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Line following and obstacle avoiding robot

Line following and obstacle avoiding robot

An black Line Follower And Obstacle Avoiding Robot using Arduino UNO, IR Sensor, L298n motor driver and HC-SR04 ultrasonic sensors.
Robot hand

Robot hand

Robot hand use Servo and PCA9685 and it was controlled by ps2 joy stick.
Nethouse manager system

Nethouse manager system

System manage pump, Display and alert Nethouse status. Setup condition for control system.
Read temperature - humidity and output to LCD screen

Read temperature - humidity and output to LCD screen

This article will guide you how to read the temperature - humidity from the sensor and output to the LCD screen. Help you get acquainted with Arduino. Read data from DHT11 temperature-humidity sensor. Use the LCD display to output information. Equipment includes: 1. LCD screen 16x2; 2. The LCD control circuit uses I2C communication. 3. DHT11 temperature sensor; 4. Arduino R3 circuit or equivalent.
Artificial intelligence with IBM Watson and Raspberry Pi (Part 1)

Artificial intelligence with IBM Watson and Raspberry Pi (Part 1)

Artificial intelligence with IBM Watson and Raspberry Pi (Part 1): Guide you to make an "intelligent" face recognition key with Raspberry Pi. Since Pi's resources are limited, part of the work (specifically the training part) must be done by another system, your personal computer. This is also the trend of artificial intelligence hardware products in the future: physical hardware is connected to the cloud / supercomputer to solve intelligent algorithms, give up resources to robots. with the peripheral environment. To better understand this issue I will guide you in this article to build a voice recognition system and guess what the mood of the speaker is happy. The operating principle of the system consists of the following 3 steps: Raspberry Pi will record the sound from the wecam with the microphone and save it to speech.wav file. Then we will use python to send this file to the IBM cloud to translate into sign text. This is handled by the Speech-to-text API. Text will be sent to the IBM AlchemyLanguage service for mood statistics and analysis. This is handled by AlchemyAPI. (Details will be guided at the Institute seminars, follow specific schedule).
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