Bhavani's IoT level 2 report
Task 1: Watering a Plant Using a Solenoid Valve
I implemented an automatic plant watering system using an ESP32, a soil moisture sensor, a relay, and a solenoid valve. The system monitored soil moisture and displayed a message when levels were low. However, the solenoid valve did not activate, likely due to relay wiring or power supply issues.
Task 2: Introduction to RFID
I interfaced an RFID card reader with the ESP32 and successfully read the unique hex code of a metro card. The hex code was displayed on an LCD screen. This task helped me understand how RFID communication works and how to extract unique identifiers from RFID tags.
Task 3: Interfacing RTC Module with ESP32
I connected a DS3231 RTC module to the ESP32 to display real-time clock data on the serial monitor. The system successfully retrieved and displayed time, demonstrating the use of I2C communication for real-time data acquisition.
Task 4: Creating an Attendance Logger
I attempted to build an attendance logging system using an RFID card reader and ESP32. The system was designed to scan RFID cards and send the ID along with a timestamp to Google Sheets using Zapier. However, I faced issues in sending data to Google Sheets, possibly due to incorrect API configurations or authentication errors in Zapier. I am trying to resolve this by checking API authentication, webhook configurations, and debugging the data transfer process.
Task 6 - Controlling Multiple Peripherals Using SPI Protocol
I used SPI communication to interface an RFID module with an ESP32 and control a DC motor using the L298N motor driver. Based on the scanned RFID card, the motor moved forward or backward. The RFID module successfully identified cards.
Task 7 - Telegram Bot Motor Control
I created a Telegram bot to control a DC motor in both directions using ESP32. The bot was set up successfully, and the ESP32 was connected, but the bot did not respond to messages. I am currently troubleshooting the issue, checking if the ESP32 is correctly receiving and processing bot commands.
Task 8 - Alexa Light Control
I successfully implemented voice-controlled light switching using a Python script and an ESP32 web server. The script used speech recognition to detect commands like "light on" and "light off" and sent HTTP requests to the ESP32, which controlled an LED based on the received commands. The ESP32 acted as a web server, processing the requests and toggling the light accordingly. This method allowed for local smart home automation without relying on external cloud services. The implementation worked as expected, and the system responded accurately to voice commands.