SCNET · Enterprise IT · Ankara, Türkiye

Sanal Çekirdek

Turn field signals into a system that can support decisions.

IoT and edge computing are the discipline of turning field signals into systems that can support decisions, bringing together device lifecycle, field connectivity, data models, OT security, edge decisions, central analytics and enterprise integrations. Sanal Çekirdek designs this path between the physical world and the digital core.

A reliable path from device to data platform

Field protocols, network conditions and device capabilities vary by location. Data frequency, local buffering, timestamps, offline behavior and quality checks are defined around the actual use case.

  • Sensor, gateway and protocol integration
  • Device identity and secure enrollment
  • Local buffering and store-and-forward
  • Shared telemetry and asset data model

Edge processing and local decisions

Latency, bandwidth, security or intermittent connectivity may make central processing inappropriate. Filtering, thresholds, rules and suitable analytics can run at the edge so local actions continue even when the upstream connection is unavailable.

  • Edge workload and resource planning
  • Local rules and event processing
  • Model deployment and version control
  • Core-to-edge synchronization

OT security and segmentation

Operational networks are not treated as simple extensions of enterprise IT. Passive visibility, secure remote access, zoning, permitted communication paths and change control provide security without ignoring production continuity.

  • Asset and communication map
  • OT/IT boundary and secure exchange
  • Vendor access and session recording
  • Anomaly visibility and incident escalation

Connecting data to operational outcomes

Collected data should not stop at a dashboard. We connect it to a defined decision in maintenance, quality, energy, asset utilization or how a location is run. Integration with ERP, MES, EAM, CRM or workflow systems is therefore part of the design.

  • Predictive maintenance signals
  • Energy and consumption visibility
  • Quality and process deviation
  • Location, fleet and asset traceability

How we work

  1. Discovery and current-state assessment
  2. Target architecture and control design
  3. Pilot, migration or modernization plan
  4. Go-live against acceptance criteria
  5. Monitoring, managed services and continual improvement

How success is measured

  • Device and data-flow availability
  • Missing, delayed or invalid telemetry
  • Unplanned downtime and maintenance-signal precision
  • Verified change in energy, quality or asset utilization

Frequently asked questions

Can existing field devices be used?

The first preference is usually to assess current investments. Protocols, data access, security, time synchronization and device capacity are reviewed, with a gateway or adapter layer added only where necessary.

Should all data be sent to the cloud?

No. The use case, latency, cost, privacy and connectivity determine what remains at the edge, what is summarized and what is sent to the central platform.

How do you plan scale beyond a proof of concept?

Provisioning, remote updates, configuration, observability, certificate renewal, spares and field support are designed during the proof of concept. The target is an operable deployment model, not just a working prototype.

Define the field problem, the required data and the resulting action together.

Plan an IoT/OT discovery