M0 + M1–M6

Learning System

Seven learning modules (M0–M6) covering the complete tech stack from hardware basics to industry delivery

Learning Overview View Learning Paths

Learning Matrix

M0–M6 × L1/L2/L3 Panorama

Horizontal axis = L1–L3 three levels, vertical axis = M0–M6 seven modules; M0 is the zero-baseline entry, M1–M6 independently selectable by direction.

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Learning matrix: horizontal = L1-L3 levels, vertical = M0-M6 modules; each cell shows the module title, duration, and outcomes for that module at that level.
Module / Level
L1 Understandable, Explainable, Demonstrable — 3-Minute "Magic Moment"
L2 Independently Configure Usable Systems, Deliver Experience Workshops
L3 Business Closed Loop & Deep Customization: API Integration / Model Training / Private Deployment
M0
Smart Hardware Fundamentals A/B/C Hardware Platform Layers

A · Perception

1d

Grove × Codecraft

  • · Complete First Runnable Prototype with Grove Kit in Codecraft
  • · Establish "Sense→Logic→Output" Mental Model

B · Interaction

1d

Wio Terminal × BMAD

  • · Implement HMI with Wio Terminal Color Screen
  • · Complete a structured project using BMAD five-role workflow

C · Vision

1d

XIAO ESP32S3 Sense

  • · Implement Image Classification & Edge AI Inference with XIAO Camera
  • · Experience SenseCraft AI No-Code Model Deployment
M1
Device Connectivity & Smart Control

Platform Introduction and Basic Device Integration

1d

Centrally manage devices of all brands in one panel, break free from expensive commercial software licenses

  • · Understand the basic Home Assistant architecture and core concepts (entities, services, states, automations)
  • · Master ESPHome firmware configuration and the XIAO ESP32-C6 sensor integration workflow

Industrial Bus Integration and Scenario Automation

3d

Integrate existing industrial equipment, view real-time data directly and enable cross-device orchestration

  • · Master Modbus RTU protocol wiring, debugging, and YAML register configuration
  • · Independently build a complete energy metering and monitoring dashboard

Business Integration and System Operations

5d

Own a dedicated smart-building monitoring dashboard, with core data kept entirely on-premises

  • · Master data integration methods between HA and external management systems (REST API/MQTT/Webhook)
  • · Orchestrate complex business flows using Node-RED
M2
Multimodal AI Interaction

Multimodal Interaction Capability Experience

1d

Own a dedicated AI voice assistant, directly query data and control devices through everyday speech

  • · Understand the technical architecture combining edge vision and LLM Agent
  • · Master the core role of the MCP protocol in integrating on-device AI with business systems

Business System Integration and Linkage Configuration

3d

Integrate internal business systems, let voice interaction directly flow work orders and simplify cumbersome operations

  • · Independently configure Watcher vision and voice Agent parameters
  • · Master Docker-based deployment of local business systems and MCP bridge services

End-to-End Local Offline Voice AI Pipeline Deployment

5d

Achieve pure local offline deployment, usable without network and core business data never leaves the intranet

  • · Master the complete local end-to-end VAD→ASR→LLM→TTS voice pipeline architecture
  • · Master LLM quantization and deployment optimization methods on Jetson edge computing hardware
M3
Mesh Networking & Resilient Communication

Basic Networking and Offline Communication

1d

Own Your Emergency Communication Network, Exchange Messages and Share Locations in Network-Free Environments

  • · Understand LoRa physical characteristics and Meshtastic routing topology principles
  • · Proficiently configure node roles (Client / Repeater / Router) and channel encryption (256-bit AES PSK)

Status Monitoring and MQTT Bridging

3d

Achieve Field Off-Grid Sensor Monitoring, Automatically Collect Environmental Data and Anomaly Alerts

  • · Master MQTT bridging methods between LoRa Mesh and LAN/public network
  • · Master Node-RED-based Mesh telemetry data parsing and automation flow orchestration

Off-Grid Sensor Integration and Firmware Customization

5d

Integrate Off-Grid Private Networks with the IoT Ecosystem, Enable Off-Grid Networks to Link with On-Site Devices

  • · Master the Meshtastic open-source firmware architecture and C++ source customization workflow
  • · Master PlatformIO-based embedded compilation and firmware flashing
M4
Edge Vision AI

Dual-Track Experience and Basic Configuration

1d

Own Your Smart Vision Sentinel, Define Alert Zones and Auto-Capture Evidence

  • · Understand core vision concepts such as frame rate, resolution, confidence threshold, and IoU
  • · Independently complete reCamera device network configuration and video stream output

Dual-Track Scenario Automation and Multi-Channel Aggregation

3d

Upgrade Existing Legacy Cameras into a Smart Monitoring Network, Filter False Alarms and Link On-Site Audio-Visual Alerts

  • · Master using Node-RED on reCamera for local edge-event linkage
  • · Master Frigate frigate.yml multi-channel configuration, zone drawing, and parameter tuning

Model Customization and Edge Deployment Optimization

5d

Customize Dedicated Vision Recognition Models, Real-Time Dashboard Business Data

  • · Master the complete engineering loop of vision AI from data annotation and model training to edge deployment
  • · Master the key toolchain for TensorRT and embedded model quantization conversion
M5
Environmental Sensing & Data Acquisition

Environmental Sensing Network Architecture and Data Monitoring

1d

Achieve wiring-free wide-area sensor monitoring, view environmental data immediately after device power-on

  • · Understand the different topologies and applicable conditions of 4G DTU and LoRaWAN gateways in IoT data acquisition
  • · Proficiently use the SenseCraft Data web and mobile apps to view multi-dimensional environmental parameters and historical trend curves

