BLOG · 30/12/2025
LVL2
 | OP |
MARVEL LEVEL 2 TASKS
TASK 1: Smart Irrigation System
This system behaves like a smart caretaker for plants. The soil moisture sensor constantly checks how wet or dry the soil is. When the soil becomes too dry (crosses the set threshold), the ESP32 instantly reacts by switching ON the relay. This relay acts like a switch that opens the solenoid valve, allowing water to flow to the plant.
Once the soil absorbs enough water and becomes moist again, the sensor detects this change. The ESP32 then turns OFF the relay, closing the solenoid valve and stopping the water supply. This cycle repeats automatically every second, ensuring the plant gets water only when needed, preventing both overwatering and underwatering. Overall, the system mimics human judgment, but works continuously and reliably without supervision. Esp32 doesnt support 5v logic to trigger relay module of 5v provided so arduino uno has been used.
TASK 2: Smart Parking System
This smart parking system works like an automatic parking attendant. Each parking slot has an ultrasonic sensor that continuously checks whether a car is present by measuring distance. When a vehicle comes close to the sensor, the ESP32 identifies the slot as occupied. This status is instantly sent over Wi-Fi to the Blynk app the platform that i have used for this task.
On the mobile app, LEDs turn ON and labels update to show “Seat Occupied” or “Not Occupied” in real time. If the car leaves the parking space, the distance increases and the system automatically updates the app. This allows users or parking managers to monitor parking availability remotely without manual checking. Though it has some draw backs it just works fine.
TASK 3: Smart Street Lighting with Node-RED Dashboard
This smart street lighting system works like an intelligent city light controller. The LDR continuously checks whether it is day or night by sensing ambient light. When it becomes dark, the system stays alert but keeps the street light dimmed or OFF to save power. As soon as a pedestrian or vehicle is detected by the PIR sensor, the ESP32 instantly turns the street light ON using a relay.
At the same time, all sensor readings and light status are sent wirelessly to a Node-RED dashboard through MQTT. The dashboard shows live light intensity, motion detection, and lamp status, allowing real-time monitoring. Once motion stops, the light automatically turns OFF again, ensuring energy-efficient and smart street illumination. Add fun working with it!
TASK 4: Intro to RFID and Attendance Logger
This system that i built works like a digital attendance register. Each person carries an RFID card with a unique ID. When the card is brought near the RFID reader, the ESP32 instantly reads its identity. In the first part, this ID is simply displayed on the serial monitor to understand how RFID works. Metro card uses a slight advanced technology for the same so the UID's cant be read that easily but yeah was able to read other card.
In the second part, the same card ID is sent through Wi-Fi to Google Sheets, where it is stored along with the current time. This removes the need for manual attendance marking. The entire process is fast, contactless, and automatically stored in the cloud, making it suitable for classrooms, offices, and secure entry systems. Initially each UID should be associated with specefic candidate name.
TASK 5: House Security System
The task was designed to be workaround esp32's cam module but i had faced problem, so switched to a old phone which streams the video and can be accessed via Ip address. This security system works by separating sensing, vision, and intelligence. The cam continuously monitors and a PIR motion sensor placed near the entrance. When motion is detected, the ESP32 sends a real-time signal to the Blynk cloud. A Python application running on a computer listens for this signal. Once triggered, Python logic triggers.
OpenCV analyzes the live video feed to detect human presence. If a person is detected, an image is captured and emailed as an alert. This design keeps it lightweight while enabling advanced security features. Fun working with Computer vision.
TASK 6: Red Light Green Light Game
Same as earlier task i ended up doing this task with a Ip cam, whole python script runs on computer and the video feed should be provided wither default cam or any external sources.
This project recreates the “Red Light Green Light” using computer vision. An ESP32-CAM or mobile camera streams live video to a Python program. The game alternates between GREEN and RED light states at fixed intervals. During GREEN light, the player is allowed to move and earns progress points. During RED light, OpenCV detects motion using frame-difference analysis. If motion is detected during RED light, the player is eliminated instantly. Visual indicators and a score bar provide real-time game feedback. This project demonstrates motion detection, game logic, and vision-based control. If a buzzer is included it makes things interesting.
TASK 7: Creating Your Own Home Assistant
I had to use the laptop as microprocessor, failed to do the TTS and STT with the SPI mic and amplifier Boards provided and used local host ai model that was easy access for me compared to API calls from cloud based models.
This project implements a smart voice-controlled home assistant using AI. The microphone captures voice commands, which are first processed offline for speed. If offline recognition fails, Whisper provides accurate speech recognition. Recognized commands control home appliances through an ESP32 or Arduino using relays. For general questions, the system forwards the query to an AI model (Ollama/ChatGPT). The assistant responds using text-to-speech for a natural interaction. Duplicate commands are filtered to protect hardware. The system works fully offline with optional AI enhancement. This project demonstrates AI-powered automation and real-time IoT control.
THANK YOU!