. There are different scenarios and several personal data...
The dynamic spectrum allocation is important to improve spectrum efficiency usage of available radio spectrum. Cognitive radio has emerged as a solution to dynamic spectrum access, due to its adaptability and re-configurability. The main problem of cognitive radio is how the secondary users can detect the holes in the frequency band of the primary users. Spectrum sensing is the main feature of cognitive...
Multispectral imaging has been studied in recent years as a means of assessing fruit firmness. Here we report on the development of a static multispectral imaging system (MSI) that was used to validate the potential of the technique for high-speed commercial grading. The system consists of a high-performance CMOS camera, four lasers, electronically controlled shutters and a location control system...
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