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- EU AI Act: a practical compliance guide for Turkish companiesArtificial intelligenceWhen does the EU AI Act apply to Turkish companies? Risk classes, GPAI, the timeline after the Digital Omnibus, video analytics and a compliance checklist.
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- Scaling GPU video analytics services with Docker and KubernetesSoftware developmentRunning a per-camera GPU analytics service on Docker and Kubernetes: NVIDIA Container Toolkit, GPU Operator, time-slicing/MIG, k3s, monitoring and updates.
- Secure IoT with MQTT: Python, TLS and access controlIoTRunning MQTT securely: QoS, retain, last will and MQTT 5; TLS, client certificates and ACLs in Mosquitto; Python publisher and subscriber with paho-mqtt 2.x.
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- Video analytics on existing cameras: the chain from RTSP stream to eventComputer visionReal-time analytics on the IP cameras you already have: RTSP intake, GPU decoding, detection and tracking, a rule engine and event output, in five links.
- Edge or cloud? Choosing where to process in computer-vision projectsComputer visionProcess video on site or in the cloud? The decision we reached from bandwidth arithmetic, latency, data protection and three-year cost, and its exceptions.
- Getting people counting to 96%: field calibration notesComputer visionA model that scores 99% in the lab drops to 85% in the field. Camera angle, counting-line position, night data and measurement method close the gap to 96.2%.
- Data protection and video analytics: building analytics without face recognitionComputer visionFive questions legal teams ask about video analytics, answered by engineering: where video goes, what is stored, who has access, face recognition, retention.
- Forklift–pedestrian proximity detection: measurable safety rules in the warehouseComputer visionMeasuring forklift–pedestrian distance by camera: metres not pixels, a velocity vector not one frame, graded warnings not one alarm. The rule set behind it.
- Combining IoT and camera analytics: MQTT and an event-driven architectureIoTA camera is the richest sensor. On one event bus with PLC signals, door contacts and temperature it yields new data: event schema, MQTT topics, lessons.
- Measuring OEE on the production line with camerasComputer visionTwo of OEE's three factors come from the PLC; the third and the reason for each stop hide in the camera. Extracting downtime and cycle time from video.
- Keeping detection models alive in the field: drift, retraining and dataset disciplineArtificial intelligenceTraining is the short part. The hard part is keeping a model accurate in 40 locations as season, light and layout change: drift, dataset and versioning.
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Older technical notes (HTML5, PowerShell, Windows administration, Active Directory, HP/Aruba switches) are available in Turkish only. Türkçe →