🚀 Project Report Analysis: Home Automation Using Raspberry Pi and Weather API 🏠

1. 🔍 Topic Selection Process

The team aimed to use data from the web and output it through sensors, deciding to utilize the Raspberry Pi for this purpose. They chose Python for its utility in handling web data and settled on using the OpenWeatherMap API to control home automation based on weather conditions.

2. 🎯 Initial Project Goals

Initially, the project goal was broad, envisioning a cloud-based system interacting with devices and apps. The idea was to create a model where sensors act as furniture, controlled by external values and an app.

3. 🔧 Necessity

The project identified three main reasons for its necessity:

1. Energy Efficiency: Supplying power only when needed.
2. Time-Saving: Automating control of lights and temperature.
3. 24/7 Protection: Guarding against external threats like fine dust.

4. 📈 Market Trends

The report highlighted the high adoption rate of smart homes, particularly in the US, with significant market growth projected. It discussed popular smart home devices like Amazon Echo, Philips Hue, and August Smart Lock, emphasizing the ongoing integration of voice assistants like Alexa and Google Assistant into smart devices.

5. 💻 Development Environment

The Raspberry Pi runs on a Linux-based OS called Raspbian, which allows remote control via SSH. Python was chosen for its simplicity and the team’s familiarity. The initial setup involved installing the OS, updating the system, and configuring the Raspberry Pi for remote access using PuTTY.

6. 🛠 Technology and Development Process

The development process involved:

• Setting up Raspberry Pi and installing necessary software like Berryconda.
• Using the OpenWeatherMap API to fetch weather data.
• Writing Python code to control LEDs, a DC fan, and a servo motor based on weather data.
• Constructing circuits and configuring GPIO pins on the Raspberry Pi.

7. 📝 Final Code and Circuit

The report detailed the final code and circuit diagrams for controlling various components. It included Python scripts for fetching weather data and controlling hardware components based on this data.

8. 📚 Understanding and Difficulty

The project aimed to control sensors using Raspberry Pi based on API values. Python was chosen for its ease of use and extensive libraries. The difficulty level was rated as medium due to the initial learning curve and the extensive time required to understand and configure the Raspberry Pi and its peripherals.

9. ✅ Completion

While the final product did not meet the initial goal of app-based control, it achieved basic automation through mobile SSH. The team expressed a desire to further develop the project to include voice control and more advanced home automation features.

10. 💬 Feedback

The team appreciated the project for providing insight into practical application development and the current level of technology they could achieve. They aimed to further their skills and work on more advanced projects in the future.

11. 📚 References

The report included various references, from online resources like blogs and documentation to books and official websites related to Raspberry Pi and home automation technologies.

• Document: Drive (Only Supports Korean)