An Intelligent Fingerprinting Technique for Low-power Embedded IoT Devices DOI
Varun Kohli, Muhammad Naveed Aman, Biplab Sikdar

et al.

IEEE Transactions on Artificial Intelligence, Journal Year: 2024, Volume and Issue: 5(9), P. 4519 - 4534

Published: April 10, 2024

The Internet of Things (IoT) has been a popular topic for research and development in the past decade. resource-constrained wireless nature IoT devices presents large surface vulnerabilities, traditional network security methods involving complex cryptography are not feasible. Studies show that Denial Service (DoS), physical intrusion, spoofing, node forgery prevalent threats IoT, there is need robust, lightweight device fingerprinting schemes. We identify eight criteria effective propose an intelligent, lightweight, whitelist-based method satisfies these properties. proposed uses power-up Static Random Access Memory (SRAM) stack as fingerprint features Autoencoder Networks (AEN) registration verification. also present threat mitigation framework based on isolation levels to handle potential identified threats. Experiments conducted with heterogeneous pool ten AVR Harvard-architecture prover from different vendors, Dell Latitude XPS 13 laptops used verifier testbeds. 99.9% accuracy, 100% precision, 99.6% recall known unknown devices, which improvement over several works. independence fingerprints stored AENs enables easy distribution update, observed evaluation latency (~ 10 −4 seconds) data collection 1 second) make our practical real-world scenarios. Lastly, we analyze regard highlight its limitations future improvement.

Language: Английский

Machine Learning-Integrated IoT-Based Smart Home Energy Management System DOI
Maganti Syamala,

C R Komala,

P. V. Pramila

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2023, Volume and Issue: unknown, P. 219 - 235

Published: June 16, 2023

The internet of things (IoT) is an important data source for science technology, providing easy trends and patterns identification, enhanced automation, constant development, ease handling multi-dimensional data, low computational cost. Prediction in energy consumption essential the enhancement sustainable cities urban planning, as buildings are world's largest consumer due to population growth, structural shifts economy. This study explored exploited deep learning-based techniques domain smart residential buildings. It found that optimal window size factor predicting prediction performance, best N size, model uncertainty estimation. Deep learning models household estimation performance uncertainty.

Language: Английский

Citations

122
Greening smart cities: An investigation of the integration of urban natural resources and smart city technologies for promoting environmental sustainability DOI Open Access

Chu Xiao Hui,

Ge Dan,

Sagr Alamri

et al.

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 99, P. 104985 - 104985

Published: Oct. 5, 2023

Language: Английский

Citations

115
A review on enhancing energy efficiency and adaptability through system integration for smart buildings DOI

Um-e-Habiba,

Ijaz Ahmed, Mohammad Asif

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: 89, P. 109354 - 109354

Published: April 18, 2024

Language: Английский

Citations

32
A critical review of machine learning algorithms in maritime, offshore, and oil & gas corrosion research: A comprehensive analysis of ANN and RF models DOI
Md Mahadi Hasan Imran, Shahrizan Jamaludin, Ahmad Faisal Mohamad Ayob

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 295, P. 116796 - 116796

Published: Jan. 30, 2024

Language: Английский

Citations

22
Deep-Fuzzy Logic Control for Optimal Energy Management: A Predictive and Adaptive Framework for Grid-Connected Microgrids DOI Creative Commons
Muhammed Cavus, Dilum Dissanayake, MC Bell

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(4), P. 995 - 995

Published: Feb. 19, 2025

This paper introduces a novel energy management framework, Deep-Fuzzy Logic Control (Deep-FLC), which combines predictive modelling using Long Short-Term Memory (LSTM) networks with adaptive fuzzy logic to optimise allocation, minimise grid dependency, and preserve battery health in grid-connected microgrid (MG) systems. Integrating LSTM-based predictions provides foresight into system parameters such as state of charge, load demand, health, while ensures real-time control. Results demonstrate that Deep-FLC achieves 25.7% reduction operational costs compared the conventional 17.5% saving cost over Fuzzy (FLC) system. Additionally, delivers highest efficiency 61% constraints depth discharge below 2% per time step, resulting degradation less than 0.2% 300 h. By combining analytics control, this study addresses limitations standalone approaches establishes robust, efficient, sustainable solution. Key contributions include integration advanced prediction mechanisms control its application battery-integrated MG

Language: Английский

Citations

3
Impacts of Cyber Security and Supply Chain Risk on Digital Operations: Evidence from the Pharmaceutical Industry DOI Open Access
Federico Del Giorgio Solfa

International Journal of Technology Innovation and Management (IJTIM), Journal Year: 2022, Volume and Issue: 2(2)

Published: Oct. 27, 2022

Purpose: The research explored empirical evidence to assess the impact of cyber security and supply chain risk on digital operations in UAE pharmaceutical industry. Methodology/Design/Approach: Based responses from 243 personnel working at 14 manufacturing companies Dubai, data were examined for normality, instrument validity regression analysis. Cyber SC by applying convenient sampling descriptive analytical design. Findings: findings validated significant positive association between with operations. Research implications Limitations: model was developed three variables evaluated only industry Dubai. Future should focus multiple industries covering a larger geographic area. Practical implications: When suppliers are highly concentrated, customer-focused organisations uncertain levels transformation could improve their ability manage diversifying clients. Pharmaceutical firms may require greater technology-based build maintain customer trust. Originality Value: To illustrate how has relationship security, operations, highlights convoluted consequences that have not been previously considered.

