AI & IoT Solutions
Turn operational data into predictable intelligence
As a Hong Kong AI solution provider, GNS brings over 16 years of software and project execution experience — from custom AI models and IoT hardware to connected platforms — to deliver measurable AI and IoT outcomes for railways, government and enterprises.
- Railway digital imaging analytics
- Reinforcement learning forecasting
- Privacy-preserving 3D area monitoring
- Predictive maintenance & quality control
- 24/7 local support
Outcomes
Measurable results
- 80–90%
- Train running-time prediction accuracy (±15 min)
- 30%+
- Fewer hardware-caused incidents
- 60×60 m
- 3D monitoring coverage per unit
- 24/7
- Local technical support
Delivery timeline
Typical AI project: 3–6 months
Hover over each bar to see what happens in that phase.
Design & blueprint · 2 mo Core development · 3 mo Testing & launch · 1 mo
Actual duration varies with project complexity and how quickly you respond; 3–6 months is the typical range for AI projects.
Capabilities
What we deliver
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Custom AI model development
Reinforcement learning, deep learning and computer vision models trained on your operational data and integrated into existing systems and workflows.
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IoT hardware & sensing →
In-house designed and manufactured IoT edge devices, data loggers and sensors compliant with industry standards such as EN50155 for railway, factory and field environments.
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Privacy-preserving area monitoring
3D depth-camera monitoring that records depth maps only — no optical images — covering over 60×60 m with dimension error below 10%.
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Predictive maintenance
Data analytics that forecast equipment failure in advance — our portable relay tester predicts relay faults up to three months ahead, reducing unplanned downtime.
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Video analytics & quality control
Real-time image processing for bread QC, depot route monitoring, people counting and goods dimension measurement.
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Connected platforms & dashboards
Cloud-based real-time monitoring, alerting and reporting so operators stay informed and can download logs remotely.
Solution details
How we deliver
Every AI and IoT engagement starts from the operational problem, not the technology. GNS engineers first review your existing processes and data, then select the right combination of sensors, edge devices, models and platforms — delivered with project governance and continuously refined in operation.
On the railway, we built a reinforcement learning model that combines SACEM data loggers and observatory weather data to forecast allowable train running time with 80–90% target accuracy (±15 minutes), reducing hardware-caused incidents by more than 30%. The same forecasting capability applies to factory equipment, power systems and logistics facilities.
Privacy and compliance
We understand the data-privacy demands of critical facilities. Our 3D area monitoring records depth maps only, never optical images, avoiding sensitive facial data while maintaining accurate zone detection. Systems ship with safety testing and complete project documentation, suitable for government procurement and audit requirements.
Why GNS
- In-house hardware design and production, free from third-party supply constraints
- Project management team with proven government and railway track record
- ISO 9001, ISO/IEC 27001 and ISO 14001 certified processes
- 24/7 local engineers to keep solutions running
Want to start with hardware and connected platforms? See our IoT Hardware & Solutions.
Case studies and guides: railway AI forecasting (EMSD S-1662), privacy-preserving 3D monitoring (Smart LAB S-0233) and how to choose a systems integrator.
Case: AI-assisted train stopping-distance assessment for MTR
This case shows how AI supports day-to-day railway operations decisions. GNS built an AI analysis process for MTR that examines the stopping distance of every train at every station. When a train stops and its doors cannot be opened, the system reports to the Operations Control Centre (OCC) and provides a reference judgement on whether the stopping distance is still suitable for door opening.
Previously, these incidents required control-centre staff to manually cross-check train position, stopping data and site conditions before deciding what to do. With AI performing the first-pass analysis, cases that do not need deeper follow-up can be classified quickly, so the OCC team can focus on the situations that genuinely require intervention — reducing the handling time per case.
Key points
- Based on stopping-distance data for every train at every station
- When doors cannot be opened, the system gives OCC a reference on whether the stopping distance is suitable for door opening
- Fewer manual cross-checks, faster case classification and handling
- Runs alongside existing railway operating systems without changing safety procedures
Some technical details and internal data are not disclosed due to confidentiality agreements. Want to see how a similar approach could work in your operation? Contact GNS or view project examples.
FAQ
Service questions
How are GNS AI solutions deployed?
We offer on-premise, cloud or hybrid deployment depending on data privacy, latency and compliance needs. Railway and government projects typically use on-premise or hybrid architecture with secured network transport.
How does the 3D monitoring protect privacy?
The system records depth maps only — no optical images — so identifiable facial imagery is never stored. All data is encrypted in transit, with safety testing and project documentation provided.
Can GNS build custom IoT hardware?
Yes. Our R&D team designs and manufactures IoT edge devices, data loggers and electronic control systems, and can test and certify them against standards such as EN50155.
How long do AI projects take?
Depending on data availability and integration scope, simple analytics or vision models typically reach pilot within months; large railway or government projects are delivered in phases with pilot validation.
There are many AI solution providers in Hong Kong — why choose GNS?
GNS does not sell off-the-shelf products. We start from your operational problem: in-house hardware design and manufacturing, a track record on large government and rail projects, ISO 9001/27001/14001-certified processes, and 24/7 local engineer support. Most AI projects reach pilot within 3–6 months, so enterprises can validate value at small scale first.
How much budget do SMEs need for an AI project?
It depends on data availability and integration scope. Simple video analytics or data model pilots typically complete within months. GNS offers phased quotations and milestone-based payments, so SMEs can start with a small pilot instead of committing millions upfront.
Which companies in Hong Kong provide AI solutions — what has GNS actually delivered?
GNS has delivered AI railway video analytics, predictive maintenance that cut hardware-related incidents by over 30%, real-time analysis of over 100 million train logs a day, privacy-preserving 3D monitoring and AI quality control for food factories.
Design your AI & IoT solution
Tell us about your operational challenge and our engineers will recommend the architecture, timeline and support model.