Research is the engine. Deployment is the proof.
NETNOVA's R&D team turns emerging technology into deployed industrial systems. Six stages — Research, Design, Prototype, Validation, Industrialization, Deployment — take an idea from whiteboard to operating asset.
A cross-disciplinary team in one lab — so hardware, firmware, network and cloud decisions happen in the same room, against the same test fixtures.
Six stages, from research to deployment
Each stage has its own deliverables, its own quality gates and its own engineering lead. You always know what's been done, what's next and what's at risk.
Research
Technology exploration, literature review, feasibility assessment and patent landscape analysis.
Design
System architecture, technology selection, hardware and software design, and risk evaluation.
Prototype
Rapid prototyping of hardware, firmware and software — proof of concept in real-world conditions.
Validation
Lab and field validation, performance and reliability testing, certification and compliance.
Industrialization
DFM/DFT, supply chain setup, production line preparation and quality systems for scale.
Deployment
Production, installation, commissioning, handover and long-term engineering support.
Where we focus our research
Five technology areas where NETNOVA R&D is actively investing — each tied to real industrial deployments and customer demand.
Industrial IoT
End-to-end IoT system design — sensors, gateways, networks, cloud and analytics — built for industrial reliability.
- Multi-protocol device integration
- Edge-to-cloud data pipelines
- OTA device management at scale
Wireless Communication
Cellular, LoRaWAN, Wi-Fi, BLE and proprietary RF — designed, tested and certified for industrial use.
- Multi-bearer fallback networks
- RF design and EMC compliance
- NTN / satellite integration
Edge Computing
Edge intelligence where latency, bandwidth or reliability demand local processing — containers, WASM, embedded ML.
- Edge runtime for containers
- Local rules and aggregation
- Intermittent-connectivity buffering
Embedded AI
On-device ML inference for anomaly detection, predictive maintenance and adaptive control — within power and memory budgets.
- TinyML on microcontrollers
- Model compression and quantization
- Federated learning options
NTN / Satellite
Non-Terrestrial Networks for global asset visibility — dual-mode cellular/satellite devices and cloud-side NTN routing.
- Dual-mode LTE / NTN devices
- NTN-aware cloud routing
- Coverage planning and SIM management
Have a research question?
Tell us what you're trying to build. We'll match you with an R&D lead in the relevant innovation area and propose a starting point — feasibility study, prototype or pilot.