Intelligent Smart Waste Bin: Optimising Waste Collection with IoT Sensors

The Smart Waste Bin is an IoT‑enabled solution that uses multiple sensors to monitor bin status in real‑time, preventing overflows and reducing environmental impact.

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Context

Effective waste management is crucial for protecting our planet. In public spaces and natural reserves, many people overlook the waste they generate, and without timely collection, trash accumulates, harming ecosystems. Even protected areas are at risk when waste is left unattended.

Polluted Waste

To preserve natural environments, well‑managed waste collection points are essential. Bins must be emptied before they overflow, which can be challenging on remote trails or hard‑to‑reach locations.

• Frequent emptying prevents overflow and reduces the risk of litter spreading.
• Automated monitoring eliminates guesswork, ensuring timely collection.

Overflowing of Waste

• Proper sorting is vital: organic waste can be composted naturally, while non‑organics require specialised treatment.
• Smart monitoring supports efficient segregation and resource recovery.

Purpose of the Project

Our goal is to deliver a supervisory device that keeps waste bins in optimal condition by integrating several sensors to continuously track their status.

• Level sensor (ultrasonic) – alerts the collection crew when the bin is nearing capacity.
• Temperature & humidity sensor (DHT11) – monitors the internal environment, crucial for compost health and fire prevention.
• Flame sensor (KY‑026) – detects potential fire risks, protecting surrounding ecosystems.
• Moisture sensor (custom copper probe) – ensures optimal humidity for composting.
• Opening sensor (mini microswitch) – records lid usage and detects improper closure.
• Location system (Sigfox 100m) – identifies bin position, aiding rapid response and enabling temporary deployment on beaches, ski slopes, or events.

The bin features two compartments: one for non‑organic waste and another for organic waste undergoing composting.

Separated Waste-Bin

Sigfox Usage

Installed in isolated areas, the bin runs on battery power, optionally supplemented by a solar panel. Sigfox is chosen for its advantages:

• Wide‑area coverage, ideal for large‑scale deployments.
• Adequate payload capacity for our data needs.
• 100 m localization eliminates the need for GPS modules.
• Low‑power consumption, extending autonomous operation.

II. Project Details

Hardware Design Method

Below is a high‑level overview of the design process and hardware components.

Project Steps

Step 1: Understand Sigfox

Sigfox connects devices to the IoT network, operating in 45+ countries with over 3 million devices. Each message is up to 12 bytes, with a maximum of 140 uplink and 4 downlink messages per day.

Step 2: Hardware Lookup

• Arduino MKR Fox 1200
• Mini Microswitch
• HC‑SR04 – Ultrasonic Sensor
• DHT11 – Temperature & Humidity Sensor
• KY‑026 – Flame Sensor Module
• Custom copper‑made Moisture Sensor (see details)
• Raspberry Pi 3 Model B (for backend server)

Step 3: Hardware Connection and Layout

See the schematic below for pin connections to the Arduino MKR Fox 1200.

Connection to Arduino MKR Fox 1200

• Mini Microswitch – C to GND, NC to Pin 3
• DHT11 – VCC to 5V, GND to GND, DATA to Pin 2
• HC‑SR04 – VCC to 5V, GND to GND, Trigger to Pin 9, Echo to Pin 10
• KY‑026 – VCC to 5V, GND to GND, DATA to A0
• Moisture Sensor – VCC to 5V, GND to GND, SIG to A1

Step 4: Arduino Code

Install Arduino IDE: Download here

Get the Code: GitHub repository

Board & Library Installation:

• Board: Arduino SAMD Boards (32‑bit ARM Cortex‑M0+)
• Libraries: Arduino Low Power, Arduino Sigfox for MKR Fox 1200, DHT sensor library, Adafruit Unified Sensor Driver, RTCZero

Key Functions:

• setup() – initializes Sigfox, DHT11, and ultrasonic sensor.
• loop() – checks lid status; when closed, reads sensor data and sends payload via Sigfox.
• sendPayload() – packages sensor values into a 12‑byte message and transmits it.

Compile and upload the sketch, ensuring the board is set to Arduino MKR Fox 1200.

Step 5: Activate Your Device

Activate the Sigfox module here: https://buy.sigfox.com/activate. Follow the prompts to register your device.

Step 6: Sending the Data

After activation, run the Arduino sketch again. Verify that data appears in the Sigfox backend: https://backend.sigfox.com/device/list.

Step 7: Application Server

A Raspberry Pi 3 Model B serves as the application server, running Node‑RED, MariaDB, and the web interface.

Step 8: Backend Using Node‑RED

Install Node‑RED following the official guide: https://nodered.org/docs/getting-started/installation. Add the node-red-node-mysql package via npm.

Node‑RED receives Sigfox messages, stores them in MariaDB, and forwards data to the web dashboard.

Step 9: Database – MariaDB

Install MariaDB on the Pi:

• Raspbian: link
• Other OS: link

Step 10: Frontend Application (Website)

The website visualises real‑time data from all bins, enabling quick decision‑making for waste collectors.

3D Printing

Custom 3D‑printed enclosures house the electronics and protect the sensors. Assembly steps:

1. Mount DHT11 at point 1 and cover with the “DHT11 maintain” part.
2. Place HC‑SR04 at point 2, covering it with the “interior” part.
3. Mount KY‑026 at point 3 on top of the interior part.
4. Install the moisture sensor at point 4.
5. Place the Arduino MKR Fox 1200 at point 5.
6. Insert the mini microswitch into the “middle top” part, sealing with the “opening detector” part.
7. Attach the “support” part to the “base” and embed the antenna inside.
8. Connect the “support” part to the main box and close with the “middle top,” “front top,” and “back top” panels.

III. Possible Extra Features

• Adjustable bin height displayed on a monitor, allowing deployment on bins of varying sizes.
• Enhanced waste segregation, distinguishing between organic and non‑organic materials.
• Real‑time level display on a nearby screen to inform users when a bin is full.
• Solar‑powered autonomous battery system for off‑grid operation.
• Active environmental control: automated water supply and ventilation shutters to optimise composting.

IV. Conclusion

The Smart Waste Bin delivers a data‑driven approach to waste management, reducing human effort and environmental harm. By providing real‑time insights into bin status, temperature, humidity, moisture, and flame risk, the system enables proactive collection scheduling and efficient resource use.

For live demonstrations, visit: https://grit.esiee-amiens.fr:8069/smartbin/

V. Acknowledgements

King Mongkut’s University of Technology Thonburi (KMUTT) – for hosting our 7‑week training program and supporting students from Electronics & Telecommunication Engineering and Computer Engineering.

ESIEE‑Amiens – for providing laboratory space, equipment, and mentorship, enabling the practical development of this project.

Special thanks to Nicolas DAILLY (supervisor), Thérèse ABY (co‑supervisor), Stéphane POMPORTES, Nicolas HENOCQ (moisture sensor materials), and Moustapha KEBE (web development guidance).

Source: Smart Waste Bin