Sensor Wiring, Modbus Configuration, and Rule-Based Alerts

3d

Own a Personalized Unified Sensor Data Dashboard, Auto-Alert on Anomalies

  • · Master RS485 differential wiring, 5V/12V power distribution, and Modbus RTU register addressing configuration
  • · Proficiently complete device binding and polling interval setup for the 4G data logger (or LoRaWAN gateway)

API Data Integration and Local Edge Automation

5d

Open up data interfaces, seamlessly integrate on-site monitoring data into own systems

  • · Master SenseCAP Open API authentication (Access ID / Access Key, HTTP Basic Auth) and telemetry data extraction API calls
  • · Deploy Node-RED on reComputer R1025 to orchestrate local automation control flows, triggering actuators based on sensor values
M6
Robotic Control & Embodied Intelligence

Selection Awareness, Safety Standards, and Out-of-Box Setup

1d

Teleoperate Six-Axis Robotic Arm, Real-Time Sync Multi-DOF Motions

  • · Understand industrial robotic-arm categories (Cartesian gantry, SCARA, Delta, six-axis articulated) and the commercial selection trade-offs of speed/precision/load/safety/cost
  • · Master robotic-arm physical workspace boundaries, hardware emergency stop usage, and safety operation procedures

Scenario Analysis, Spatial Intuition, and Multimodal Orchestration

3d

Autonomously Identify Targets & Execute Grasping, Flexibly Respond to Position Changes

  • · Clearly explain to clients why 3D scenarios require six-axis robotic arms and their selection boundaries
  • · Master SenseCraft multi-action flow orchestration and the "Generate → 3D Preview → Human Confirm → Real-Machine Execute" safety-confirmation mechanism

3D Spatial Grasping Closed Loop and Embodied Intelligence Outlook

5d

Customize Dedicated Scenario Applications, Quickly Adapt to Specific Workflows

  • · Use an RGB-D depth camera to obtain target 3D physical coordinates, call Pinocchio via Python for automatic motor-angle conversion, and use Motorbridge to drive the real machine for spatial grasping and exception handling
  • · Master the master-slave teleoperation action dataset collection workflow (LeRobot standard format), understand the basic principles of VLA embodied LLMs and Isaac Sim digital twin simulation
Legend L1 Understandable, Explainable, Demonstrable — 3-Minute "Magic Moment" L2 Independently Configure Usable Systems, Deliver Experience Workshops L3 Business Closed Loop & Deep Customization: API Integration / Model Training / Private Deployment

How Modules and Levels Combine

M0-M6 indicates learning direction, L1/L2/L3 indicates practice depth.

Horizontal Axis · M0–M6

Learning direction. M0 is the zero-baseline flagship entry (smart hardware fundamentals), M1–M6 are six industry directions, independently selectable by goal.

  • M0 · Zero-Baseline Flagship Entry
  • M1–M5 · Five Industry Directions

Vertical Axis · L1 / L2 / L3

Mastery depth. L1 Demo Level — understandable and demonstrable, L2 Consultant Level — independently configure usable systems, L3 Design Level — business integration and deep customization.

  • L1Demo Level | Understandable, demonstrable
  • L2Consultant Level | Independently configure systems
  • L3Design Level | Business integration

Each module can be introduced independently at L1/L2/L3 depths, or combined across modules.

Seven Adoptable Learning Modules

Each module includes real hardware, classroom experiments, and takeaway materials.

M0

Smart Hardware Fundamentals

Tell AI what you want to do in Chinese, AI writes code, compiles, flashes. Zero coding foundation, yet create your own smart hardware project.

 M1

Device Connectivity & Smart Control

Based on Home Assistant and ESPHome, unify multi-protocol device access within a local area network to enable energy monitoring and automated orchestration.

 M2

Multimodal AI Interaction

Based on physical AI terminals, integrating edge vision, voice, and business-system APIs to enable multimodal spatial interaction.

 M3

Mesh Networking & Resilient Communication

Based on the LoRa Mesh self-organizing protocol, build an off-grid emergency communication and sensor-data backhaul network with no public-network dependency and multi-hop relaying.

 M4

Edge Vision AI

Based on lightweight edge cameras and industrial-grade multi-channel AI compute hosts, build an edge vision solution for object detection, zone intrusion alerts, and automated linkage.

 M5

Environmental Sensing & Data Acquisition

Industrial-grade sensors with dual 4G/LoRaWAN links enable low-power environmental monitoring and data acquisition in wide-area scenarios.

 M6

Robotic Control & Embodied Intelligence

A six-axis desktop robotic arm combined with multimodal perception, enabling master-slave teleoperation, precise 3D spatial grasping, and embodied intelligence development.

Three Learning Tracks

Build with AI (M0), Build AI Products (M2 · M4), Solutions (M1 · M3 · M5).

Three Learning Tracks Combine modules by learning goal; M0 is the zero-baseline entry.
M0

Build with AI

Let AI be your programmer while you be the maker. Use natural language to drive AI code generation, and create your own smart hardware projects.

M0
View this module combination
M2 · M4 · M6

Build AI Products

From multimodal AI interaction to edge vision AI, build smart terminals and products that understand business needs.

M2M4M6
View this module combination
M1 · M3 · M5

Solutions

Combine device interconnectivity, mesh networking, and environmental sensing into deliverable industry solutions.

M1M3M5
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Bring learning modules into your team or project site

If you already have a clear direction, we can discuss Bare Hardware Kit, Standard Teaching Kit, Full-Delivery, or Train-the-Trainer. We will recommend module combinations and practice depth based on your goals.

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