This playbook focuses on the connectivity layer, helping you make smarter choices for your deployment. Download the PDF today ...

Guest post about the challenges of tracking a large number of IoT assets and how LTE-M can help businesses scale tracking ...

As AI systems become more embedded in business operations, IT must lead the charge to secure AI access, monitor its behavior, and guard against new forms of cyberrisk.

For CIOs, critically important first steps toward IT’s future require the kind of customer-informed vision few vendors and CEO ‘visionaries’ are offering right now.

This second part of the FAQ discusses the three upper layers of the IoT architecture, which extend beyond the physical and network layers. The middleware layer processes and manages raw IoT data from ...

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Most of the existing Internet of Things (IoT) applications are built upon the conventional three-layered architecture that possesses several issues in terms of security, privacy and scalability. In ...

The architecture will provide a reference to deploy Deep Q Learning based workloads to run on IoT edge devices with the help of containers. This will help in building solutions that spend less time to ...

Servers interacting with build systems, containerization, CI/CD, or deployment platforms. zenoengine/msbuild-mcp-server: Automates MSBuild project builds with dynamic discovery and customizable ...

Servers integrating with other AI models, AI platforms, RAG tools, prompt management, or agent frameworks. comitest22/linear-mcp: Facilitates interaction with the Linear API through a Model Context ...