Description
IOT TRAINING SYSTEM
Experiment Content :
Basic IoT Sensor Integration: Interface temperature, humidity,
and light sensors to display real-time readings on the LCD.
Smart Home Simulation: Use PIR sensors for motion detection to automate lights and fans.
Speech-Activated Devices: Control LEDs or fans using voice
commands with Google Assistant integration.
Environmental Monitoring: Monitor air quality using gas,
dust, and temperature sensors and display results.
AI-Based Object Detection: Detect objects or movements
using ultrasonic or PIR sensors and trigger actions like alarms.
Gesture Control System: Control RGB LEDs or other devices
using hand gestures detected by the gesture sensor.
Data Logging and Persistence: Store sensor data (temperature, humidity, etc.) in a local or cloud-based database for analysis.
ET 25 0011
AI-Powered Smart Farming: Automate irrigation based on
soil moisture and temperature data using relays and water pumps
Technical Specification :
Main module supporting AI acceleration calculation,
multimedia and various IoT sensors should be integrated
into the base board.
Minimum 5-inch TFT LCD with 800×480 or higher resolu
tion and Minimum 8M pixel high resolution camera
Digital microphones and speakers should support cloud
based speech recognition and audio playback
Minimum 4 dedicated expansion interfaces support various
IoT sensor modules Soda OS, the exclusive AIoT operating system, and Pop library
A dedicated web browser-based learning environment for training Python 3 and C/C++
Educational contents for IoT sensor control, multimedia and AI.
Training Contents:
Introduction to AIoT Home:
Configuration and Practice Environment of AIoT Home
Python and Linux 101
IoT Application Technology
Sensor Control:
File and DB-Based Data Persistence
Audio Recording and Playback
Google Text-to-Speech Converter, Google Assistant and
User Device Actions
AI Technology:
Numpy for Fast Multidimensional Matrix Operations
Pandas for Time Series and Tabular Data Analysis
Matplotlib for Data Visualization
Supervised and Unsupervised Learning
Theory & Practice for Pop.AI-based Linear and Logistic
Regression Algorithm, Perceptron, ANN, DNN, and CNN &
OpenAI DQN-based Reinforcement Learning
Understanding Tensorflow.
Software Specifications:
Soda OS:
Linux Kernel: 4.19
Desktop: X-Server, Openbox, LightDM, Tint2, blueman,
network-manager, conk CLI: Zsh, Tmux, Peco, powerlevel9k
thema, Powerline fonts
IDE: Visual Studio Code, NeoVim, Geany
Data Science & AI: Python3, Numpy, Matplotlib, sympy,
Pandas, Seaborn, Scipy, Gym Scikit-learn, Tensorflow, Kerast.
Pop Library:
Output Object (C/C++, Python3): Led, Laser, Buzzer, Relay,
RGBLed, DCMotor, StepMotor, OLed, PiezoBuzzer,
PixelDisplay, TextLCD, FND, Led Bar
Input Object (C/C++, Python3): Switch, Touch, Reed,
LimitSwitch, Mercury, Knock, Tilt, Opto, Pir, Flame LineTrace,
TempHumi, UltraSonic, Shock, Sound, Potentiometer, CdS,
SoilMoisture, Thermistor, Temperature, Gas, Dust, Psd. Gesture
AI (Python3): Linear Regression, Logistic Regression,
Perceptron, ANN, DNN, CNN, DQN
Hardware Specifications:
Channel: Input 2ch, Output 2ch
2CH Microphone
Stereo Speaker
Servo Motor:
Working Speed: 0.12sec/60 (4.8V no Load)
Stall torque: 1.2kg/cm (4.8V), 1.6kg/cm (6.0V)
TEXT LCD:
Format Size: 16 X 2 or higher
LED B/L, Black and White
Interface: GPIO
LED: (1×3) Group x 3EA: Light Display
Stand Light Display 1EA
Interface: GPIO
RGB LED:
Size: 5pi
Wavelength: RED (630 nm), GREEN (525 nm), BLUE (430nm)
Interface: I2C
PIEZO:
Rated Current: Max 30mA
