Solar-Powered Smart Sensing System

This project involves the design and implementation of a solar-powered smart sensing system using the Raspberry Pi Pico W microcontroller and Amazon Web Services (AWS) IoT platform. The system collects environmental data using a DHT11 temperature and humidity sensor and sends the data to AWS IoT Core for further processing and storage.

Introduction

The demand for energy-efficient and sustainable solutions has led to the development of smart systems based on renewable energy sources. This project presents the design and implementation of a solar-powered smart sensing system using the Raspberry Pi Pico W and AWS IoT platform. The system is powered by a solar panel and a 18650 lithium battery, and it periodically collects sensor data, which is sent to AWS for analysis.

Components

• Raspberry Pi Pico W
• DHT11 temperature and humidity sensor
• 6V 250mA solar panel
• 3.7V 2200mAh 18650 lithium battery
• TP4056 charging module
• Schottky diodes
• Various connecting wires and resistors

Setup

1. Hardware Setup:

   • Connect the solar panel and battery to the TP4056 charging module.
   • Connect the DHT11 sensor to the Raspberry Pi Pico W (Pin 28).
   • Connect the TP4056 charging module to the Raspberry Pi Pico W for power supply.
   • Add Schottky diodes to protect the solar panel and battery.

2. Software Setup:

   • Install MicroPython on the Raspberry Pi Pico W.
   • Install required libraries (e.g., umqtt.simple, machine, dht).

3. AWS Setup:

   • Create an AWS IoT Core account and set up a new "Thing".
   • Download the necessary certificates and keys.
   • Configure AWS IoT Core, AWS Lambda, and DynamoDB for data storage and analysis.

Code Overview

The main components of the code are as follows:

• WiFi Connection: Connects to a specified WiFi network.
• MQTT Client: Configures and connects to the MQTT broker using TLS/SSL for secure communication.
• Sensor Data Collection: Reads temperature and humidity data from the DHT11 sensor.
• Data Transmission: Publishes the sensor data to the MQTT broker.
• LED Indications: Uses onboard LED to indicate different statuses (connection, data sent, error).

blink.py

Defines three LED blink modes:

• attention_blink: Infinite fast blink to indicate a problem.
• blink: Normal blink to indicate data has been successfully sent.
• fast_blink: Quick blink to indicate a successful connection.

Usage

1. Clone the repository:

   git clone https://github.com/yourusername/picow-smart-sensing.git