A vendor-agnostic edge layer that normalizes heterogeneous field data — and delivers structured, decision-ready streams to your core systems.
A decade as Actuate. Three decades of field engineering.
The same edge platform, configured for each sector — from sensor firmware to decision-ready data.
The platform bridges operational reality and edge platform engineering — building a distributed control layer from micro edge to cloud edge. The same engineering stack is configured to each environment rather than rebuilt for it. Each deployment, prototype, and research program feeds back into the platform — 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, protocol middleware, and field deployments — across R&D programs and production sites.
A position-independent layer that normalizes, validates, and time-aligns field data across edge-to-cloud deployments. The same layer functions identically whether deployed pre-MEC, post-MEC, or fully autonomous — defined by what it does, not where it sits.
Pre-MEC
Data normalization at the source, before mobile edge computing integration.
Post-MEC
Refining and structuring high-volume streams after initial regional processing.
Autonomous Edge
Self-contained orchestration for environments without continuous cloud connectivity.
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 as structured streams to ERP, MES, or monitoring systems — without modifying plant-side equipment.
Whatever the sensor type — vibration, temperature, flow, pressure, current — the underlying signal is the same. The sensor type and its transfer function are modeled in the edge layer. Your production platform receives clean, validated, time-aligned data regardless of plant equipment diversity.
Plant floor sensors
PLCs • energy analyzers • vibration • 4-20mA signals
MSEC normalization
Time alignment • validation • schema mapping
Decision systems
ERP • MES • SCADA — structured streams
Traffic sensors, environmental monitors, utility meters, and structural health sensors connect through MQTT, LoRaWAN, and cellular IoT protocols. Heterogeneous urban sensor streams are unified at the edge into a single decision-ready data model — enabling local processing with eventual synchronization.
Every sensor type — from passive IR motion detectors to multispectral cameras — produces data in its native format and protocol. The sensor type and its metadata are known in the edge layer. Your city platform ingests streams that are already clean, time-aligned, and decoded.
Traffic, environmental, utility, structural sensors
MQTT • LoRaWAN • cellular IoT protocols
MSEC stream unification
Time alignment • schema harmonization
City platforms & dashboards
Traffic management • environmental monitoring
Wearable devices, bedside monitors, and lab equipment transmit data through their existing standard protocols — HL7, CAN, Bluetooth. At the edge, the data is normalized and structured into clinically-safe, audit-ready streams before reaching your EHR or clinical decision support systems. Patient data remains within the facility perimeter; structuring happens locally.
Whatever the sensor type — wearable accelerometer, ECG, temperature, SpO2 — the underlying signal is the same. The sensor type and its transfer function are modeled in the edge layer. Your clinical platform receives clean, validated, and audit-ready data streams.
Medical devices, wearables, bedside monitors
HL7 • CAN • Bluetooth protocols
MSEC signal normalization
Validation • audit trails • compliance preparation
Clinical systems
EHR • clinical decision support • monitoring dashboards
Multispectral cameras, soil moisture probes, weather stations, and irrigation controllers transmit data via LoRa, 4G, and local RS-485 connections. Diverse data streams are normalized at the edge and delivered as structured, actionable outputs — NDVI, soil health metrics, irrigation recommendations — ready for precision agriculture platforms. Field operation does not depend on continuous cloud connectivity.
Sensors in the field — multispectral, soil moisture, weather, flow meters — each speak their own language. The field data is translated and time-aligned in the edge layer. Your precision agriculture platform receives unified, consistent data ready to drive irrigation, fertilization, and yield predictions.
Field sensors & irrigation
Multispectral • soil • weather • flow (LoRa, 4G, RS-485)
MSEC agronomic processing
NDVI calculation • soil health metrics • time alignment
Precision ag platforms
Irrigation controllers • yield prediction • decision dashboards
Energy meters, water flow sensors, gas analyzers, and emissions sensors report through their native protocols — Modbus, IEC 60870-5-104, and proprietary RS-485 variants. Heterogeneous utility data is normalized at the edge and delivered as consistent, audit-ready Scope 1 and Scope 2 metric streams to your ESG reporting platform. Every metric is tied to a physical sensor reading and timestamped for traceability.
Every utility measurement — energy consumption, water usage, gas flow, CO2 levels — arrives with different units and sampling frequencies. The measurements are synchronized and normalized in the edge layer. Your ESG platform receives clean, time-aligned, unit-normalized streams ready for Scope calculations.
Utility sensors & meters
Energy • water • gas • emissions (Modbus, IEC 60870-5-104, RS-485)
MSEC normalization & validation
Unit normalization • time alignment • Scope 1/2 prep
ESG platforms & reporting
Carbon accounting • sustainability dashboards • audit trails
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.