🗑️ SenseBin — Smart Dustbin

Industry-Oriented Embedded Systems & IoT Project

SenseBin is an ESP32-based smart waste-management system designed to automate dustbin monitoring, touchless lid operation, and waste-level detection. The system combines ultrasonic sensing, servo motor control, embedded firmware, alert mechanisms, and a real-time IoT dashboard to demonstrate an industry-oriented smart waste-management solution.

The project is developed with a hardware-ready architecture and a Wokwi virtual simulation, making it possible to develop and validate the complete embedded system without physical hardware.

🚀 Project Overview

Traditional waste bins require manual checking to determine whether they are full. This can result in unnecessary collection trips, overflowing bins, poor maintenance efficiency, and hygiene concerns.

SenseBin addresses this problem by continuously monitoring the bin and automatically responding to detected objects and waste levels.

The system provides:

🤖 Touchless automatic lid operation
📡 Ultrasonic-based object detection
📊 Real-time waste-level estimation
🚨 Full-bin alert generation
💡 LED-based status indication
🔊 Buzzer-based critical alert
⚙️ Servo-controlled lid
📟 Local status monitoring through OLED
🌐 Flask-based telemetry API
📈 Real-time web dashboard
🧪 Wokwi virtual embedded-system simulation

🎯 Objectives

The main objectives of SenseBin are:

Detect a nearby hand/object without physical contact.
Automatically open and close the dustbin lid.
Measure the distance between the sensor and waste.
Calculate the approximate waste-fill percentage.
Classify the bin as NORMAL, HIGH, or FULL.
Generate visual and audible alerts when collection is required.
Stream telemetry to a monitoring dashboard.
Validate the embedded system using virtual simulation.

🏗️ System Architecture

                    ┌──────────────────────┐
                    │       ESP32          │
                    │   Microcontroller    │
                    └──────────┬───────────┘
                               │
             ┌─────────────────┴─────────────────┐
             │                                   │
             ▼                                   ▼
   ┌──────────────────┐               ┌──────────────────┐
   │ HC-SR04 Sensor 1 │               │ HC-SR04 Sensor 2 │
   │ Hand/Object      │               │ Waste Level      │
   │ Detection        │               │ Measurement      │
   └────────┬─────────┘               └────────┬─────────┘
            │                                  │
            ▼                                  ▼
   Object Detection                    Distance Measurement
            │                                  │
            ▼                                  ▼
     Servo Control                       Fill Calculation
            │                                  │
            ▼                                  ▼
       Lid OPEN/CLOSE                 NORMAL/HIGH/FULL
                                               │
                           ┌───────────────────┼──────────────────┐
                           │                   │                  │
                           ▼                   ▼                  ▼
                       Green LED           Red LED             Buzzer
                           │                   │                  │
                           └───────────────────┴──────────────────┘
                                               │
                                               ▼
                                    Telemetry / Monitoring
                                               │
                                               ▼
                                    Flask REST API
                                               │
                                               ▼
                                    SenseBin Dashboard

⚙️ Hardware Components

Component	Purpose
ESP32	Main microcontroller
HC-SR04 #1	Hand/object detection
HC-SR04 #2	Waste-level measurement
Servo Motor	Automatic lid control
Green LED	Normal status
Red LED	High/full status
Buzzer	Critical/full-bin alert
OLED Display	Local system information
Breadboard	Circuit prototyping
Jumper Wires	Component connections

Note: Physical hardware is optional for this implementation. The embedded circuit is validated using Wokwi simulation.

🧠 Embedded System Logic

1. Object Detection

The first ultrasonic sensor monitors the area near the dustbin.

Object Distance ≤ Detection Threshold
                ↓
        Object Detected
                ↓
          Servo Activated
                ↓
            Lid OPEN

After the configured delay:

Lid CLOSE

2. Waste-Level Detection

The second ultrasonic sensor measures the distance between the sensor and the waste surface.

Assuming a known bin height:

Fill Level = Bin Height − Measured Distance

The fill percentage is calculated as:

Fill Percentage =
((Bin Height − Measured Distance) / Bin Height) × 100

Example for a 30 cm bin:

Waste Level	Sensor Distance	Status
0%	30 cm	NORMAL
25%	22.5 cm	NORMAL
50%	15 cm	NORMAL
75%	7.5 cm	HIGH
90%	3 cm	FULL

🚦 Status Classification

0–74%
   ↓
NORMAL
   ↓
Green LED

75–89%
   ↓
HIGH
   ↓
Warning indication

90–100%
   ↓
FULL
   ↓
Red LED + Buzzer

📡 Telemetry

SenseBin uses a lightweight telemetry structure to communicate sensor and system states.

