International Journal of Engineering & Tech Development

E-ISSN: 3067-672X

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Volume 3 Issue 10
October 2026

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Edge Computing Frameworks for Low-Latency Industrial Decision-Making

Author(s) Enzo Mingozzi
Country Italy
Abstract The increasing adoption of connected industrial systems has created significant demand for computational architectures capable of processing data with minimal latency. Conventional cloud-centric computing models may introduce communication delays, bandwidth limitations, and dependence on remote data centers when large volumes of industrial information must be processed in real time. Edge computing addresses these limitations by placing computational resources closer to industrial devices, machines, sensors, and control systems. This paper examines edge computing frameworks for low-latency industrial decision-making, focusing on architectural components, data processing mechanisms, resource management, intelligent analytics, and industrial applications. A structured review-based methodology is adopted to analyze edge-enabled approaches across manufacturing, industrial automation, energy systems, transportation, robotics, and infrastructure.
The analysis demonstrates that edge computing can reduce response time by enabling localized data processing and decision-making while reducing unnecessary data transmission to centralized cloud environments. Integration with artificial intelligence, machine learning, Internet of Things technologies, and containerized services can further improve the intelligence and flexibility of edge platforms. However, practical implementation remains affected by limited edge resources, heterogeneous devices, network reliability, cybersecurity, interoperability, scalability, and workload management. The study highlights the importance of hierarchical edge-cloud architectures that distribute computation according to latency, resource, security, and application requirements. Future research should focus on adaptive resource orchestration, lightweight AI models, federated intelligence, secure edge architectures, digital twins, and autonomous industrial decision-making. Edge computing therefore represents a critical architectural approach for developing responsive, intelligent, and reliable industrial systems where rapid decisions are essential.
Keywords Edge Computing, Industrial Decision-Making, Low Latency, Industrial IoT, Edge Intelligence, Cloud Computing, Real-Time Processing, Smart Manufacturing.
Field Engineering
Published In Volume 2, Issue 6, June 2025
Published On 2025-06-03
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E-ISSN: 3067-672X
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