Smart City Gnosys
Smart city article details
| Title | Edge-Ai In Iot: Leveraging Cloud Computing And Big Data For Intelligent Decision-Making |
|---|---|
| ID_Doc | 21815 |
| Authors | Murthy V.S.N.; Kumari R.; Goyal M.; Dubey P.; Meenakshi; Manikandan S.; Ramesh P. |
| Year | 2025 |
| Published | Journal of Information Systems Engineering and Management, 10 |
| DOI | http://dx.doi.org/10.52783/jisem.v10i20s.3194 |
| Abstract | The extremely rapid increase in the number of these IoT devices has led to an unprecedented creation of data that requires intelligent and efficient mechanisms for decision-making. Today, Edge Artificial Intelligence (Edge-AI) is transforming the world with real-time data-processing capabilities, minimizing latency, optimizing bandwidth, and establishing separation for security. The integration of Edge-AI, cloud computing, and big data technology is studied in this research to optimize intelligent decision-making in IoT ecosystems. Using the distributed nature of edge computing, we present an Edge-Cloud AI framework which dynamically assigns computation workloads onto the edge nodes and centralized cloud infrastructures. The experimental results together with the validation through real IoT scenarios show that the proposed methods outstand in terms of response time, energy consumption and predictiveness. This approach strikes a proper balance between inference at the edge in real time and training of the models and big data analytics at the cloud; thus allowing adoption in intelligent solutions leading to adaptive, context aware intelligence. Innovative Elements include a new decision-making model based on federated learning, distributed pre-processing of data, and mechanisms for maintaining the confidentiality of data. These results highlight the capabilities of Edge-AI in improving the scalability and reliability of IoT applications in different domains such as smart cities, healthcare, and industrial automation. This work lays the groundwork for the next step in autonomous IoT, connecting edge intelligence with cloud-based learning analytics. © 2024 by Author/s and Licensed by JISEM. |
| Author Keywords | cloud; computing; decision; distributed; edge; energy; optimize |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
27178  | 0.938 | Prerna; Sharma S. | From Data To Decisions: Cloud, Iot, And Ai Integration | Integration of Cloud Computing and IoT: Trends, Case Studies and Applications (2024) |
| 27257 | 0.924 | Ficili I.; Giacobbe M.; Tricomi G.; Puliafito A. | From Sensors To Data Intelligence: Leveraging Iot, Cloud, And Edge Computing With Ai | Sensors, 25, 6 (2025) |
| 21762 | 0.918 | Chandrasekaran S.; Athinarayanan S.; Masthan M.; Kakkar A.; Bhatnagar P.; Samad A. | Edge Computing Revolution: Unleashing Artificial Intelligence Potential In The World Of Edge Intelligence | Edge of Intelligence: Exploring the Frontiers of AI at the Edge (2025) |
| 33904 | 0.915 | Kilaru M.; Maheswari P.; Boddepalli E.; Venkataramana K.; Patel J.D.; Sharma M.K. | Iot Services And Intelligence: Empowering The Internet Of Things With Real-Time Data Analytics And Decision-Making | TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 (2024) |
| 55982 | 0.912 | Hasan M.M.; Sultana T.; Hossain M.D.; Mandal A.K.; Ngo T.-T.; Lee G.-W.; Huh E.-N. | The Journey To Cloud As A Continuum: Opportunities, Challenges, And Research Directions | ICT Express (2025) |
| 14842 | 0.91 | Grzesik P.; Mrozek D. | Combining Machine Learning And Edge Computing: Opportunities, Challenges, Platforms, Frameworks, And Use Cases | Electronics (Switzerland), 13, 3 (2024) |
| 22927 | 0.905 | Nizam M.K.; Goyal S.B.; Verma C.; Illés Z. | Empowering Smart Cities With Edge Computing-Based Iot Systems: A Focus On Data Analytics And Machine Learning Techniques | Lecture Notes in Electrical Engineering, 1194 (2024) |
| 44385 | 0.905 | Guarda T.; Torres W. | Real-Time Iot With Edge Computing: Efficiency, Security, And Future Trends | Lecture Notes in Computer Science, 15889 LNCS (2026) |
| 30629 | 0.898 | Asha A.; Rajeshkumar L.; Pandi V.S.; Shobana D.; Lakshmi Priya J.; Dayanidhy M. | Implementing Cloud Computing With Internet Of Things (Iot) Technologies: Novel Approaches To Data Management And Service Delivery Innovation | 2024 Global Conference on Communications and Information Technologies, GCCIT 2024 (2024) |
| 21768 | 0.898 | Rajagopal S.; Tripathi P.K.; Deshmukh M.; Choudari S.; Kumar A.; Long C.S. | Edge Computing- Smart Cities: Optimizing Data Processing & Resource Management In Urban Environments | Journal of Information Systems Engineering and Management, 10 (2025) |