This letter proposes a group key distribution scheme using smart contract-based blockchain technology. The contract’s functions allow for securely distributing the session key, following initial legitimacy detection public infrastructure-based authentication. For message authentication, we propose lightweight symmetric cryptography-based signature method, supporting security and privacy requirements of vehicular ad hoc networks (VANETs). Our discussion examined scheme’s robustness against...

Abstract Wireless sensing is the state-of-the-art technique for next generation health activity monitoring. Smart homes and healthcare centres have a demand multi-subject monitoring to cater future requirements. 5 G -sensing coupled with deep learning models has enabled smart systems, which potential classify multiple activities based on variations in channel state information (CSI) of wireless signals. Proposed first 5G-enabled system operating at 3.75 GHz multi-subject, in-home monitoring,...

By 2050, experts estimate that the agricultural produce must increase by 60%–70% to meet needs of ever increasing population world. To this aim, concept precision agriculture or smart farming has recently been coined. The idea is well represented as a management system, having ability monitor, observe, sense, measure and control health water contents in plants at nano-scale crops macro-scale. goal maximise production while preserving vital resources. combination terahertz (THz) based sensing...

Intelligent transportation systems are an emerging technology that facilitates real-time vehicle-to-everything communication. Hence, securing and authenticating data packets for intra- inter-vehicle communication fundamental security services in vehicular ad-hoc networks (VANETs). However, public-key cryptography (PKC) is commonly used signature-based authentication, which consumes significant computation resources bandwidth signatures generation verification, key distribution. Therefore,...

This review paper is a foundational resource for power distribution and management decisions, thoroughly examining short-term load forecasting (STLF) models within systems. The study categorizes these into three groups: statistical approaches, intelligent-computing-based methods, hybrid models. Performance indicators are compared, revealing the superiority of heuristic search population-based optimization learning algorithms integrated with artificial neural networks (ANNs) STLF. However,...

This article provides a new benchmark dataset for 3-D point cloud classification in which the manually labeled human activity data exceeds 100 clouds per frame and is capable of meeting training needs data-intensive learning approaches. In this study, case study considered evaluating using deep long short-term memory (LSTM) neural network, demonstrated significant performance improvement over state-of-the-art recognition (HAR) area. To date, numerous types collection devices have been used...

Intelligent transportation systems are pivotal in enhancing road safety by enabling intra-vehicle communication. Due to the nature of wireless communication link, several potential risks attacks exist, including impersonation, modification, and replay. To ensure security vehicular ad hoc networks (VANETs) against malicious activities, secure data exchange between inter-communicating terminals, specifically vehicle-to-everything (V2X) communication, becomes a critical technological challenge...

Solar forecasting plays a key part in the renewable energy transition. Major challenges, related to load balancing and grid stability, emerge when high percentage of is provided by renewables. These can be tackled new management strategies guided power forecasts. This paper presents data-driven contextual optimisation (DCF) algorithm for solar irradiance that was comprehensively validated using short- long-term predictions, three US cities: Denver, Boston, Seattle. Moreover, step-by-step...

Vehicle-to-everything (V2X) communication is expected to offer users available and ultra-reliable transmission, particularly for critical applications related safety autonomy. In this context, establishing a secure resilient authentication process with low latency high functionality may not be achieved using conventional cryptographic methodologies due their significant computation costs. Recent research has focused on employing the physical (PHY) characteristics of wireless channels develop...

The increasing demand for considering multisensor data fusion technology has drawn attention precise human activity recognition (HAR) over standalone due to its reliability and robustness. This article presents a framework that fuses from multiple sensing systems applies neuromorphic computing sense classify activities. is collected by utilizing inertial measurement unit (IMU) sensors, software-defined radios, radars, feature extraction selection are performed on the data. For each of...

Smart building technologies transform buildings into agile, sustainable, and health-conscious ecosystems by leveraging IoT platforms. In this regard, we have developed a Persuasive Energy Conscious Network (PECN) at the University of Glasgow to understand user-centric energy consumption patterns in an agile workspace. PECN consists desk-level monitoring sensors that enable us develop models can be exploited characterize normal usage behavior office occupant. study, make use staked long...

Abstract Reconfigurable Intelligent Surfaces have recently emerged as a revolutionary next-generation wireless networks paradigm that harnesses engineered electromagnetic environments to reshape radio wave propagation. Pioneering research presented in this article establishes the viability of Surfaces-enhanced indoor localisation and charts roadmap for its integration into network architectures. Here, we present comprehensive experimental analysis Surfaces-enabled scheme evaluates accuracy...

Non-invasive indoor human activity detection using radio waves has attracted the interest of researchers, contributing to a range new applications including smart healthcare. Localisation activities can assist in developing advanced healthcare systems able identify location patients. Radio frequencies have been shown numerous studies as non-invasive method activity. This is achieved by observing signal propagation described Channel State Information (CSI). paper presents experimental results...

The increasing popularity of Unmanned Aerial Vehicles (UAV) has resulted in exponential growth the market owing to numerous applications that have been facilitated by advances battery technology and wireless communications. Given successes UAVs thus far, researchers are already gearing towards aerial transport systems consist dense deployment both Personal (PAVs) with human passengers. Although fifth-generation mobile network (5G) key performance indicators optimised support drone use cases...

This study focuses on improving the sustainability of electrical supply in healthcare system UK, to contribute current efforts made towards 2050 net-zero carbon target. As a case study, we propose grid-connected hybrid renewable energy (HRES) for hospital south-east England. Electrical consumption data were gathered from five wards period one year. PV-battery-grid architecture was selected ensure practical execution through installation PV arrays roof facility. Selection optimal conducted...

Battery energy storage systems and multilevel converters are the most essential constituents of modern medium voltage networks. In this regard, modular converter offers numerous advantages over other converters. The key feature is its capability to integrate small battery packs in a split manner, given opportunity submodules operate at considerably low voltages. paper, we focus on study potential SMs for based system while, keeping view inconsistency secondary batteries. Although, selecting...

Wireless communication has become an integral part of modern vehicles. However, securing the information exchanged between interconnected terminals poses a significant challenge. Effective security solutions should be computationally inexpensive, ultra-reliable, and capable operating in any wireless propagation environment. Physical layer secret key generation emerged as promising technique, which leverages inherent randomness wireless-channel responses amplitude phase to generate...

This paper presents a smart diagnostic framework for dental smile analysis. To accurately and efficiently identify esthetic issues from single image of smile, convolutional neural network (CNN) was trained. overcome the limitations scarce data, diffusion model employed to generate images in addition manually curated data. The CNN trained evaluated on three datasets: all real images, generated hybrid dataset comprising equal proportions real-to-generated images. All models demonstrate...