Building an IoT Light Intensity Monitor using LDR and the Bolt WiFi Module (ESP8266-12S)
The Internet of Things (IoT) has revolutionized the way we interact with the world around us, enabling us to collect and analyze data from various sensors remotely. In this blog post, I will explain how I've built a simple yet effective IoT project: a Light Intensity Monitor using an LDR (Light Dependent Resistor) and the Bolt WiFi Module (ESP8266-12S). This project will allow you to remotely monitor the intensity of light in a particular environment and make informed decisions based on the collected data.
Prerequisites
Before we dive into the project, make sure you have the following components ready:
Bolt WiFi Module (ESP8266-12S)
Light Dependent Resistor (LDR)
Resistor (10kΩ)
Bolt Cloud account (Sign up at cloud.boltiot.com if you haven't already)
Project Overview
The Light Intensity Monitor project involves building a circuit that uses an LDR to measure the intensity of light in the environment. The Bolt WiFi Module will then transmit this data to the Bolt Cloud platform, where you can visualize and analyze it in real time.
Circuit Connections
Connect one leg of the LDR to the 3.3V pin on the Wi-Fi module.
Connect the other leg of the LDR to the A0 (analog input) pin on the Wi-Fi module.
Connect one leg of the 10k Ohm resistor to the GND pin.
Connect the other leg of the 10kΩ resistor to the AO pin.
Setting Up the Bolt Cloud
Log in to your Bolt Cloud account.
Link your device to Bolt Cloud.
Create a new project.
Programming the Bolt WiFi Module
plotChart("time_stamp","light")
In the provided line of JavaScript code, the function plotchart()
is defined, taking two input arguments: time_stamp
, which captures the timestamp of the light intensity measurement, and light
, which is a variable responsible for storing the light intensity value.
Project Outcome
Upon completing the setup, your Bolt WiFi Module will start reading the light intensity using the LDR and send this data to the Bolt Cloud. This data can be valuable for various applications, such as optimizing indoor lighting, monitoring daylight exposure, or even studying natural light patterns.