Analysis of integration of IoMT with blockchain: issues, challenges and solutions DOI Creative Commons
Tehseen Mazhar,

Syed Faisal Abbas Shah,

A. K. M. Sarwar Inam

et al.

Discover Internet of Things, Journal Year: 2024, Volume and Issue: 4(1)

Published: Oct. 23, 2024

The incorporation of Artificial Intelligence (AI) into the fields Neurosurgery and Neurology has transformed landscape healthcare industry. present study describes seven dimensions AI that have way providing care, diagnosing, treating patients. It exhibited unparalleled accuracy in analyzing complex medical imaging data expediting precise diagnoses neurological conditions. also enabled personalized treatment plans by harnessing patient-specific genetic information, promising more effective therapies. For instance, AI-powered surgical robots brought precision remote capabilities to neurosurgical procedures, reducing human error. In AI, machine learning models predict disease progression, optimizing resource allocation patient whereas wearable devices with provide continuous monitoring, enable early intervention for chronic accelerated drug discovery vast datasets, potentially leading breakthrough Chatbots virtual assistants powered enhance engagement adherence plans. holds promise further personalization augmented decision-making, earlier intervention, development groundbreaking treatments. mainly focuses on blockchain technology provides a reasonable understanding associated issues challenges along its solutions. will allow professionals advance field contribute towards improvement an individual's well-being when facing challenges.

Language: Английский

Global Models of Smart Cities and Potential IoT Applications: A Review DOI Creative Commons
Ahmed Hassebo,

Mohamed Tealab

IoT, Journal Year: 2023, Volume and Issue: 4(3), P. 366 - 411

Published: Aug. 31, 2023

As the world becomes increasingly urbanized, development of smart cities and deployment IoT applications will play an essential role in addressing urban challenges shaping sustainable resilient environments. However, there are also to overcome, including privacy security concerns, interoperability issues. Addressing these requires collaboration between governments, industry stakeholders, citizens ensure responsible equitable implementation technologies cities. The offers a vast array possibilities for city applications, enabling integration various devices, sensors, networks collect analyze data real time. These span across different sectors, transportation, energy management, waste public safety, healthcare, more. By leveraging technologies, can optimize their infrastructure, enhance resource allocation, improve quality life citizens. In this paper, eight global models have been proposed guide provide frameworks standards planners stakeholders design deploy solutions effectively. We detailed evaluation based on nine metrics. implement mentioned, recommendations stated overcome challenges.

Language: Английский

Citations

27
Security risk models against attacks in smart grid using big data and artificial intelligence DOI Creative Commons
Yazeed Yasin Ghadi, Tehseen Mazhar, Khursheed Aurangzeb

et al.

PeerJ Computer Science, Journal Year: 2024, Volume and Issue: 10, P. e1840 - e1840

Published: April 26, 2024

The need to update the electrical infrastructure led directly idea of smart grids (SG). Modern security technologies are almost perfect for detecting and preventing numerous attacks on grid. They unable meet challenging cyber standards, nevertheless. We many methods techniques effectively defend against threats. Therefore, a more flexible approach is required assess data sets identify hidden risks. This possible vast amounts due recent developments in artificial intelligence, machine learning, deep learning. Due adaptable base behavior models, learning can recognize new unexpected attacks. Security will be significantly improved by combining previously released with predictive analytics. Artificial Intelligence (AI) big used learn about current situation potential solutions cybersecurity issues grids. article focuses different types Furthermore, it also challenges AI It using other applications like healthcare. Finally, solution grid intelligence discussed. In end, some future directions discussed this article. Researchers graduate students audience our

Language: Английский

Citations

13
A comprehensive review of advancements in green IoT for smart grids: Paving the path to sustainability DOI Creative Commons

P. Pandiyan,

S. Saravanan,

Raju Kannadasan

et al.

Energy Reports, Journal Year: 2024, Volume and Issue: 11, P. 5504 - 5531

Published: May 22, 2024

Electricity consumption is increasing rapidly, and the limited availability of natural resources necessitates efficient energy usage. Predicting managing electricity costs challenging, leading to delays in pricing. Smart appliances Internet Things (IoT) networks offer a solution by enabling monitoring control from broadcaster side. Green IoT, also known as Things, emerges sustainable approach for communication, data management, device utilization. It leverages technologies such Wireless Sensor Networks (WSN), Cloud Computing (CC), Machine-to-Machine (M2M) Communication, Data Centres (DC), advanced metering infrastructure reduce promote environmentally friendly practices design, manufacturing, IoT optimizes processing through enhanced signal bandwidth, faster more communication. This comprehensive review explores advancements smart grids, paving path sustainability. covers energy-efficient communication protocols, intelligent renewable integration, demand response, predictive analytics, real-time monitoring. The importance edge computing fog allowing distributed intelligence emphasized. addresses challenges, opportunities presents successful case studies. Finally, concludes outlining future research avenues providing policy recommendations foster advancement IoT.

Language: Английский

Citations

12
Anomaly detection based on LSTM and autoencoders using federated learning in smart electric grid DOI Creative Commons
Rakesh Shrestha, Mohammadreza Mohammadi, Sima Sinaei

et al.

