Where Bits Meet Atoms - Pioneering the future of intelligent connected systems through cutting-edge research in IoT, Artificial Intelligence, and Machine Learning.

The Cyber Physical Laboratory is an interdisciplinary research hub dedicated to advancing the frontiers of intelligent systems. We bridge the gap between digital intelligence and physical reality, creating solutions that transform industries and enhance human experiences.

# Intelligent Threat Detection
class SmartSecurity:
    def __init__(self):
        self.iot_sensors = MultiModalSensors()
        self.ml_engine = ThreatDetectionModel()
        self.response_system = AdaptiveControl()
    
    def monitor_environment(self):
        return "Real-time anomaly detection with 99.2% accuracy"

Tech Stack: TensorFlow ROS MQTT ESP32 Python

Features:

• Multi-sensor environmental monitoring
• AI-powered pollution prediction
• Autonomous response systems

Innovations:

• Swarm robotics for logistics
• Reinforcement learning for path optimization
• Blockchain for secure transactions

Hardware:
  - Microcontrollers: "ESP32, Arduino, Raspberry Pi"
  - Sensors: "LiDAR, Thermal, Multi-spectral, Biometric"
  - Actuators: "Servo Motors, Solenoids, Smart Relays"
  - Communication: "LoRaWAN, 5G, Bluetooth Mesh, Zigbee"

Software:
  - ML Frameworks: "TensorFlow, PyTorch, Scikit-learn"
  - Edge Computing: "AWS Greengrass, Azure IoT Edge"
  - Data Platforms: "Apache Kafka, InfluxDB, TimescaleDB"
  - Visualization: "Grafana, Kibana, Custom Dashboards"

AI/ML Stack:
  - Computer Vision: "OpenCV, YOLO, CNN Architectures"
  - NLP: "Transformers, BERT, GPT-based models"
  - Time Series: "LSTM, Prophet, ARIMA"
  - Reinforcement Learning: "DQN, PPO, SAC"

graph TB
    subgraph Physical Layer
        A[Sensors]
        B[Actuators]
        C[Edge Devices]
    end
    
    subgraph Edge Intelligence
        D[Data Preprocessing]
        E[Lightweight ML Models]
        F[Real-time Inference]
    end
    
    subgraph Cloud Analytics
        G[Data Lake]
        H[Model Training]
        I[Digital Twins]
    end
    
    A --> D
    B --> C
    C --> D
    D --> E
    E --> F
    F --> C
    D --> G
    G --> H
    H --> E
    I --> F

• Dr. Md. Dulal Haque - Director, AI Research
• Dr. Md. Shahzamal - Director, ML Engineering

{
  "compute_resources": {
    "cloud_gpu": "200,000 GPU hours/month",
    "edge_devices": "500+ deployed units",
    "data_storage": "2PB distributed storage"
  },
  "monitoring": {
    "real_time_dashboards": "15+ active",
    "alert_systems": "Multi-level escalation",
    "performance_metrics": "99.95% uptime"
  }
}

• MIT Media Lab - Joint research in human-computer interaction
• Stanford AI Lab - Collaborative ML research
• ETH Zurich - Cyber-physical systems security

class LabImpact:
    def __init__(self):
        self.patents_filed = 15
        self.products_launched = 8
        self.companies_spunoff = 3
        self.research_citations = 1200
        
    def social_impact(self):
        return {
            'lives_touched': '1M+',
            'energy_saved': '50 GWh',
            'carbon_reduced': '10K tons'
        }

• Deploy city-scale digital twin
• Launch federated learning platform
• Publish 10+ research papers

• Develop quantum-resistant CPS security
• Establish international testbeds
• Scale to 1000+ IoT nodes

Copyright 2024 Cyber Physical Laboratory

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this software except in compliance with the License.
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.