Sound Output at 10cm(dB): Min 85dB
FAN:
Main Module:
CPU: 6-core NVIDIA Carmel ARM v8.2 64-bit; 6MB L2 + 4MB
L3; Max Freq: 2-core@1900MHz, 4/6-core@1400Mhz
GPU: 384-core NVIDIA VoltaTM GPU with 48 Tensor Cores
Max Freq: 1100MHz
Memory: Minimum 8GB 128-bit LPDDR4x@ 1600MHz
Video Encoder: 2x464MP/sec(HEVC),2x4k@30(HEVC); 6x
1080p@ 60(HEVC), 14x 1080p@ 30(HEVC)
Video Decoder: 2x690MP/sec(HEVC), 2x4k@ 60(HEVC),
4x4k@30(HEVC); 12x1080p@ 60(HEVC), 32x 1080p@
30(HEVC), 16x 1080p@30(H.264)
CSI Camera: Up to 6 cameras (36 via virtual channels); 12
Lanes MIPI CSI-2, D-PHY 1.2 (up to 30 Gbps)
Connectivity: Dual Band Wireless Wi-Fi 2GHz/5GHz Band,
867Mbps, 802.11ac; Bluetooth 4.2; 10/100/1000 Base-T Ethernet
Display: 2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0
USB: Min. 4x USB 3.0, Min. USB 2.0 Micro-B
Base Board:
Camera: Image Sensor: Sony IMX219
Resolution: Min. 8M Pixel Native Resolution Sensor (3280 x
2464 or higher Pixel Static Images)
Video: 1080p30, 720p60 and 640x480p90
Linux Integration: V4L2 Driver Available
Sound: Sound IC: WM8960
Channel: Input 2ch, Output 2ch
2CH Microphone
Stereo Speaker
Servo Motor:
Working Speed: 0.12sec/60 (4.8V no Load)
Stall torque: 1.2kg/cm (4.8V), 1.6kg/cm (6.0V)
TEXT LCD:
Format Size: 16 X 2 or higher
LED B/L, Black and White
Interface: GPIO
LED: (1×3) Group x 3EA: Light Display
Stand Light Display 1EA
Interface: GPIO
RGB LED:
Size: 5pi
Wavelength: RED (630 nm), GREEN (525 nm), BLUE (430nm)
Interface: I2C
PIEZO:
Size: 30 X 30mm
Speed: 900RPM
Supply Voltage: 5V
LED BAR x 2EA:
Size: 20 X 10mm
Humidity & Temperature Sensor:
Humidity Resolution: 12bit(0.04%RH), 8bit(0.7%RH)
Humidity Accuracy: +-3%RH or better
Temperature Resolution: 14bit(0.01C), 12bit(0.04C)
Temperature Accuracy: +-4°C or better
PIR Sensor:
Transmittance: ≥75%
Detecting Distance: 10~80cm
DUST Sensor:
Based on Laser Scattering Technology
Measured Particle Size: 0.3μm~10μm
Measurement Range: PM1.0/PM2.5/PM10: 0~1,000μg/m³
TFT LCD:
Size: 4 inch
Resolution: 800X480 or higher
IPS technology, High quality and perfect displaying from
very wide viewing angle
Interface: HDMI
Illuminance Sensor:
Sensor: CdS
Power Dissipation (at 25): 100mW
Temp. Range: -30~+70
Interface: AD
GAS Sensor:
Measure: LPG, Alcohol, Propane, Hydrogen, CO and Even
Methane
Touch Keypad:
12 Key Input
Sensor Module Block:
Sensor Block1: +5V, +3.3V, GND, I2C, ADC, GPIO
Sensor Block2: +5V, +3.3V, GND, I2C, ADC, GPIO
Sensor Block3: +5V, +3.3V, GND, SPI, GPIO
Sensor Block4: +5V, +3.3V, GND, ADC, GPIO
Main Board Size: Minimum 460 X 310 (mm)
Sensor Pack:
Flame Module:
Sensing Range: 60 Degree
Eco Sensor Module:
Light Sensor: Illuminance to digital converter; Wide range: 1
~ 65535(lx)
Temperature Measure: -40 ~ 85 or higher
Humidity Measure: 0 ~ 100%r.H.
Pressure Range: 300 ~ 1100hPa or higher
VOC Measure: Ethane, Ethanol, Acetone, Carbon Monoxide,
Butadiene, methyl
Carbon Dioxide (CO2) Gas Sensor Module:
Measuring Range: 0 ~ 10000 ppm or higher
Accuracy: ±7%~±50ppm or better
Pixel Display:
Color: Pixel RGB
Pixel: 8×8
Digital Thermopile Module Laser (DTPML):
IR Refresh Rate: 50Hz
Digital Resolution: 0.1
Accuracy: ±2% or better
Microwave Motion Sensor Module:
Frequency Setting: 10.525 GHz (Typ)
Spurious Emission: -7.3 dBm
Pulse Repetition Frequency: 2KHz
IR Receiver Module:
Carrier Frequency: 38kHz
PIR Senor Module:
Sensing Range: 110°
Spectral Response: 5 ~ 14 um
Accessories :
Single-phase power cord
4mm Banana Socket-1Set
User Manual
Others :
Country of Origin: China
Manufacturing: Assemble in Bangladesh
Installation
3 Days Training
Warranty: 01 year
