The Internet of Things (IoT) is sensors, machines and devices talking to each other and to software by sending and receiving data over a network. In industry it turns data such as temperature, door contacts or PLC signals into real-time events and decisions.
Work in this area
Abdulaziz Akyol builds integrations that put camera analytics and IoT sensor data on the same event pipeline (ERP, MES, POS, BI). CX Teknoloji is a project partner in the TÜBİTAK 2553-funded GTÜ–NUST project developing a smart greenhouse with IoT and AI.
- Camera + sensor integration with MQTT and event-driven architecture
- Measuring OEE and downtime on the line with PLCs and cameras
- Edge or cloud: bandwidth, latency and cost decisions
- IoT and yield prediction in the TÜBİTAK 2553 smart greenhouse project
Frequently asked questions (3)
Which protocol should IoT projects use?
For most industrial and commercial scenarios MQTT is a good start: it is lightweight, publish/subscribe based and supports QoS and persistent sessions. It should never go to the field without TLS, authentication and topic-level authorisation.
Should IoT data be processed at the edge or in the cloud?
Data that needs constant high bandwidth (video, for example) should be processed at the edge, sending only events and metrics to the cloud. Latency, connectivity and data privacy drive the decision.
Is a camera an IoT sensor?
Yes — one of the richest. When camera events join temperature, door-contact or PLC signals in the same event schema, they provide context no single sensor could.
- 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.
- 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.
- 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.
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