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IPSD Insect Pest Monitoring And Reporting System

IPSD Pest Monitoring System is an advanced IoT-enabled solution designed for 24/7 automated pest detection, data collection, and cloud-based analysis, providing real-time insights for precision agriculture and integrated pest management (IPM).

 

Insect–rain separation design Superior Stability
IoT-enabled system Automatic insect collection & cleaning
Remote control Remote pest identification

IPSD Insect Pest Monitoring And Reporting System

 

The SINOSO IPSD Insect Pest Monitoring and Forecasting System is an unattended smart agriculture solution integrating insect capture, image collection and transmission, and cloud management. It enables 24/7 uninterrupted and accurate collection of insect pest information, which is transmitted to a cloud platform. By connecting to an expert system, it comprehensively and intuitively presents agricultural insect pest status and changes at each monitoring site, achieving stable, accurate, and reliable real-time online monitoring of regional agricultural insect pest situations. It is widely used in agriculture, forestry, horticulture, scientific research institutions, universities, and other fields for insect and pest monitoring and forecasting.

 

 

 

Product Features

 

1. High-Efficiency Pest Capture & Processing:

  • 98% Pest Elimination Rate – High-temperature sterilization ensures ≥98% insect mortality while maintaining ≥98% specimen integrity for accurate AI identification.
  • Rain-Separation Technology – Patented auto-rain rejection prevents water interference, ensuring dry and intact insect samples.
  • Anti-Mixing Mechanism – Vibrating + brush-cleaning collection chamber isolates pests by time intervals, eliminating cross-contamination.

 

2. Smart Remote Monitoring & Control:

  • AI-Powered Pest Recognition – Automatically captures, classifies, and uploads high-resolution insect images via 4G/5G/NB-IoT.
  • Cloud-Based Management – Remotely adjust operating schedules, trap activation, and GPS-track all field units via centralized dashboard.
  • GPS Anti-Theft Protection – Real-time location tracking with geo-fencing alerts for device security.

 

3. IoT-Enabled Data Analytics:

  • Multi-Dimensional Pest Trends – Cloud platform aggregates data by time/location, generating heatmaps & infestation forecasts.
  • Early-Warning System – Automated alerts when pest thresholds exceed predefined levels.

 

 

Technical Parameter

Project Description
Basic parameters Light source 20W black light tube(main wavelength:365nm)
Chamber temp. 15-min op:85%Temp.
Startup time ≤5S
Insulation resistance ≥2.5 MΩ(Leakage Protection)
Control mode Light control,rain control,time control
Camera 5 million pixels
Work env. Temp.range 0~70℃
Humidity range 0~85%relative humidity,no condensation
Power supply Mains power supply:220VAC/Solar power supply+Battery
Other Communication 4G
Chassis material It is made of steel structure and treated with electrostatic powder spraying

 

 

Selection Instructions

 

 

Application Scenarios

IPSD Pest Monitoring System

Widely applicable to:

 

√ Agricultural pest monitoring and forecasting

Forestry insect situation tracking

Horticultural pest management

Scientific research in entomology (universities and research institutions)

 

Why Choose SINOSO

 
Since 2006
SINOSO holds numerous prestigious certifications, establishing itself as a benchmark in the industry. Our strong research capabilities are built on deep collaborations with renowned universities and research institutions. We provide one-stop solutions, ensuring rapid response through our nationwide service network. As a CCTV-reported company, we actively participate in national strategic projects, making us a preferred partner with both technical strength, comprehensive services, and extensive influence.
 

 

 

 

Research Partner

SINOSO is a postgraduate workstation in Jiangsu Province, a research cooperation unit, a research experimental base and a postgraduate training base of China Agricultural University, Nanjing Agricultural University, Hohai University, Jiangsu University, Southwest University of Science and Technology, Jiangsu Academy of Agricultural Sciences, and Nanjing Institute of Agricultural Mechanization of the Ministry of Agriculture and Rural Affairs.

 

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