Enabling emergent configurations in the industrial internet of things for oil and gas explorations : a survey

Abstract: Several heterogeneous, intelligent, and distributed devices can be connected to interact with one another over the Internet in what is termed internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for enhancing the production of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). Emergent configuration (EC) is a technology that can be adopted to enhance the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this paper, a survey of the concept of IoT is presented in addition to a review of IIoT systems. The application of ubiquitous computing-aided software define networking (SDN)-based EC architecture is propounded for enhancing the throughput of oil and gas production in the maritime ecosystems by managing the exploration process especially in emergency situations that involve anthropogenic oil and gas spillages

Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature

Characterization and parameterization of dynamic wireless channels over long duration using evolutionary channel parameters

The characterization and parameterization of processes that arise in many fields of science and technology are very crucial. Of particular importance are dynamic processes whose statistics are time-varying and are often modeled as stochastic processes. A typical example of such process is the wireless communication channel. Existing methods that are used to characterize and parameterize the dynamic stochastic wireless channel often consider short-term duration over which the channel statistics are invariant. Conversely, this paper presents the characterization of the dynamic wireless communication channel over a long-term duration where time/frequency channel realizations are obtained at sample intervals. To structure such channel realizations over a long duration, the idea of concatenating the 'instantaneous' channel realizations is presented. The resultant concatenated multivariable process is characterized using the concepts of process non-summability and piecewise separability. Based on these concepts, the second-order statistical parameterization of the concatenated stochastic process in both time and frequency domain is presented. The parameterization approach is based on fitting appropriate set of unit step functions that approximate the raw concatenated data using sets of evolutionary stationarity parameters. To illustrate the concepts developed in this paper, measurement-based experiments and analysis are presented and adaptively applied to improve wideband multicarrier system performance

Channel measurement and time dispersion analysis for outdoor mobile ultrawideband environment

Ultrawideband (UWB) technology offers short-range high-data transmission rates. Most researchers in recent times have focused on indoor UWB channel measurements and in instances where outdoor cases were reported, they focused on static scenarios. This paper reports on mobile outdoor channel measurements typical of roadway and recreation park Infostation scenarios. It also chronicles the delay spread as well as channel stationarity analysis of the measurement data. We carried out measurements in the 3.1{5.3 GHz frequency range in various line-of-sight scenarios. The results of this research show that the delay spread values generally decrease with increasing mobile speed. Additionally, the degree of variation in the channel statistics show that systems designed with the obtained reference parameter values will perform well on average, but with low resource utilization

Development of generic wireless channel simulator for diverse environment

The development of generic wireless channel simulator is proposed in this work. This simulator is based on the time-scale domain generalized eigenstructure for all wireless propagation channels and developed in LabVIEW®. It is envisaged that such simulator will be able to serve as all-in-one system for the evaluation of the channel characteristics and transceiver performance for almost all contemporary communication channels and systems

Experimental characterization of an UWB channel in outdoor environment

An experimental characterization of the ultrawide-band (UWB) channel in an outdoor environment over the frequency range from 3.1 GHz to 5.3 GHz is presented in this paper. The measurements are taken in time domain and line-of-sight (LOS). The statistical model for the delay spread is characterized and there is no correlation between delay spread and transmitter receiver distance. Different statistical distributions for the delay spread are investigated. The reflective nature of this environment is shown in the Ricean K-factor

Hybrid channel estimation for LTE downlink

In this paper, a new channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) technique in the long-term evolution (LTE). This method combines three different type channel estimations which is termed Hybrid Linear Mean Square Error(HLMSE). This proposed estimator is a hybrid of the least square(LS)estimator block for low mobility, LS fast fading estimator for moderate mobility and linear minimum mean square error (LMMSE)estimator for high mobility. The performance of the HLMSE estimator compared with LS in terms of throughput and mean square error(MSE) outperforms the LS in both throughput and MSE

Hybrid channel estimation technique with reduced complexity for LTE downlink

This paper proposes a hybrid channel estimation (CE) method for orthogonal frequency division multiplexing technique for use in long-term evolution technology with application suitable for highly mobile devices, such as in passenger trains. This method, termed hybrid linear (HL) estimator, combines three different CE algorithms, namely, blocked-based least square (B-LS), fast fading-based LS (FF-LS), and linear minimum mean square error (LMMSE) estimators. This proposed estimation adaptively employs a given algorithm based on the mobility condition of the receiver. The computational complexity of HL estimator is reduced nearly to the half compared with LMMSE. The performance of proposed estimator is compared with the B-LS and FF-LS in terms of throughput and mean square error (MSE). Results show that the HL performs better than the B-LS and FF-LS in both MSE and throughput. The proposed method offers a good bit-error-rate for different velocitie