AI-powered trash can detection system

Posted March 5, 2025

Table of Contents

Forgetting to take out the trash can be frustrating, and I do it a lot. To solve this problem, I built a reminder system using Home assistant and Node-RED to alert me on my phone, computers, TV, and smart speakers. This worked great IF I remembered to turn off the “put out trash today” switch…I didn’t.

Notification sent by Home Assistant companion app.

Notification sent by Home Assistant.

So, I created an locally-hosted AI-powered solution using YOLO object detection, with a model specifically trained to recognize my trash cans. Now, the system automatically stops the reminders once I’ve put the trash out!

Alt text

Tech stack

Machine learning approach

I leveraged YOLO—a real-time object detection algorithm—to train a model specifically designed to detect my trash cans. The process involved:

# Docker Compose file for YOLO trash can detection API container
services:
  yolo:
    container_name: yolo
    image: glandix/yolo
    build:
      context: yolo-trashcan/build
      dockerfile: Dockerfile
      pull: true
    ports:
      - 9192:8080
    env_file:
      - ../.env
    restart: always
    volumes:
      # Maps custom-trained model to expected location within container
      # (allows reuse of the image with other models)
      - ./yolo-objects/yolo11m.pt:/home/app/yolov8m.pt
      # Maps directory where camera images are located for processing
      - /home/storage/internal/ha_media:/media
    deploy:
      resources:
        limits:
          pids: 600
          cpus: "6"
          memory: 8G
    security_opt:
      - no-new-privileges:true

Integration with Home Automation

After training the model and ensuring its accuracy, I integrated it into my home automation setup using Node-RED:

Image of 'Trash cans out back' input boolean in Home Assistant.

Image of ‘Trash cans out back’ input boolean in Home Assistant.

Trash can detection logic

Four cameras in two locations are checked for trash cans:

This lets me know with reasonable certainty whether the trash cans are in the front or back yard. The selected cameras also reduce the likelihood of a neighbor’s trash cans being detected.

Image of Node-RED logic flow for trash can detection

  1. Node-RED listens to the MQTT topic camera/+/event for an image_downloaded event sent by my camera notifications flow

  2. The image size (contained in the MQTT payload) is compared to the known size of a full notification image and only proceeds it matches

    • This prevents cropped images (such as would occur with a person detection event on the camera) from being processed for trash cans, as they often are cropped out

  3. The image is sent to a locally-run YOLO service using a model custom-trained on my particular trash cans

  4. The number of trash cans detected is counted and if > 1, the trash cans are assumed to be in the same location as the camera image being processed

    //
// Code for "Process detections" function node
//

// Only count detections with a confidence level of 75%+
let confidence = 0.75

// If detections were returned, process them
if (msg.payload.data.inference_results[0].detections.length > 0) {
    const detections = msg.payload.data.inference_results[0].detections

    // Filter array of detections by confidence level
    const trashCans = detections.filter((value) => value.name === "trash can" && value.confidence > confidence)

    // Save trash can count to msg
    msg.numTrashCans = trashCans.length
}

// If any trash cans were detected, set state to "on"
msg.state = msg.numTrashCans > 0 ? "on" : "off"
return msg;

  5. If the trash cans were NOT detected, only update the trash cans’ location between 5AM and 11PM

    • This prevents false negatives from causing my reminders to prematurely be disabled when a dark camera image causes the system to think the trash cans are no longer out back

“Put out trash” reminder logic

Image of Node-RED logic flow for turning on/off ‘Put out trash’ boolean

  1. If a “Put out trash” event is in the “Household Tasks” calendar in Home Assistant, a “Put out trash” input boolean is turned on
  2. If trash cans are NOT detected out back and trash is scheduled to be put out today, it’s assumed the trash has been put out, so “Put out trash” is turned off
  3. If trash cans ARE detected out back and trash is scheduled to be put out today, the “Put out trash” boolean is turned on
    • This is a fail-safe in the off-chance that a false negative causes the system to think trash had been put out prematurely
  4. At 9am, 12pm, 5pm, and 7pm if “Put out trash” boolean is on, reminders are sent in the form of notifications and spoken announcements on smart speakers in occupied rooms. If “Put out trash” is off, the reminders are skipped

Image of Node-RED logic flow for sending reminders

Future improvements

Automated image collection

Semi-automated retraining

Nearly fully-automated retraining

Conclusion

This project showcases how AI and automation can be combined to create smart, practical solutions. By leveraging YOLO’s real-time object detection, I developed a system that reduces forgetfulness and enhances household efficiency. It’s a great example of applying machine learning to everyday life in a meaningful way.

Change log