Engineering Insights on AI, Robotics, Automation & Embedded Systems
Engineering deep-dives, technical examples, and practical guides on AI automation, robotics, edge AI, embedded systems, and industrial IoT.
Practical, engineering-first writing from the 5Tech team on AI automation, robotics, machine vision, embedded systems, and industrial IoT — how the technology actually works in production and where it pays off for businesses across Canada. Each article connects back to a service we deliver.
Articles
- Beyond Sidecars: How eBPF is Redefining High-Performance Cloud-Native Observability — A deep dive into how eBPF provides a high-performance, low-overhead alternative to traditional observability methods like sidecars and agents, enabling unprecedented visibility into complex cloud-native systems directly from the Linux kernel.
- Designing for Failure: A Practical Guide to Building Fault-Tolerant, Self-Healing Systems — A deep dive into the principles and patterns of fault tolerance. Move beyond simple uptime monitoring to build resilient systems that anticipate, isolate, and recover from failures automatically, ensuring service continuity in complex distributed environments.
- Implementing Edge AI on Resource-Constrained Devices: From Silicon Selection to Lifecycle Management — A pragmatic guide for engineers and technology leaders who need to run machine-learning inference on microcontrollers, low-power SoCs, and other constrained hardware without sacrificing accuracy, security, or maintainability.
- From Prototype to Production: Implementing Edge AI Across Industrial IoT Fleets — A practical guide for engineering leaders on moving edge-based machine-learning solutions from the lab bench to thousands of deployed industrial devices—covering hardware selection, data pipelines, fleet-wide orchestration, security, and cost modeling.
- Edge AI Model Optimization: Strategies for Real-Time Inference on Resource-Constrained Devices — A practical guide for engineers and technical leaders on squeezing maximum performance, accuracy, and reliability out of machine-learning models deployed at the network edge.
- Edge Computing Architectures for Industrial IoT: A Practical Guide — A step-by-step technical guide to selecting, designing, and deploying edge computing architectures that meet the latency, reliability, and security demands of Industrial IoT environments.
- Edge AI: The Next Frontier in Industrial Automation — Edge AI is moving compute and intelligence from the cloud to the factory floor, enabling real-time decision-making, lower latency, and greater resilience. This article explains the technology stack, benefits, and implementation roadmap for engineering leaders.
- Edge AI: Transforming Industrial Systems with On-Device Intelligence — Discover how Edge AI is revolutionizing industrial automation, enabling real-time, on-device decisions that improve efficiency, security, and scalability.
- The Future of Industrial IoT: 2025 Outlook — How edge computing and 5G are reshaping the landscape of industrial automation and remote monitoring.
- The Role of Predictive Maintenance in Modern Manufacturing — Why waiting for a breakdown is a strategy of the past. Learn how IoT sensors are saving billions in downtime.
- Optimizing Poultry Processing with Vision AI — A case study on how 5Tech computer vision systems increased throughput by 18% in high-speed sorting lines.
- Understanding EtherCAT for Robotics Control — Deep dive into why high-speed deterministic protocols are essential for multi-axis robotic synchronization.
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