Language: Английский

Citations

48
Artificial Intelligence Incidents & Ethics A Narrative Review DOI Open Access

Syeda Faiza Nasim,

Muhammad Ali,

Umme Kulsoom

et al.

International Journal of Technology Innovation and Management (IJTIM), Journal Year: 2022, Volume and Issue: 2(2)

Published: Oct. 27, 2022

There has been a lot of media debate about “Artificial Intelligence (AI) Ethics” nowadays and many scientists researchers have shared their views on this topic. As technology is evolving, security issues are also emerging in new forms. Machines should be ethical, the “Build Design” such machines based ethics. Infact, AI must Ethics as part design within software code, just like measures encoded within. In review paper, statistics incidents areas presented along with social impact. Using online Incident Database, some applications identified, which shows unethical use AI. Applications Language Computer vision models, intelligent robots autonomous driving top ranking. Ethical appear various forms incorrect technology, racism, non-safety malicious algorithms biasness. Data collection helped to identify ethical Time, Geographic Locations, Application Areas, Classifications

Language: Английский

Citations

46
Industry 4.0 technologies and Lean Production Combination: A Strategic Methodology Based on Links Quantification DOI Open Access
Anne Zouggar Amrani, Ilse Urquia, Bruno Vallespir

et al.

International Journal of Technology Innovation and Management (IJTIM), Journal Year: 2022, Volume and Issue: 2(2)

Published: Oct. 27, 2022

The current environment faced to economy and sustainability requirements brings the fore two paradigms sustaining industrial performance: Lean Production (LP) Industry 4.0 technologies (I4.0). Whatever business companies run they have consider benefits of both. methodology this paper is based not only upon combined analysis identifying nature links but also on quantifying these in order provide a dashboard with Key indexes helpful for decision makers. It involves strategic method figure out tools deployment priority. consists an attempt quantify providing Layers modular implementation approach settle calculation actionable elements. Indicators comes strategy deployment: Index relevancy coverage. They are built increase visibility, followed by proposal Expansion indexto allow monitoring. At end, managers initially attempting deploy industry reserve impressed giant transformations, will beneficiate structured roadmap (algorithm-based) culminating priority implemented technologies.

Language: Английский

Citations

38
A Sustainable Pattern of Waste Management and Energy Efficiency in Smart Homes Using the Internet of Things (IoT) DOI Open Access
Mohammad Ehsanifar, Fatemeh Dekamini, Cristi Spulbăr

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(6), P. 5081 - 5081

Published: March 13, 2023

Nowadays, environmental protection involves many issues and problems, among which the waste generated by various human activities makes up a significant share, is becoming newer day day. Moreover, production of normal, industrial, special, hospital, agricultural improper management these materials has created health, safety, problems. Based on this approach, research study aims to determine model energy efficiency in smart homes using Internet Things (IoT). The method used estimative-computational. For purpose, required data were collected computational approach. views through experts field calculated MATLAB STATA software. analysis tool was represented fuzzy calculations for purpose software used. revealed that costs IoT technology are impressive. number home residents Home area innovative also

Language: Английский

Citations

20
AI-driven approaches for optimizing power consumption: a comprehensive survey DOI Creative Commons

Parag Biswas,

Abdur Rashid,

Angona Biswas

et al.

Discover Artificial Intelligence, Journal Year: 2024, Volume and Issue: 4(1)

Published: Dec. 27, 2024

Reduced environmental impacts, lower operating costs, and a stable, sustainable energy supply for current future generations are the main reasons why power optimization is important. Power ensures that used more efficiently, reducing waste optimizing utilization of resources. In today's world, integration artificial intelligence (AI) essential transforming how produced, used, distributed. AI-driven algorithms predictive analytics enable real-time monitoring analysis usage trends, allowing dynamic adjustments to effectively meet demand. Efficiency sustainability enhanced across various sectors by consumption through intelligent systems. This survey paper provides an extensive review different AI techniques optimization, along with systematic literature on application systems diverse areas consumption. The evaluates performance outcomes 17 distinct research methodologies, highlighting their strengths limitations. Additionally, this article outlines directions in optimization.

Language: Английский

Citations

8