Week 5 and 6 Sensors and Embedded Systems

Sensors and Embedded Systems


Introduction

Welcome to our journey into the world of servo motors! In this project, we're discovering how these special motors can help machines react to changes in their environment. Imagine a world where machines can move or adjust by themselves based on what they 'see' or 'feel'—that's exactly what we're exploring with servo motors.

Our Project Kit

We got our hands on some cool stuff for this project:

  • Sensors: We used sensors like photoresistors to see how bright it is and thermistors to measure temperature changes.

  • Transducers: These are like the translators in our project. They help the sensors talk to the servo motor by converting their signals.

  • Servo Motor: This is the star of our show! The servo motor is like a little robot arm that can move in precise ways.

Types of Output

Our project mainly focused on the servo motor. It's the part that moves based on what the sensors tell it. So, when the light changes or the temperature goes up, the servo motor responds by moving in a certain way. It's like magic!

Code Stuff

To make all this happen, we used something called the Arduino IDE. It's like a special tool that lets us write instructions for the Arduino board. We wrote simple commands in a language called Arduino, which is like a simplified version of C/C++. These commands told the Arduino board how to read the sensor data and control the servo motor.

Use of Input and Output

In our project, we used input from the sensors to trigger actions by the servo motor. For instance, when the light sensor detected darkness, it sent a signal to the servo motor to turn on a light. This demonstrates how sensors provide input to the system, which then produces output through the servo motor's movement.

Analog vs. Digital

The signals from our sensors can be either analog or digital. Analog signals are like a smooth wave, providing continuous data about things like light intensity or temperature. Digital signals, on the other hand, are like simple on/off switches, providing discrete information. We used both types of signals in our project to detect changes in the environment and control the servo motor's movement accordingly.












.


Comments

Post a Comment

Popular posts from this blog

Week 11-17 Group Project

Image
  In our group project, my friends Shakline, Nelushan, and I teamed up to create something exciting: a lie detector machine. Our aim was to use Arduino technology to figure out when someone might be lying. We used two fancy sensors: one to measure heart rate changes (ECG sensor) and another to track sweat levels on the skin (GSR sensor). These changes often happen when someone is feeling stressed, like when they're not telling the truth. To complete our lie detector setup, we also placed the skin sensor between two fingers. This sensor helps measure changes in skin conductivity, which can indicate stress levels. By positioning it this way, we could get accurate readings of how much a person might be sweating, adding another layer to our detection system. For our lie detector, we placed the pads of the ECG sensor on different pulse points. We used three colors of pads: green, yellow, and red. Each color was for a specific pulse point. We had a picture showing where to put the pads ...
Read more

week 18 Recommender systems

Image
  Recommender systems Exploring Recommender Systems: Shaping User Experiences This week's exploration led me into the fascinating world of recommender systems, which play a vital role in shaping the user experiences of modern online platforms like Netflix and Amazon. Throughout this journey, I delved into understanding how these systems personalize recommendations based on individual preferences derived from past interactions. Harnessing Data for Personalization Recommender systems harness various data inputs, including user behavior and item characteristics, to suggest products or content tailored to each user. Beyond enhancing user experience, these systems are essential for businesses to stay competitive by quickly adapting to consumer needs and staying ahead of technological advancements. The Role of Machine Learning in Recommender Systems A key aspect of our exploration was uncovering the role of machine learning in powering recommender systems. Machine learning algorithms an...
Read more

week 21 Intro too AI

Image
  Intro too AI This week, we delved into the XOR challenge, a key puzzle in the field of artificial intelligence (AI) that initially stumped early AI models. The XOR (exclusive OR) logic gate is simple yet tricky: it outputs true only when the inputs differ. For a while, early neural networks couldn’t crack it due to its non-linear nature, highlighting a crucial limitation in AI's early days. Addressing this puzzle required a rethink of neural network design. By integrating more layers and employing varied activation functions, these networks gained the ability to grasp the XOR’s complexities, marking a leap forward in AI's capability to solve non-linear problems. Our practical exploration involved programming an Arduino Uno to tackle the XOR problem with a neural network. This setup included configuring the network with layers for input, hidden processing, and output, then training it with appropriate data. The training process is pivotal: through repeated cycles, the network ...
Read more