Example:

{
  "event": "object_detected",
  "fill_percentage": 50,
  "status": "NORMAL",
  "lid": "OPEN",
  "alert": false,
  "hand_distance": 15,
  "bin_distance": 15
}

Telemetry fields:

Field	Description
`event`	Current system event
`fill_percentage`	Calculated waste level
`status`	NORMAL / HIGH / FULL
`lid`	OPEN / CLOSED
`alert`	Collection alert state
`hand_distance`	Object detection distance
`bin_distance`	Waste sensor distance

🌐 IoT Dashboard

The project includes a futuristic web dashboard designed specifically for SenseBin telemetry.

Dashboard Features

Real-time waste level
Bin status
Lid status
Sensor distance
Object detection state
Collection alerts
Waste-level trend
Activity/event log
Sensor telemetry
System status

The dashboard does not use unrelated metrics. All displayed values correspond to actual SenseBin sensor inputs, calculated states, actuator states, or system events.

🖥️ Backend

The project uses a lightweight Flask backend.

frontend
    │
    │ GET
    ▼
Flask Server
    │
    │ telemetry
    ▼
SenseBin Dashboard

API Endpoint

GET /api/telemetry

Used by the dashboard to retrieve the latest SenseBin telemetry.

Telemetry Input

Telemetry can also be simulated directly from the terminal using:

backend/telemetry_input.py

Example:

{"event":"bin_full","fill_percentage":90,"status":"FULL","lid":"CLOSED","alert":true,"hand_distance":100,"bin_distance":3}

🧪 Virtual Simulation

The embedded system is simulated using Wokwi.

The simulation includes:

ESP32
Two ultrasonic sensors
Servo motor
Green LED
Red LED
Buzzer
OLED display
Serial Monitor

Simulation Workflow

Sensor Input
     ↓
ESP32 Firmware
     ↓
Sensor Processing
     ↓
Decision Logic
     ↓
Servo / LED / Buzzer
     ↓
Serial Monitor

🧪 Testing Scenarios

Test 1 — Object Detection

Hand Distance : 2.9 cm
Bin Distance  : 100.9 cm
Fill Level    : 0%
Status        : NORMAL
Lid           : OPEN

Expected:

Object Detected
Servo → OPEN
Green LED → ON

Test 2 — Normal Bin

Fill Percentage : 50%
Status          : NORMAL
Lid             : CLOSED
Alert           : FALSE

Expected:

Green LED → ON
Red LED → OFF
Buzzer → OFF

Test 3 — High Fill Level

Fill Percentage : 75%
Status          : HIGH
Lid             : CLOSED
Alert           : FALSE

Expected:

Warning state activated

Test 4 — Full Bin

Fill Percentage : 90%
Status          : FULL
Lid             : CLOSED
Alert           : TRUE

Expected:

Red LED → ON
Buzzer → ON
Collection Required

📁 Project Structure

Smart-Dustbin/
│
├── backend/
│   ├── server.py
│   └── telemetry_input.py
│
├── frontend/
│   ├── index.html
│   ├── styles.css
│   ├── app.js
│   └── sb.jpeg
│
├── wokwi/
│   ├── sketch.ino
│   ├── diagram.json
│   └── libraries.txt
│
├── screenshots/
├── circuit_diagram/
├── reports/
├── docs/
│
├── requirements.txt
├── README.md
└── .gitignore

📂 Directory Description

`backend/`

Contains the Flask telemetry server and terminal-based telemetry simulator.

`frontend/`

Contains the SenseBin IoT monitoring dashboard.

`wokwi/`

Contains the embedded firmware and Wokwi circuit configuration.

`screenshots/`

Project demonstration screenshots.

`circuit_diagram/`

Circuit and wiring documentation.

`reports/`

Project reports and documentation.

`docs/`

Additional technical documentation.

🛠️ Software Requirements

Python 3.x
Flask
Flask-CORS
Requests
Arduino IDE or Wokwi
VS Code
Modern web browser

▶️ Running the Project

1. Install Backend Dependencies

pip install flask flask-cors requests

2. Start Flask Server

cd backend
python server.py

The server runs at:

http://localhost:3000

3. Start Telemetry Input

Open another terminal:

cd backend
python telemetry_input.py

Send telemetry as JSON.

Example:

{"event":"object_detected","fill_percentage":50,"status":"NORMAL","lid":"OPEN","alert":false,"hand_distance":15,"bin_distance":15}

4. Open Dashboard

Open:

frontend/index.html

using VS Code Live Server.

