A distributed control layer between field and decision systems makes that path direct. Sensors, PLCs, and field devices speak different protocols across different sectors. Actuate operates as a vendor-agnostic edge layer that integrates heterogeneous field infrastructure and delivers structured data to the systems that decide.
A decade as Actuate. Three decades in the field.
The same edge infrastructure, configured for your sector — from sensor firmware to decision-ready data.
Actuate is an R&D company building a distributed control platform from micro edge to cloud edge. The same engineering stack is configured to each environment rather than rebuilt for it. Engineering effort extends the platform — research programs, prototype validation, deployment iteration — across sectors.
From bare metal firmware on 32-bit ARM to RTOS applications and protocol middleware — every layer written and owned in-house.
The platform integrates with field equipment through its existing interfaces — serial fieldbus, industrial Ethernet, IoT messaging. Application logic does not depend on a single PLC or sensor brand.
Structured R&D programs introduce new sensor integrations, protocol layers, and deployment architectures to the platform. Validated outputs become reusable engineering components across sectors.
Engineering base at Marmara University Research Park, Istanbul. Work spans firmware-level integration, multi-protocol middleware, and field-deployable systems — across both R&D programs and production sites.
PLCs, energy analyzers, and field sensors connect through their existing protocol interfaces — serial fieldbus, industrial Ethernet, and IoT messaging. Operational data is normalized at the edge and delivered to ERP, MES, or monitoring systems without modifying plant-side equipment.
No standard deployment. We assess your existing infrastructure and configure the right solution.
You want to monitor energy, water, or gas but have no hardware in place. We advise on what to procure — then connect to it via Ethernet, RS-485, or any available interface. You buy the hardware. We make it talk.
You have automation in place but the data stays inside. We ask for the make, model, and data structure of your PLCs — then configure our edge layer to extract, validate, and forward structured data to wherever you need it.
Your systems are connected and data is standardized — but you need deeper insight. Vibration, temperature, and acoustic data from individual motors, processed at the edge, with only anomalies forwarded to your decision systems.
Water, Air, Gas, Electricity, Steam — configured to your facility. Only the utilities you measure, nothing else.
Vibration, temperature, and acoustic signals from individual assets — only anomalies forwarded upstream.
OPC-UA, Modbus, Profibus, CAN — configured for your existing PLC brands and models.
Independent municipal subsystems — environmental sensing, parking, lighting, utility metering — converged through a common edge layer. Distributed nodes process locally and continue operating during intermittent connectivity, then synchronize structured telemetry upstream.
Infrastructure rollout is defined but the data collection and processing architecture is not. We design the edge layer from the ground up — hardware selection, protocol stack, and data model aligned to your platform.
Multiple sensor types from different vendors are in the field but data streams are disconnected. We unify heterogeneous sources onto a common timeline and schema — no platform change required on your side.
Your city platform receives data but quality, latency, or coverage is inconsistent. We add a position-independent data preparation layer that validates, synchronizes, and structures data before it reaches your platform.
Whatever the sensor type — environmental, traffic, utility, structural — the underlying signal is the same. We know the sensor type and its transfer function. Your platform receives clean, validated, time-aligned data regardless of source diversity.
Wearable biometrics, bedside monitors, and patient telemetry from multiple device brands aggregated and normalized at the edge before synchronization with hospital information systems. Patient data remains within facility perimeter; structuring happens locally.
Patient environment conditions are checked manually or logged by standalone devices. We automate collection, structure the data, and deliver it to your HIS or reporting system.
Monitoring devices from different manufacturers produce incompatible formats. We normalize them at the edge into a unified schema — consistent, time-aligned, and validated before forwarding.
Your clinical systems receive data but completeness and reliability are inconsistent. We add an edge validation layer that catches missing values, out-of-range readings, and transmission errors before data enters your system of record.
Edge processing keeps sensitive data within your facility perimeter. Validation and structuring happen on-device — what leaves the edge is clean, audit-ready, and prepared for your clinical decision layer.
Soil, irrigation, environmental, and multispectral imaging data processed at field gateways — operating on battery or solar, with LoRaWAN, cellular, or local mesh transport. Data reaches decision platforms when connectivity allows; field operation does not depend on it.
Field conditions are monitored manually or with standalone loggers. We automate collection with low-power edge devices — solar or battery powered — and deliver structured data via LoRa, cellular, or Wi-Fi.
Sensors are transmitting but raw values arrive at your platform without context, calibration, or validation. We add an edge processing layer that converts raw signals into meaningful, validated readings before transmission.
Your agronomic decision system is operational but coverage in specific zones limits effectiveness. We fill gaps with additional edge nodes — configured to match your existing data schema and platform requirements.
Edge devices in agriculture must operate autonomously for extended periods with minimal maintenance. We size the hardware and firmware footprint to the task — from a single-parameter soil sensor to a multi-channel weather and irrigation control node.
ESG-relevant operational data — direct emissions, energy consumption, fuel use, fleet telemetry — connected through the same edge layer used for industrial deployments. Reporting platforms receive structured, traceable data, every metric tied to a physical sensor reading.
Emissions and energy data are gathered manually from utility bills or meter readings. We automate collection at the source — electricity meters, gas analyzers, fuel sensors — and structure the output for your reporting framework.
Certain utilities are monitored automatically but coverage is incomplete. Scope 1 direct emissions or Scope 2 indirect energy data may be missing or inconsistent. We close the gaps without replacing existing systems.
Your ESG reporting process is established but input data quality affects auditability. We add edge-level validation — ensuring every metric that enters your pipeline is measured, timestamped, and traceable to a physical sensor.
ESG compliance increasingly requires audit trails that go back to the measurement source. We provide that traceability — from the physical sensor reading, through edge validation, to the structured data package your reporting framework consumes. No estimation. No manual entry.
Three engineering layers under single ownership: bare-metal firmware on 32-bit ARM, a modular communication layer for field protocols, and MSEC — the position-independent data preparation layer. Configured to environment, not rebuilt for each project.
The same engineering stack deployed across all five verticals — configured, not rebuilt, for each use case.
Bare metal on 32-bit ARM for minimal footprint — when the task requires nothing more than signal acquisition and forwarding. RTOS when multi-task execution or larger memory is required. Hardware is sized to the task.
The physical signal layer is universal — 4-20mA, 0-10V, on/off, digital. The protocol layer adapts to your infrastructure: OPC-UA for modern facilities, Modbus and Profibus for legacy systems, MQTT for IoT environments.
MSEC is our position-independent data preparation layer — defined by what it does, not where it sits. The same software functions regardless of deployment position: pre-MEC, post-MEC, or fully autonomous.
The data preparation layer in motion — heterogeneous sensor input on the left, MSEC processing at the center, structured output on the right. Configuration commands flow back through the same path.
Every layer between sensor and decision system is written and owned in-house — firmware, protocol, and data preparation.
The data preparation layer functions identically whether deployed pre-MEC, post-MEC, or fully autonomous — defined by what it does, not where it sits.
Decision systems can write back through MSEC to firmware — sampling rates, thresholds, and setpoints update without redeployment.
Five stages, single ownership. The same pipeline runs across all five verticals — configured per environment, not rewritten per project. Decision systems can write back through the pipeline to firmware: setpoints, sampling rates, and thresholds update without redeployment.
Hardware-agnostic, software-independent, protocol-flexible. New deployments enter through configuration of existing equipment, sensor types, and decision systems on the receiving end. Engineering effort extends the platform — it does not rebuild it for each project.
Existing infrastructure, sensor types, decision systems on the receiving end — describe the configuration. The response describes how the platform fits.