Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110030 - 110030
Published: Jan. 29, 2025
Language: Английский
Environmental Science and Ecotechnology, Journal Year: 2024, Volume and Issue: 20, P. 100433 - 100433
Published: May 17, 2024
In the dynamic landscape of sustainable smart cities, emerging computational technologies and models are reshaping data-driven planning strategies, practices, approaches, paving way for attaining environmental sustainability goals. This transformative wave signals a fundamental shift — marked by synergistic operation artificial intelligence (AI), things (AIoT), urban digital twin (UDT) technologies. While previous research has largely explored AI, AIoT, UDT in isolation, significant knowledge gap exists regarding their interplay, collaborative integration, collective impact on context cities. To address this gap, study conducts comprehensive systematic review to uncover intricate interactions among these interconnected technologies, models, domains while elucidating nuanced dynamics untapped synergies complex ecosystem Central four guiding questions: What theoretical practical foundations underpin convergence UDT, planning, how can components be synthesized into novel framework? How does integrating AI AIoT reshape improve performance cities? augment capabilities enhance processes challenges barriers arise implementing what strategies devised surmount or mitigate them? Methodologically, involves rigorous analysis synthesis studies published between January 2019 December 2023, comprising an extensive body literature totaling 185 studies. The findings surpass mere interdisciplinary enrichment, offering valuable insights potential advance development practices. By enhancing processes, integrated offer innovative solutions challenges. However, endeavor is fraught with formidable complexities that require careful navigation mitigation achieve desired outcomes. serves as reference guide, spurring groundbreaking endeavors, stimulating implementations, informing strategic initiatives, shaping policy formulations sustainable, development. These have profound implications researchers, practitioners, policymakers, providing roadmap fostering resiliently designed, technologically advanced, environmentally conscious environments.
Language: Английский
Citations
38
Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102132 - 102132
Published: April 21, 2024
Multiple industries have been revolutionized by the incorporation of data science advancements into intelligent environment technologies, specifically in context smart grids. Smart grids offer a dynamic and efficient framework for management optimization electricity generation, distribution, consumption, thanks to developments big analytics. This review delves integration Grid applications Big Data analytics reviewing 25 papers screened with PRISMA standard. The paper matter encompasses critical domains including adaptive energy management, canonical correlation analysis, novel methodologies blockchain machine learning. emphasizes contributions efficiency, security, sustainability means rigorous methodology.
Language: Английский
Citations
22
Sensors, Journal Year: 2024, Volume and Issue: 24(9), P. 2793 - 2793
Published: April 27, 2024
This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore integration environments with sensor technologies, health capabilities, and location-based services, focusing on their impacts objectives outcomes. work analyzes foundational encompassing Internet Things (IoT), Medical (IoMT), machine learning (ML), artificial intelligence (AI), that underpin functionalities also examine unique characteristics homes hospitals, highlighting to revolutionize through remote patient monitoring, telemedicine, real-time data sharing. The presents a novel solution framework leveraging twins address both needs user requirements. incorporates wearable devices, AI-driven analytics, proof-of-concept application. Furthermore, we role services (LBS) environments, emphasizing enhance personalized interventions emergency response capabilities. By analyzing technical advancements technologies applications, this contributes valuable insights evolving landscape for healthcare. identify opportunities challenges associated emerging field highlight need further research fully realize its improve well-being.
Language: Английский
Citations
17
Electronics, Journal Year: 2023, Volume and Issue: 12(24), P. 4925 - 4925
Published: Dec. 7, 2023
The internet of things (IoT) has emerged as a pivotal technological paradigm facilitating interconnected and intelligent devices across multifarious domains. proliferation IoT resulted in an unprecedented surge data, presenting formidable challenges concerning efficient processing, meaningful analysis, informed decision making. Deep-learning (DL) methodologies, notably convolutional neural networks (CNNs), recurrent (RNNs), deep-belief (DBNs), have demonstrated significant efficacy mitigating these by furnishing robust tools for learning extraction insights from vast diverse IoT-generated data. This survey article offers comprehensive meticulous examination recent scholarly endeavors encompassing the amalgamation deep-learning techniques within landscape. Our scrutiny encompasses extensive exploration models, expounding on their architectures applications domains, including but not limited to smart cities, healthcare informatics, surveillance applications. We proffer into prospective research trajectories, discerning exigency innovative solutions that surmount extant limitations intricacies deploying methodologies effectively frameworks.
