Machine learning (ML) is a branch of artificial intelligence (AI) that has been successfully applied in variety remote sensing applications, including geophysical information retrieval such as soil moisture content (SMC). Deep (DL) subfield ML uses models with complex structures to solve prediction problems higher performance than traditional ML. In this study, framework based on DL was developed for SMC retrieval. For purpose, sample dataset built, which included synthetic aperture radar...

Smart cities are now embracing the new frontier of urban living, with advanced technology being used to enhance quality life for residents. Many these have developed transportation systems that improve efficiency and sustainability, as well quality. Integrating cutting-edge data-driven solutions improves safety, reduces environmental impact, optimizes traffic flow during peak hours, congestion. Intelligent consist many systems, one which is sign detection. This type system utilizes...

Abstract In designing a modern home with focus on comfort of resident and energy usage optimization simultaneously, the rise Internet Things incorporation sensors technology plays vital role these days. The first foremost task is to predict consumption in based available data. This study investigates integration artificial neural networks smart improve prediction efficiency, compromising occupant. A dynamic model an network designed this which artificially controls light, heating process...

Mobile Ad Hoc Networks (MANETs) are decentralized wireless networks characterized by dynamic topologies and the absence of fixed infrastructure. These unique features make MANETs critical for applications such as disaster recovery, military operations, IoT systems. However, they also pose significant challenges efficient effective routing. This study evaluates performance eight MANET routing protocols: Optimized Link State Routing (OLSR), Destination-Sequenced Distance Vector (DSDV),...

The rapid advancement in self-driving and autonomous vehicles (AVs) integrated with artificial intelligence (AI) technology demands not only precision but also output transparency. In this paper, we propose a novel hybrid explainable AI (XAI) framework that combines local interpretable model-agnostic explanations (LIME) Shapley additive (SHAP). Our the globality of SHAP low computational requirements LIME, creating balanced approach for onboard deployment enhanced We evaluate proposed on...

After the advent of 5th generation (5G) and 6th (6G) cellular networks, complexity managing real-time signal interference has increased in dense dynamic environments. Traditional techniques, such as frequency reuse allocation, while effective, lack robust adaptability transparency needed to reduce advanced communication networks. This paper introduces a novel approach that fuses large language models (LLMs) Explainable Artificial Intelligence (XAI) mitigate enhance management mathematical...

IPv6 Routing Protocol for Low Power and Lossy Networks (RPL), is based on building an acyclic graph where Objective Function (OF) responsible selecting the preferred parent during Destination Oriented Directed Acyclic Graph (DODAG) construction. In this paper, we propose a new multi-metric OF Analytical Hierarchy Processes decision masking algorithm. AHP-OF, combines set of routing metrics aiming to provide best RPL satisfy different application requirements LLN s such as reliable...

The field of scene recognition, which lies at the crossroads computer vision and artificial intelligence, has experienced notable progress because scholarly pursuits. This article introduces a novel methodology for recognition by combining convolutional neural networks (CNNs) with feature selection techniques based on mutual information (MI). main goal our study is to address limitations inherent in conventional unimodal methods, aim improving precision dependability classification. focus...

WiFi networks carrying IPv6 traffic with Proxy-based mobility support are to considered here. The performance of the handover function is first tested through analysis effects packet size and inter-arrival times. Then, sequence events occurring during period scrutinized observe drawbacks that led obtained results. Finally, some suggestions given decrease number dropped packets, thus improving system.

In this paper, we evaluate the performance of RPL (IPv6 Routing Protocol for Low Power and Lossy Networks) based on Objective Function being used to construct Destination Oriented Directed Acyclic Graph (DODAG). Using Cooja simulator, compared Zero (OF0) with Minimum Rank Hysteresis (MRHOF) in terms average power consumption, packet loss ratio, end-to-end latency. Our study shows that performs better ratio latency when MRHOF is as an objective function. However, consumption noticeably higher OF0.

This study presents an advanced framework integrating LLAMA_V2, a large language model, into Open Radio Access Network (O-RAN) systems. The focus is on efficient network slicing for various services. Sensors in IoT devices generate continuous data streams, enabling resource allocation through O-RAN's dynamic and LLAMA_V2's optimization. LLAMA_V2 was selected its superior ability to capture complex dynamics, surpassing traditional AI/ML models. proposed method combines sophisticated...

Handover characteristics over WiMAX networks using PMIPv6 are studied. A special look is taken at the QoS provisioning, that includes an analysis of effects packet size and inter-arrival times on average delay, dropping rate, fragmentation rate. Then, this followed by a thorough sequence packets exchange during handover period. Finally, some changes in PMIpv6 protocol ought to improve system performance suggested, including means decreasing number fragmented packets.