AI and Embedded Systems

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Hardware

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High-Performance Computer / Workstation
  • High-performance computer or workstation
  • Multi-core CPU (Intel i7/i9 or AMD Ryzen)
  • GPU (NVIDIA RTX, Jetson, or Tesla cards for deep learning)
  • 16–32 GB RAM minimum (64 GB+ recommended)
  • SSD storage (fast read/write for datasets)
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Edge AI Hardware
  • NVIDIA Jetson Nano
  • NVIDIA Jetson Xavier NX
  • Google Coral Dev Board / TPU
  • Raspberry Pi 4 / 5
  • Intel Neural Compute Stick 2
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Sensors & Cameras for AI
  • RGB, IR, and depth cameras (stereo, LiDAR, Time-of-Flight)
  • Machine vision cameras with high frame rates
    • Environmental Sensors
  • Temperature sensors
  • Humidity sensors
  • Pressure sensors
  • Gas sensors
  • Light sensors
  • Proximity sensors
    • Inertial Sensors
  • IMUs (accelerometer, gyroscope, magnetometer)
    • Microphones / Arrays
  • Microphone modules
  • Microphone arrays for sound localization
  • Acoustic AI project microphones

Embedded Systems – Common Requirements

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Microcontrollers & Boards
  • Arduino Uno / Mega / Nano
  • ESP32 / ESP8266 (Wi-Fi + Bluetooth)
  • STM32 Nucleo boards
  • Raspberry Pi 4 / Pico (Wireless)
  • BeagleBone Black
  • Teensy series
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Sensors & Actuators
    Sensors
  • Temperature & Humidity (DHT11, DHT22)
  • Ultrasonic distance sensor (HC-SR04)
  • PIR motion sensor
  • IR sensor
  • LDR (light sensor)
  • Accelerometer & Gyroscope (MPU-6050)
  • Gas sensors (MQ-2, MQ-135)
    • Actuators:
  • Servo motors (SG90, MG995)
  • DC motors
  • Stepper motors
  • Relays (5V / 12V)
  • Buzzers
  • LEDs
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Networking & Communication Modules
  • Wi-Fi / Bluetooth / BLE modules
  • Ethernet and 5G/LTE modems for real-time connectivity
  • LoRa / ZigBee modules for low-power AIoT networks
  • GPS / GNSS receivers for location-aware applications
  • Edge gateways for data aggregation and cloud synchronization
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Power, Support & Testing Hardware
  • Regulated DC power supplies and battery packs (Li-ion, Li-Po)
  • UPS and surge protection for servers
  • Multimeters, oscilloscopes, and logic analyzers for signal testing
  • Soldering and rework stations for prototype assembly
  • Thermal cameras / sensors for hardware diagnostics
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Data Handling & Storage Systems
  • Local NAS or SAN setups for dataset hosting
  • Cloud storage (AWS S3, Google Cloud Storage, Azure Blob)
  • High-speed transfer systems (10GbE, Thunderbolt, USB 3.2)
  • Backup drives and RAID storage configurations

Common Overlap (AI + Embedded Integration)

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  • Raspberry Pi 4 / Jetson Nano (AI computing + I/O control)
  • Camera modules with ML models (TensorFlow Lite / Edge TPU)
  • Microcontroller units (ESP32 or STM32) for sensor control
  • Cloud platforms for data logging (ThingSpeak, AWS IoT, Blynk)
  • AI frameworks optimized for edge devices (TensorFlow Lite, PyTorch Mobile, OpenVINO)