Language: Английский
Citations
29
Computers in Industry, Journal Year: 2025, Volume and Issue: 166, P. 104234 - 104234
Published: Jan. 5, 2025
Language: Английский
Citations
1
Environmental Science and Ecotechnology, Journal Year: 2025, Volume and Issue: 24, P. 100526 - 100526
Published: Jan. 15, 2025
Language: Английский
Citations
1
Peer-to-Peer Networking and Applications, Journal Year: 2025, Volume and Issue: 18(2)
Published: Jan. 18, 2025
Language: Английский
Citations
1
Big Data and Cognitive Computing, Journal Year: 2024, Volume and Issue: 8(9), P. 95 - 95
Published: Aug. 23, 2024
A self-driving vehicle can navigate autonomously in smart cities without the need for human intervention. The emergence of Autonomous Connected Vehicles (ACVs) poses a substantial threat to public and passenger safety due possibility cyber-attacks, which encompass remote hacking, manipulation sensor data, probable disablement or accidents. sensors collect data facilitate network’s recognition local landmarks, such as trees, curbs, pedestrians, signs, traffic lights. ACVs gather vast amounts encompassing exact geographical coordinates vehicle, captured images, signals received from various sensors. To create fully autonomous system, it is imperative intelligently integrate several technologies, sensors, communication, computation, machine learning (ML), analytics, other technologies. primary issues involve privacy security when instantaneously exchanging volumes data. This study investigates related research using Blockchain-enabled Federated Reinforcement Learning (BFRL) framework. paper provides literature review examining BFRL framework that be used protect ACVs. presents integration FRL Blockchain (BC) context cities. Furthermore, challenges opportunities future on utilising frameworks are discussed.
Language: Английский
Citations
7
Future Internet, Journal Year: 2024, Volume and Issue: 16(9), P. 324 - 324
Published: Sept. 6, 2024
The integration of machine learning (ML), blockchain, and the Internet Things (IoT) in smart cities represents a pivotal advancement urban innovation. This convergence addresses complexities modern environments by leveraging ML’s data analytics predictive capabilities to enhance intelligence IoT systems, while blockchain provides secure, decentralized framework that ensures integrity trust. synergy these technologies not only optimizes management but also fortifies security privacy increasingly connected cities. survey explores transformative potential ML-driven blockchain-IoT ecosystems enabling autonomous, resilient, sustainable city infrastructure. It discusses challenges such as scalability, privacy, ethical considerations, outlines possible applications future research directions are critical for advancing initiatives. Understanding dynamics is essential realizing full cities, where technology enhances efficiency sustainability resilience.
Language: Английский
Citations
7
Electronics, Journal Year: 2024, Volume and Issue: 13(3), P. 497 - 497
Published: Jan. 24, 2024
Identifying relevant machine learning features for multi-sensing platforms is both an applicative limitation to recognize environments and a necessity interpret the physical relevance of transducers’ complementarity in their information processing. Particularly long acquisitions, feature extraction must be fully automatized without human intervention resilient perturbations significantly increasing computational cost classifier. In this study, we investigate relative resistance current modulation 24-dimensional conductimetric electronic nose, which uses exponential moving average as floating reference low-cost descriptor environment recognition. particular, identified that depending on structure linear classifier, ‘modema’ optimized different material sensing elements’ contributions classify patterns. The low-pass filtering optimization leads opposite behaviors between unsupervised supervised learning: latter favors longer integration reference, allowing recognition five classes over 90%, while first one prefers using latest events its cluster patterns by nature. Its implementation shall greatly diminish requirements noses on-board supervision.
Language: Английский
Citations
6