The dashboard retrieves telemetry from:

/api/telemetry

📊 Example Telemetry Sequence

The dashboard can be tested using a progressive waste-level sequence:

0%

{"event":"bin_monitoring","fill_percentage":0,"status":"NORMAL","lid":"CLOSED","alert":false,"hand_distance":100,"bin_distance":30}

25%

{"event":"bin_monitoring","fill_percentage":25,"status":"NORMAL","lid":"CLOSED","alert":false,"hand_distance":100,"bin_distance":22.5}

50%

{"event":"object_detected","fill_percentage":50,"status":"NORMAL","lid":"OPEN","alert":false,"hand_distance":15,"bin_distance":15}

75%

{"event":"bin_warning","fill_percentage":75,"status":"HIGH","lid":"CLOSED","alert":false,"hand_distance":100,"bin_distance":7.5}

90%

{"event":"bin_full","fill_percentage":90,"status":"FULL","lid":"CLOSED","alert":true,"hand_distance":100,"bin_distance":3}

This produces a meaningful Waste Level Trend from 0% → 25% → 50% → 75% → 90%.

🔬 Testing & Validation

The system is validated across three layers:

Embedded Layer

Ultrasonic Sensors
        ↓
ESP32
        ↓
Servo / LED / Buzzer

Backend Layer

Telemetry JSON
        ↓
Flask REST API
        ↓
HTTP 200 Response

Dashboard Layer

API Telemetry
        ↓
Real-Time Visualization
        ↓
Status / Trends / Alerts

This layered architecture allows the embedded system, communication layer, and monitoring interface to be tested independently.

🏭 Industry Relevance

Smart waste-management systems can improve operational efficiency in:

Smart cities
Hospitals
Airports
Railway stations
Shopping malls
Office buildings
Educational campuses
Industrial facilities
Public spaces

Potential benefits include:

Touchless waste disposal
Improved hygiene
Reduced manual monitoring
Early detection of overflowing bins
More efficient collection planning
Reduced unnecessary collection trips
Real-time operational visibility

🔮 Future Enhancements

The current system can be extended with:

ESP32 Wi-Fi telemetry
MQTT communication
Cloud-based monitoring
Multiple-bin management
GPS-based bin tracking
Mobile notifications
Predictive waste-level analytics
Waste collection route optimization
Battery and power monitoring
Solar-powered operation
Machine-learning-based collection prediction

🎓 Embedded Systems Concepts Demonstrated

This project demonstrates practical implementation of:

Microcontroller programming
GPIO
Digital input/output
Ultrasonic sensing
PWM
Servo motor control
Sensor interfacing
Threshold-based decision making
Actuator control
Embedded C / Arduino programming
Serial communication
Sensor calibration
Real-time telemetry
REST API communication
IoT dashboard integration
Virtual hardware simulation
System testing and validation

📸 Project Evidence

The repository contains evidence of:

Wokwi embedded-system simulation
Sensor readings
Servo response
LED and buzzer alerts
Flask telemetry communication
SenseBin dashboard
Waste-level trend visualization
Full-bin detection

👨‍💻 Project Type

Domain: Embedded Systems / IoT / Smart Infrastructure

Project Level: Industry-Oriented Student Project

Controller: ESP32

Simulation: Wokwi

Backend: Python + Flask

Frontend: HTML + CSS + JavaScript

Communication: REST API / JSON Telemetry

📌 Conclusion

SenseBin demonstrates how an embedded system can combine sensing, real-time decision-making, actuator control, telemetry, and visualization into a practical smart-infrastructure solution.

By integrating ESP32 firmware, ultrasonic sensors, servo control, alert mechanisms, virtual hardware simulation, Flask telemetry, and a real-time dashboard, the project provides a complete prototype architecture for intelligent waste-level monitoring and automated waste-bin management.

Name		Name	Last commit message	Last commit date
backend		backend
frontend		frontend
screenshots		screenshots
wokwi		wokwi
.gitignore		.gitignore
README.md		README.md
requirements.txt		requirements.txt

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🗑️ SenseBin — Smart Dustbin

Industry-Oriented Embedded Systems & IoT Project

🚀 Project Overview

🎯 Objectives

🏗️ System Architecture

⚙️ Hardware Components

🧠 Embedded System Logic

1. Object Detection

2. Waste-Level Detection

🚦 Status Classification

📡 Telemetry

🌐 IoT Dashboard

Dashboard Features

🖥️ Backend

API Endpoint

Telemetry Input

🧪 Virtual Simulation

Simulation Workflow

🧪 Testing Scenarios

Test 1 — Object Detection

Test 2 — Normal Bin

Test 3 — High Fill Level

Test 4 — Full Bin

📁 Project Structure

📂 Directory Description

backend/

frontend/

wokwi/

screenshots/

circuit_diagram/

reports/

docs/

🛠️ Software Requirements

▶️ Running the Project

1. Install Backend Dependencies

2. Start Flask Server

3. Start Telemetry Input

4. Open Dashboard

📊 Example Telemetry Sequence

0%

25%

50%

75%

90%

🔬 Testing & Validation

Embedded Layer

Backend Layer

Dashboard Layer

🏭 Industry Relevance

🔮 Future Enhancements

🎓 Embedded Systems Concepts Demonstrated

📸 Project Evidence

👨‍💻 Project Type

📌 Conclusion

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