Iraqi Journal of Information and communication technology

With the advent of smart and green cities, the development of energy-efficient smart parking systems has attracted researchers to reduce environmental pollution in smart cities due to reducing traffic congestion as well as waste of time and fuel consumption. This article investigates how to integrate the Internet of Spatial Things(IoST) with workload balancing and image processing in fog computing to build an energy-efficient smart parking system. The suggested system applies Q-Learning, a reinforcement learning method, to achieve workload balancing and then deploys image processing to detect vacant parking slots. The proposed method’s main objective of load balancing is to reduce energy consumption. The evaluation of the proposed system is done by comparing two case studies, fog-based and cloud-based IoST implementations, in the iFogSim simulator for various scenarios and scales. Moreover, it evaluates and compares the energy consumption of various devices. Experimental findings show that the devised system in fog-based IoST greatly reduces energy consumption with improves parking space availability in smart parking in contrast to the cloud-based deployment of smart car parking.

The escalating usage of light weapons in criminal and terrorist activities has necessitated the development of advanced weapon detection systems. This study centers on the application of the high-speed deep learning detection model, You Only Look Once version 7 (YOLOv7), to address the need for efficient and swift threat identification. The proposed system, trained on a self-curated dataset rich in images of various dangerous light weapons, is designed to recognize and distinguish multiple weapons simultaneously. The unique value of YOLOv7 in object and specifically weapon detection lies in its outstanding speed and accuracy, as demonstrated by certain weapon categories achieving a mean average precision (mAP) of97%. The system’s performance can potentially be further enhanced by augmenting the image dataset for each weapon category. This study, therefore, not only validates the critical importance of YOLOv7 in advancing detection methodologies but also presents a practical solution for bolstering public safety.

The Non-Orthogonal Multiple Access (NOMA) and the Orthogonal Frequency Division Multiple Access(OFDMA) are promising techniques for next-generation wireless systems. Although much attention in the literature considered these techniques, an effective combination between such systems as hybrid multiple access (HMA) needs more attention. For this reason, this paper devotes to proposing two different scenarios of HMA using multi-user OFDM (MU-OFDM) and power domain (PD) NOMA for downlink transmission to overcome the limitations of both Orthogonal Multiple Access (OMA) and NOMA. Due to the randomness of a wireless channel, different user grouping strategies and dynamic power allocation (DPA) strategies are employed to satisfy users’ requirements. The proposed systems give high flexibility utilizing bitrate allocation and user fairness. System results show superior performance to traditional OMA and NOMA systems. The achieved variety of fairness is helpful for the diversity of applications which is a principal requirement for beyond-fifth-generation (B5G) networks. The next step in this analysis is to enhance the proposed systems’ spectral efficiency (SE) by introducing beamforming for massive Multiple-Input Multiple-Output (MIMO) systems. The bit error rate (BER) result of the proposed system achieves almost the same error floor with a benefit of approximately10 dB signal to-noise ratio (SNR) when 90 resource blocks (RBs) are used.

One of the major problems of cyclostationary spectrum sensing (CSS) system in cognitive radios (CR)are the implementation complexity. One possible way to reduce CSS complexity is to use efficient algorithms for performing Fast Fourier Transformation (FFT). Over the years, a lot of different FFT algorithms have been created. This includes the Split-Radix algorithm., the Fast Hartley Transform (FHT), and slide DFT. This paper investigates the suitable FFT algorithm among the aforementioned techniques, cyclostationary feature detection (CFD)-based spectrum sensing stands out. The methods have been thoroughly compared based on computational time, object size, code size, data dependence (real or complex), and the amount of mathematical operations involved in the computations. Simulation results show that slide FFT is the suitable frequency domain transformation algorithm to use in implementing cyclostationary spectrum sensing in cognitive radios as compared to the other considered algorithms where it provides a significant reduction in FFT stage computation complexity reach to17%in SRFFT,70%in FHT and82%in SDFT while keeping the detection probability at satisfactory level.

This paper presents a novel high gain meta surface (MS) antenna. The antenna structure consists of a slotted square patch in a fractal shape, integrated with a meta surface layer stacked on Taconic RF-30 dielectric material. The individual cells are arranged periodically, creating a 5×5 layer configuration. The proposed antenna is designed with physical dimensions of 290×290 mm2and achieves a maximum gain of 13.3 dBi at a frequency of2.2 GHz. Moreover, it achieves a satisfactory minimum reflection coefficient of -10.9 dB. The design process and analysis were performed using the CST MWS simulation software. Based on the performance results obtained from this study, the suggested antenna can be considered suitable for applications in 5G communication

In recent years, traffic congestion has become one of many cities’ most significant financial and ecological concerns worldwide. It also costs citizens a substantial amount of time and fuel. Many experts believe that identifying traffic congestion characteristics is the first step in reducing traffic congestion. This study aimed to determine the extent of traffic congestion and fuel consumption at Taxila Chowk. The research’s primary methodological tools were a traffic volume survey and peak hour volume study using Aim sun software. According to this study, auto-ricks haws, bicycles, motorcycles, and trucks were the most common modes of transportation. Traffic flow is particularly heavy in the morning, noon, and evening hours. It was revealed that the H.M.C. road is the most congestion-prone route compared to the other four routes. Also, the distinctive design of rickshaws and bus stands and the misplacement of fruit and vegetable markets play a considerable role in Congestion. The level of service of the four routes is almost intolerable, and the sole P.O.F. road that offered comparable better services to city commuters is an acceptable illustration. The study has also identified the amount of fuel consumption on each route, focused on the environmental impact of Congestion due to emissions of green gasses, and provided feasible solutions in the form of alternatives

The acoustic communications are extremely challenging in underwater environments due to harsh
conditions of this kind of nature. That medium\'s harshness affects the transmission reliability which in turn
crucially requires an adoption of robust channel codes based on cooperative approaches to attain a more reliable
data communication. This study proposes a cooperative communication system based on a protograph low-density
parity check (P-LDPC) code. The system is elaborated in an Internet of underwater things (IoUT) scenario in which
a relay node is acting as a helper that provides side information to destination. Compression and channel coding
are offered by the system to cope with requirements of IoT in terms of reliable communication and compressed
data between nodes. Furthermore, an algorithm for joint source channel coding is presented based on a modified
version of offset min-sum. Moreover, layered decoding is Implemented in order to minimize number of iterations
for the P-LDPC code. The results prove that proposed design can achieve a bit error rate (BER) of 5 × 10−6 at
signal to noise ratio SNR = 8 dB for a coding rate of 1/3 and block length of 1500 bits. In addition, the proposed
system shows a coding gain of 3.6 dB when compared with a non cooperative (no relay) approach. Besides, the
proposed cooperative design can offer reduced computations versus the non cooperative system to achieve the same BER at a fixed SNR.