| Parameter | Value | |-----------|-------| | Model | MEYD‑675 | | Dimensions | 120 × 80 × 30 mm | | Weight | 350 g (without battery) | | Power | 2 × Li‑ion 18650 (12 months @ 1 Hz) | | Operating Temp. | –40 °C to +85 °C | | IP Rating | IP67 (IP68 optional) | | Storage | 64 GB eMMC (expandable to 2 TB) | | Comm. | LoRaWAN, LTE‑Cat‑M1, Bluetooth 5.0, USB‑C | | Sensors (stock) | Temp., RH, Pressure, CO₂, PM, VOC, Light, (optional wind) | | Certifications | CE, FCC, RoHS, ATEX‑Ex dII (optional) | | Software | MEYD‑Suite GUI
| Sensor | Measurement Range | Accuracy | Typical Use Cases | |--------|-------------------|----------|-------------------| | Temperature (Thermistor) | –50 °C to +150 °C | ±0.1 °C (±0.5 °C @ –40 °C) | Climate stations, HVAC, cold‑chain | | Relative Humidity (Capacitive) | 0 %–100 % RH | ±1.5 % RH (±3 % @ 0 %/100 %) | Greenhouses, museums | | Barometric Pressure (MEMS) | 300 hPa–1100 hPa | ±0.3 hPa | Weather forecasting, altitude tracking | | CO₂ (NDIR) | 0 – 5000 ppm | ±30 ppm + 3 % of reading | Indoor air quality, labs | | Particulate Matter (Laser Scattering) | PM₁.₀, PM₂.₅, PM₁₀ (0 – 1000 µg m⁻³) | ±10 % | Urban pollution, mine ventilation | | VOC (Metal‑oxide) | 0 – 1000 ppb | ±15 % | Industrial safety, building health | | Light (Lux) (Photodiode) | 0 – 200 000 lx | ±5 % | Solar irradiance, plant research | | Wind Speed & Direction (Ultrasonic) (optional add‑on) | 0 – 60 m s⁻¹, 0°–360° | ±0.2 m s⁻¹, ±3° | Meteorology, wind‑farm siting |
Note: The MEYD‑675 can be ordered with any combination of the above sensors. Additional specialized probes (e.g., soil moisture, water level, radiation) are available as plug‑and‑play modules. meyd675
| # | As a … | I want … | So that … | |---|--------|----------|-----------| | 1 | Operator | to see a single, colour‑coded health bar for each critical asset on my HMI | I can instantly spot which machine needs attention without digging through logs | | 2 | Maintenance Engineer | an auto‑generated RCA notebook when an alarm fires (including sensor traces, correlation graphs, and probable cause) | I spend minutes, not hours, fixing the issue | | 3 | Production Planner | a predictive output forecast for the next 24 h based on current equipment health and process set‑points | I can adjust shift plans and inventory proactively | | 4 | Business Analyst | a monthly “Insight Dashboard” that aggregates OEE, energy usage, and anomaly trends across all MEYD‑675 hubs | I can report ROI and justify further automation investments | | 5 | IT/DevOps | a plug‑and‑play container that can be deployed on the MEYD‑675 edge runtime (Docker‑Slim) | I avoid complex installs and can roll out updates centrally |
+----------------+ +--------------------+ +-------------------+
| MEYD‑675 | MQTT/ | Edge Runtime | HTTPS | Cloud Platform |
| Sensor Hub |-------> | (Docker‑Slim) |<------->| (K8s, PostgreSQL,|
| (8‑64 I/O) | AMQP | • Signal Proc. | API | Grafana, S3) |
+----------------+ | • Feature Engine | +-------------------+
| • TinyML Inference|
| • XAI Layer |
| • Alert Dispatcher|
+--------------------+
|
v
+-------------------+
| HMI / Mobile UI |
| (React SPA + PWA) |
+-------------------+
| Aspect | Description |
|--------|-------------|
| Name | Adaptive Insight Engine (AIE) – “MEYD‑675 Insight Layer” |
| Goal | Transform high‑frequency sensor data from MEYD‑675 into real‑time, context‑aware recommendations, anomaly‑driven alerts, and predictive maintenance schedules without requiring a data‑science expert on‑site. |
| Primary Users | • Plant floor operators
• Maintenance engineers
• Production planners
• Business analysts / executives |
| Business Value | • 10‑20 % reduction in unplanned downtime
• 5‑8 % increase in overall equipment effectiveness (OEE)
• Faster root‑cause analysis (RCA) → lower labor cost
• Ability to monetize data (trend reports, compliance dashboards) |
| Key Differentiators | 1️⃣ Edge‑first analytics (no need for constant cloud round‑trip)
2️⃣ Self‑learning models that auto‑tune to each plant’s unique operating envelope
3️⃣ “Explain‑Why” UI that surfaces sensor‑level evidence for every recommendation | | Parameter | Value | |-----------|-------| | Model
The MEYD‑675 is a high‑performance, low‑power System‑on‑Chip (SoC) designed specifically for edge‑AI workloads in industrial, automotive, and consumer‑grade devices. By combining a heterogeneous compute fabric with an on‑die AI‑optimized memory subsystem, the MEYD‑675 delivers up to 2 TOPS/W (tera‑operations per second per watt) while maintaining a compact 12 mm × 12 mm footprint in a 7 nm FinFET process.
Key selling points:
| Feature | Benefit | |---------|----------| | Hybrid Compute Engine – 4× ARM Cortex‑A78AE + 8× custom AI‑matrix cores | Seamless handling of control‑plane code and massive data‑parallel inference | | Unified 8 GB LPDDR5X on‑die with 2 TB/s bandwidth | Eliminates off‑chip memory bottlenecks, reduces latency | | Integrated Secure Enclave (TEE) | Hardware‑rooted attestation, secure model deployment | | Dynamic Voltage & Frequency Scaling (DVFS) + power islands | Fine‑grained power management for battery‑operated devices | | Standardized I/O – PCIe 4.0 x4, USB 3.2, MIPI‑CSI/DSI, Ethernet 1 GbE | Easy integration into existing hardware ecosystems | | Software Stack – Open‑source SDK, ONNX runtime, TensorFlow‑Lite micro | Fast time‑to‑market for developers |