INSECT DETECTION SYSTEM FOR REFRIGERATION MONITORING

Abstract

A Design of automated insect detection system for refrigeration environments that uses infrared, optical, and temperature sensors (102) to continuously monitor key conditions (101). It detects movement (104), captures images for analysis (202), and processes them with a deep learning model (203) to identify insects by matching patterns with an insect database (207). If an insect is confirmed (208), the system alerts users (209); otherwise, it returns to monitoring mode (210), enhancing food safety and operational efficiency.

Specification

Description:The insect detection system for refrigeration monitoring is aimed to an automated insect detection system for refrigeration monitoring, which integrates multiple sensors and advanced processing techniques to enhance food safety. The system comprises two primary phases: initial monitoring and image analysis. , C , Claims:1.An automated insect detection system for refrigeration monitoring comprising:
(i)A continuous monitoring mode (101) that utilizes multiple sensors, including infrared, optical, and temperature sensors (102),
(ii)To detect signs of insect presence that identifies abnormal movement (105)
1.A design of insect detection system as claimed in claim 1, wherein the system monitors critical environmental factors such as temperature, humidity, and light levels (103) to establish a baseline for normal conditions within the refrigerator.
2.A design of insect detection system as claimed in claim 1, further comprising an initial scan feature (104) that identifies abnormal movement (105) and captures images for further analysis when insect activity is detected.
3.A design of insect detection system as claimed in claim 3, wherein the captured images are processed using a deep learning model (203) to detect object edges and contours (204), enabling accurate identification of potential insects.
4.A design of insect detection system as claimed in claim 4, wherein the deep learning model further analyzes the size, dimensions (205), and movement characteristics (206) of detected objects before matching them with a comprehensive insect database (207).
5.A design of insect detection system as claimed in claim 5, wherein the system triggers an alert (209) to notify the user if a detected object matches a known insect profile (208), and returns to monitoring mode (210) if no match is found.

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