Cloud radio access network (CRAN) has been shown as an effective means to boost performance. Such gain stems from the intelligent management of remote heads (RRHs) in terms on/off operation mode and power consumption. Most conventional resource allocation (RA) methods, however, optimize utility without considering switching overhead RRHs adjacent time intervals. When environment becomes time-correlated, mathematical optimization is not directly applicable. In this paper, we aim energy...

Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes and capabilities has received significant attention from researchers are being deployed in a variety real-world applications. From sensors actuators improved by communication technologies to powerful computing systems utilizing advanced Artificial Intelligence (AI) algorithms have rapidly driven the development MRS, so Internet Things (IoT) MRS become new topic, namely Robots (IoRT). This paper summarises...

The continuous evolution of cellular networks has resulted in the rapid increase both mobile applications and devices Internet Vehicles. introduction multi-access edge computing method makes it possible for vehicles remote areas to offload their computational tasks, which can effectively relieve pressure local reduce delay as well. Tasks offloading multi-user is a resource competition problem, especially dynamic environments, difficult be solved by traditional algorithms. In this article, we...

This paper proposes a neural-network-based framework using Convolutional Neural Network and Long-Short Term Memory (CNN-LSTM) for detecting faults recovering signals from Hall sensors in brushless DC motors. are critical components determining the position speed of motors, these can disrupt their normal operation. Traditional fault-diagnosis methods, such as state-sensitive transition-sensitive approaches, fault-recovery vector tracking observer, have been widely used industry but be...

Accurate detection of transportation objects is pivotal for enhancing driving safety and operational efficiency. In the rapidly evolving domain systems, utilization unmanned aerial vehicles (UAVs) low-altitude detection, leveraging remotely-sensed images videos, has become increasingly vital. Addressing growing demands robust, real-time object-detection capabilities, this study introduces a lightweight, memory-efficient model specifically engineered constrained computational power resources...

This paper investigates the performance of non-orthogonal multiple access (NOMA) in vehicular networks where a base station (BS) communicates with vehicles moving away from BS single-input multiple-output. To combine signals received at antennas, diversity combining techniques such as maximal ratio (MRC) and selection (SC) are performed receiver each vehicle. However, practice, expected may not be achieved due to fact that all branches independent identically distributed (i.i.d) time. In...

A low complexity hierarchical quadrature amplitude modulation (QAM) symbol bits allocation algorithm for unequal error protection of video transmission over wireless channels is proposed in this paper. An (UEP) scheme using QAM, which takes into consideration the non-uniformly distributed importance intracoded frame (I-frame) and predictive coded (P-frame) a group pictures (GOP), first proposed. In order to optimally allocate QAM's high priority (HP), medium (MP) (LP) H.264/AVC video,...

In this paper, a low-complexity unequal error protection (UEP) of H.264/AVC coded video using adaptive hierarchical quadrature amplitude modulation (HQAM), which takes into consideration the non-uniformly distributed importance intracoded frame (I-frame) and predictive (P-frame) is proposed. Simulation results show that in terms average peak signal-to-noise ratio (average PSNR), our proposed (EEP) scheme outperforms equal by up to 5 dB

A new fast forward error correction (FEC) allocation algorithm for unequal protection (UEP) of video transmission over wireless channels is proposed in this paper. First, an UEP scheme, which takes into consideration the non-uniformly distributed importance frames a group pictures (GOP) and macroblocks frame, proposed. An enhanced propagation model, namely expected number (ENMEP) also paper to measure amount caused by errors. Finally, making use our ENMEP FEC scheme Simulation results...

Abstract Cognitive radio network and vehicular ad hoc (VANET) are recent emerging concepts in wireless networking. obtains knowledge of its operational geographical environment to manage sharing spectrum between primary secondary users, while VANET shares emergency safety messages among vehicles ensure users on the road. is employed efficient use spectrum, as well support VANET's deployment. Random increase decrease unpredictable nature VANET, high mobility, varying interference, security,...

The rapid growth of data traffic has pushed the mobile telecommunication industry towards adoption fifth generation (5G) communications. Cloud radio access network (CRAN), one 5G key enabler, facilitates fine-grained management resources by separating remote head (RRH) from baseband unit (BBU) via a highspeed front-haul link. Classical resource allocation (RA) schemes rely on numerical techniques to optimize various performance metrics. Most these works can be defined as instantaneous since...

With the increasing elderly population all around world, healthcare services to has become more important. Dementia is one of common cognitive problems among where a basic daily dining activity could be difficult for them perform. Drinking activities most important needs keep person away from dehydrating. Most existing works on recognitions are mainly based wearable sensors and sensor rich eating utensil. Although accuracy techniques high, some might reluctant wear, even forgot wear...

The recent surge of mobile subscribers and user data traffic has accelerated the telecommunication sector towards adoption fifth-generation (5G) networks. Cloud radio access network (CRAN) is a prominent framework in 5G to meet above requirements by deploying low-cost intelligent multiple distributed antennas known as remote heads (RRHs). However, achieving optimal resource allocation (RA) CRAN using traditional approach still challenging due complex structure. In this paper, we introduce...

Drinking activity recognition is not a well-researched area in the human area. In this paper, novel technique to recognize hand grasping posture drinking activities proposed. The proposed method aims overcome accuracy issue of Kinect detecting correct position during and no training required posture. Instead, directly extracts unique features grasp by using special Haar-like feature on input image. By comparing difference between total pixel values each region set thresholds, can be detected...

Vehicular communications are important to ensure emergency messages transmitted on time prevent accidents. Therefore, in recent years, various standardization bodies and automobile companies have developed vehicular ad hoc network (VANET) public road safety. The current IEEE802.11p schemes utilize only traffic type categorize priority levels. However, accidents prone occur when vehicles close distance. based the latest standard draft of IEEE1609.4 IEEE802.11p, proposed scheme, namely...

In this letter, we investigate the energy detection performance over arbitrarily correlated Nakagami-m channels under vehicle mobility. We consider that is protection range of primary user. derive probability density function received signal-to-noise ratio by means two distributions. Next, closed-form expression for average derived considering maximal combining diversity dual-antenna branches The numerical results demonstrate impact arbitrary correlation mobility in terms receiver operating...

Cloud radio access network (CRAN) facilitates resource allocation (RA) by isolating remote heads (RRHs) from baseband units (BBUs). Traditional RA algorithms save energy dynamically turning on/off RRHs and allocating power in each time slot. However, when the switching cost is considered, decisions of adjacent slots are correlated, which cannot be solved directly. Fortunately, deep reinforcement learning (DRL) can effectively model such problem, motivates us to minimize total consumption...

Automatic License Plate Recognition (ALPR) systems are crucial in extracting vehicle information. However, ALPR alone is insufficient for robust owner identification, especially the event of misidentification or covered license plates (LPs). Acknowledging significance colour enhancing identification accuracy, this paper proposes a more secure and comprehensive approach by integrating car recognition (VCR) with LP detection optical character (OCR) tasks. Unlike conventional two-stage systems,...

Face detection is a stepping stone to all facial processing systems such as face recognition with the task of determining region from input frame for applications like surveillance and law enforcement. However, computational expensive process thus, acceleration it can influence performance system. The latest Graphics Processing Unit (GPU) technology via Compute Unified Device Architecture (CUDA) has proven its capability accelerate computation intensive algorithms improve overall system...