REDDY, 2023 - Google Patents
AI and Edge Computing: Synergistic Approaches for Real-time Data Processing in Cloud EnvironmentsREDDY, 2023
View PDF- Document ID
- 12143521153489796680
- Author
- REDDY P
- Publication year
External Links
Snippet
The application of AI integrated with edge computing systems and cloud solutions in data processing and decision-making processes rapidly evolves to enhance real-time decision- making across several industries. The following article explains the relationship between …
- 238000012545 processing 0 title abstract description 31
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
- H04L67/12—Network-specific arrangements or communication protocols supporting networked applications adapted for proprietary or special purpose networking environments, e.g. medical networks, sensor networks, networks in a car or remote metering networks
- H04L67/125—Network-specific arrangements or communication protocols supporting networked applications adapted for proprietary or special purpose networking environments, e.g. medical networks, sensor networks, networks in a car or remote metering networks involving the control of end-device applications over a network
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/08—Configuration management of network or network elements
- H04L41/0803—Configuration setting of network or network elements
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3318046B1 (en) | A cognitive intelligence platform for distributed m2m/iot systems | |
| Borangiu et al. | Digital transformation of manufacturing through cloud services and resource virtualization | |
| Dai et al. | Toward self-manageable and adaptive industrial cyber-physical systems with knowledge-driven autonomic service management | |
| Karnouskos et al. | The IMC-AESOP architecture for cloud-based industrial cyber-physical systems | |
| Hegedűs et al. | The mantis architecture for proactive maintenance | |
| Vater et al. | A reference architecture based on edge and cloud computing for smart manufacturing | |
| Lam et al. | Dynamical orchestration and configuration services in industrial iot systems: An autonomic approach | |
| Ajayi | Integrating IoT and cloud computing for continuous process optimization in real-time systems | |
| Bablu et al. | Edge computing and its impact on real-time data processing for IoT-driven applications | |
| Lyu et al. | Multi-agent modelling of cyber-physical systems for IEC 61499-based distributed intelligent automation | |
| REDDY | AI and Edge Computing: Synergistic Approaches for Real-time Data Processing in Cloud Environments | |
| Sharma | From Data to Decisions: Cloud, IoT, and AI Integration | |
| Alimam et al. | Digital Triplet Paradigm for Brownfield Development towards Industry 5.0: A Case Study of Intelligent Retrofitting for Oil and Gas Boosting Plant in the Industrial Internet of Things (IIoT) Context | |
| Jain et al. | Internet of Things (IoT) technology: A critical component of industry 4.0 | |
| Liu et al. | Investigation and implementation of digital software architecture based on internet of things | |
| Annavarapu et al. | Smart Manufacturing: Integrating IoT and AI for Agile Production Management | |
| Rizky et al. | NEXT-GENERATION NETWORK AUTOMATION: LEVERAGING AI AND MACHINE LEARNING FOR AUTONOMOUS INFRASTRUCTURE | |
| Jayashree et al. | Edge data analytics technologies and tools | |
| Aggarwal et al. | Comprehensive Review of Recent Trends, Challenges, Applications, and Case Studies in Fog Computing | |
| Banerjee | The influence of edge-to-cloud data pipelines on real-time decision analytics | |
| Singh et al. | A Comprehensive Overview of Cloud Computing and IoT Integration: Trends and Real-world Applications | |
| Kumar et al. | Self-Adaptive Cyber-Physical Systems in IoT | |
| Raj et al. | Artificial Intelligence and Machine Learning-Based Predictive Maintenance in Fog and Edge Computing Environment | |
| Saheb | Development, Deployment, and Management of IoT Systems: A Software Hypothesis | |
| Jonnalagadda | Integrating AI and Cloud Technologies for Scalable, Low-Latency Edge Computing in Enterprise Workloads |