Case Study
Autonomous field monitoring, engineered for scale
A computer-vision and IoT system for real-time field monitoring, built for reliable performance in demanding industrial environments.
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01 / The Problem
What challenge needed solving?
Manual field inspection was slow and inconsistent — operations teams needed real-time data to react fast, but had no live visibility into field conditions.
High cost of manual inspection
Low accuracy in early issue detection
No real-time data for fast decisions
02 / The Solution
How ZLab designed and delivered the solution
Our team designed an embedded computer-vision system integrated with IoT sensors and deep-learning models for on-site inference, streaming results into a centralized real-time monitoring interface.
Computer VisionDeep LearningIoTEmbedded Systems
01
System design
Sensor architecture and vision models were designed.
02
Prototyping
The prototype was built and validated in the lab.
03
Field deployment
The system was deployed and evaluated at pilot sites.
Measurable Results
Results that matter to the business
0
Lower operating costs
0
System uptime
0
Months, design to deployment
0
Industrial pilot sites
Project Team
The people behind it
Ramin Buzarpur
Lead Frontend / AI Developer
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Person Name
Machine Learning Engineer
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Person Name
Embedded Systems Engineer
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Person Name
Product Manager
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