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aliallouf/Virtual-Sensor-DT-Implementation

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Consolidated Digital Twin (cDT) for IoT Industrial Monitoring

This project implements a Consolidated Digital Twin (cDT) based on the architectural framework defined in the survey paper:

"Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models"
— Minerva et al.

The system bridges the Physical Space (Atoms) and the Virtualization Space (Bits) to create a persistent software counterpart featuring:

  • ✅ Strong Entanglement
  • ✅ Reflection
  • ✅ Memorization
  • ✅ Replication & Specialization
  • ✅ Persistency

🏗️ System Architecture: The Three-Space Model

1️⃣ Physical Space (The Atoms)

Using Wokwi, we simulated an industrial sensing unit that generates a continuous data stream (temperature, humidity, proximity) and reacts to remote actuation commands.

🔧 Components

Component Role
ESP32 Physical Object (PO) Controller
DHT22 Thermal Attribute Sensor
HC-SR04 Proximity/Distance Sensor
Servo Motor Actuator for Strong Entanglement feedback

Physical Object Wiring

Figure 1: Physical Object (PO) wiring and sensor integration.


2️⃣ Virtualization Space (The Middleware)

The middleware layer handles the Entanglement between atoms and bits.

  • Broker: HiveMQ Cloud
  • Orchestration: Python-based Master Logical Object (LO)

🔁 Reflection Property

The Physical Object mirrors its status to the cloud in real time using JSON format.

Reflection JSON

Figure 2: Verisimilar representation of PO attributes in the cloud.


🧠 Master LO Replication

A Python-based Master Logical Object (LO) orchestrates data distribution.
It prevents overloading the physical device by replicating data into:

  • Real-time monitoring stream
  • Historical logging stream

Master LO Replication

Figure 3: Master LO replicating status to specialized virtual instances.


3️⃣ Application Space (The Bits)

The Application Space contains specialized services consuming LO data.


A. 🧠 Cognitive Engine (Augmentation)

  • Monitors the Real-Time LO
  • Applies autonomous logic
  • If temperature > 25°C → sends actuation command
  • Simulates cooling vent opening (Servo activation)

Cognitive Engine Feedback Loop

Figure 4: Autonomous feedback loop triggering Strong Entanglement actuation.


B. 💾 Memorization Layer (Status Log)

Implemented using Node-RED.

  • Captures object history
  • Stores data in persistent CSV file
  • Enables trend analysis & forensic inspection

Node-RED Flow

Figure 5: Node-RED flow connecting Virtualization Space to the Memorization Status Log.


🚀 Technical Features Implemented

  • Strong Entanglement
    Bidirectional communication between LO and PO (Servo control)

  • Promptness
    Negligible synchronization delay between PO and LO

  • Replication & Specialization
    Master Replica serving multiple application instances

  • Persistency
    LO maintains last known state even if sensors go offline


🛠️ Setup Instructions

1️⃣ Physical Layer

Load the code inside:

into Wokwi ESP32 simulator.


2️⃣ Middleware Setup

Install dependencies:

pip install paho-mqtt

About

A Consolidated Digital Twin (cDT) implementation based on the Minerva et al. survey. Features a 3-space architectural model (Physical, Virtualization, Application) with Strong Entanglement, Replication, and Memorization using ESP32, Python, and Node-RED.

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