Journal of Parallel and Distributed Computing, Journal Year: 2024, Volume and Issue: 193, P. 104951 - 104951

Published: July 4, 2024

In smart electric grid systems, various sensors and Internet of Things (IoT) devices are used to collect electrical data at substations. a traditional system, multitude energy-related from substations needs be migrated central storage, such as Cloud or edge devices, for knowledge extraction that might impose severe misuse, manipulation, privacy leakage. This motivates propose anomaly detection system detect threats Federated Learning resolve the issues silos data. this article, we present framework identify anomalies in industrial gathered remote terminal deployed system. The is based on Long Short-Term Memory (LSTM) autoencoders employs Mean Standard Deviation (MSD) Median Absolute (MAD) approaches detecting anomalies. We deploy (FL) preserve generated by FL enables energy providers train shared AI models cooperatively without disclosing server. order further enhance security properties proposed framework, implemented homomorphic encryption Paillier algorithm preserving privacy. model performs better with MSD approach using HE-128 bit key providing 97% F1-score 98% accuracy K=5 low computation overhead compared HE-256 key.

Language: Английский

Citations

10
Enhancing Internet of Things security using performance gradient boosting for network intrusion detection systems DOI Creative Commons
Muhammad Ahmed, Yasser AbdelSatar, Raed Alotaibi

et al.

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 116, P. 472 - 482

Published: Jan. 5, 2025

Language: Английский

Citations

1
Cybersecurity in the AI era: analyzing the impact of machine learning on intrusion detection DOI
Huiyao Dong, Igor Kotenko

Knowledge and Information Systems, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

Language: Английский

Citations

1
IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition DOI Creative Commons
Mashael Maashi,

Huda G. Iskandar,

Mohammed Rizwanullah

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 20, 2025

Deaf and hard-of-hearing people utilize sign language recognition (SLR) to interconnect. Sign (SL) is vital for deaf individuals communicate. SL uses varied hand gestures speak words, sentences, or letters. It aids in linking the gap of communication between with hearing loss other persons. Also, it creates comfortable convey their feelings. The Internet Things (IoTs) can help persons disabilities sustain desire attain a good quality life permit them contribute economic social lives. Modern machine learning (ML) computer vision (CV) developments have allowed gesture detection decipherment. This study presents Smart Assistive Communication System Hearing-Impaired using Language Recognition Hybrid Deep Learning (SACHI-SLRHDL) methodology IoT. SACHI-SLRHDL technique aims assist impairments by creating an intelligent solution. At primary stage, utilizes bilateral filtering (BF) image pre-processing increase excellence captured images reducing noise while preserving edges. Furthermore, improved MobileNetV3 model employed feature extraction process. Moreover, convolutional neural network bidirectional gated recurrent unit attention (CNN-BiGRU-A) classifier implemented SLR Finally, attraction-repulsion optimization algorithm (AROA) adjusts hyperparameter values CNN-BiGRU-A method optimally, resulting more excellent classification performance. To exhibit significant solution method, comprehensive experimental analysis performed under Indian dataset. validation portrayed superior accuracy value 99.19% over existing techniques.

Language: Английский

Citations

1
Enhancing electricity theft detection with ADASYN-enhanced machine learning models DOI
Sheikh Muhammad Saqib, Tehseen Mazhar, Muhammad Iqbal

et al.

Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 23, 2025

Language: Английский

Citations

1
The Role of Smart Grid Technologies in Urban and Sustainable Energy Planning DOI Creative Commons
Mohamed G Moh Almihat, Josiah L. Munda

Energies, Journal Year: 2025, Volume and Issue: 18(7), P. 1618 - 1618

Published: March 24, 2025

Traditional centralized energy grids struggle to meet urban areas’ increasingly complex demands, necessitating the development of more sustainable and resilient solutions. Smart microgrids offer a decentralized approach that enhances efficiency, facilitates integration renewable sources, improves resilience. This study follows systematic review approach, analyzing literature published in peer-reviewed journals, conference proceedings, industry reports between 2011 2025. The research draws from academic publications institutions alongside regulatory reports, examining actual smart microgrid deployments San Diego, Barcelona, Seoul. Additionally, this article provides real-world case studies New York London, showcasing successful unsuccessful deployments. Brooklyn Microgrid demonstrates peer-to-peer trading, while London faces regulations funding challenges its systems. paper also explores economic policy frameworks such as public–private partnerships (PPPs), localized markets, standardized models enable adoption at scale. While PPPs provide financial infrastructural support for deployment, they introduce stakeholder alignment compliance complexities. Countries like Germany India have successfully used development, leveraging low-interest loans, government incentives, mechanisms encourage innovation technologies. In addition, examines new trends utilization AI quantum computing optimize energy, climate design before outlining future agenda focused on cybersecurity, decarbonization, inclusion technology. Contributions include modular scalable framework, innovative hybrid storage systems, performance-based model suited environment. These contributions help fill gap what is possible today needed systems create foundation cities next century.

Language: Английский

Citations

1
An enhanced coati optimization algorithm for optimizing energy management in smart grids for home appliances DOI Creative Commons

S. Balavignesh,

C. Kumar,

Ramalingam Sripriya

et al.

Energy Reports, Journal Year: 2024, Volume and Issue: 11, P. 3695 - 3720

Published: March 22, 2024

This research presents an innovative approach to energy management in smart homes, aiming efficiently regulate demands while ensuring customer loyalty. The focus is on addressing the limitations of existing demand-side (DSM) programs, which predominantly target residential sector. proposed solution introduces Adaptive Coati Optimization algorithm, optimizes device organization based Critical-Peak-Price and Real-Time-Price power payment systems. By strategically managing consumption, algorithm reduces electrical expenses peaks without compromising user convenience. study evaluates effectiveness across three operational periods (60 minutes, 12 24 minutes) align with varying needs. Overall, offers a promising for cost-efficient combining both financial benefits enhanced satisfaction. results indicate significant decrease tariffs rates, up 30%, leading 20% increase satisfaction 25% improvement cost utilization.

Language: Английский

Citations

8