Over the past two years, with the gradual penetration of technologies such as the Internet of Things, artificial intelligence, cloud computing, and big data in the smart sanitation sector, the digital operation model of urban sanitation has become increasingly mature. A widely recognized example is garbage classification management. Garbage classification management utilizes trash bins to collect waste separately, improving the efficiency of bin usage. Additionally, installing overflow detection devices inside the bins enables real-time monitoring and timely clearance of waste, thereby reducing operational costs. Below, the editors at Gongcai.com will explore the ultrasonic sensor solution for monitoring overflow levels in trash bin overflow detectors. The following is a detailed technical design for the ultrasonic sensor solution for trash bin overflow monitoring, including hardware selection, installation optimization, and data algorithm processing:

I. System Architecture Design

The trash bin overflow detector involves installing intelligent overflow sensors in trash bins, using ultrasonic sensing technology to measure the height of the waste inside. The monitoring interval can be customized based on the scenario. The detection principle primarily involves a microcomputer-controlled piezoelectric transducer emitting ultrasonic waves. By measuring the time taken for the ultrasonic waves to travel and return after hitting an object, the actual distance from the sensor to the target object is calculated, enabling real-time monitoring of the waste height inside the bin. When the bin is filled to a certain level, an overflow signal is output. This signal is transmitted to a remote reception and monitoring platform, which then issues instructions to maintenance terminals for bin processing, achieving overflow alerts. Managers can analyze the uploaded data through the system and, combined with smart city environmental protection applications, plan and dispatch vehicles and personnel for targeted cleaning based on the usage frequency and growth rate of bins and collection points in the operational area.

II. Core Hardware Selection

1. Ultrasonic Sensor Parameters

2. Anti-Interference Design

• Acoustic Waveguide Tube: PVC tube guides ultrasonic waves (avoids sidewall reflection interference)
• Foam Suppression: Sensor surface covered with breathable anti-fouling membrane (prevents waste adhesion)
• Multi-Frequency Switching: 38kHz/58kHz dual-frequency avoids same-frequency interference

III. Installation Optimization Plan

1. Deployment Location

• Top-Mounted: Installed inside the bin lid (1.2m from the bottom, standard 240L bin)
• Side-Mounted: Tilted 30° downward for detection (requires waterproofing for drilled holes)

2. Mechanical Protection

• Anti-Collision Design: Stainless steel protective grid (spacing ≤5cm)
• Anti-Corrosion: 316L stainless steel housing + epoxy resin sealing

IV. Software Algorithm Processing

1. Dynamic Threshold Calibration

2. Data Filtering Strategy

• Median Filtering: Take the median value from 5 consecutive samples
• Moving Average: Window width of 10, eliminating sudden noise

V. Communication and Power Supply Plan

VI. Typical Performance Indicators

• Detection Accuracy: ±3% (affected by waste shape)
• Response Time: ≤2 seconds (from detection to upload completion)
• Lifecycle: 3 years (48 detections per day)