A Delivery System Embedded Trap Device for Attracting Female and Male Fruit Flies is disclosed in the present invention which can attract both female and male of fruit flies for an extended period of 180 days irrespective of the season thereby effectively controlling the major pest in agriculture.

The present disclosure relates to devices for controlling pests, and, more specifically, to devices for monitoring and communicating the presence of pests, and eliminating pests. The pest control system comprises a frame configured to be removably positioned in a pest control station, a panel pivotally coupled to the frame, and pest control device positioned in the frame.

One example method includes receiving information indicating a population of wild insects within a geographic region; determining a number of wild insects per unit area within the geographic region; placing, based on the number of wild insects per unit area, one or more insect release points based on the number of wild insects per unit area, each insect release point indicating a release of a predefined quantity of insects; and generating an insect release route through the geographic region, the insect release route passing through each insect release point.

A light source device for trapping indoor adult Phycitinae, which is an adult moth belonging to subfamily Phycitinae, is configured to: emit an attracting light at a predetermined photon flux density; and form a guide path by the attracting light to guide the adult Phycitinae to a vicinity of an emission end of the attracting light in a region having a photon flux density lower than the predetermined photon flux density on a side lower than a height of the emission end of the attracting light

A pest control and/or detection system generally includes an electrically conductive bait matrix including at least one carrier material that is at least one of palatable, a phagostimulant and/or consumable and/or displaceable by pests, and a plurality of electrically conductive particles. The electrically conductive particles are substantially randomly interspersed throughout the at least one carrier material. The at least one carrier material includes a thermoplastic material and/or a resin.

A pest monitoring system and associated method includes pest monitoring devices for placement at a site and generating a signal upon detection of a pest, and a pesticide dispensing unit including a reservoir housing a diluent and a pesticide module housing a pesticide. A computer device remotely disposed to the pest monitoring devices receives generated signals therefrom, analyzes environmental and historical factor data for the site to determine an amount and placement location of the pest monitoring devices for monitoring the site, and directs deployment of the pest control monitoring devices according to the analysis. The computer device also receives data from the pesticide dispensing unit including an amount or rate of the pesticide substance dispensed from the pesticide module, to form treatment having a concentration of the pesticide substance in the diluent, the treatment being dispensed from the pesticide dispensing unit to treat a detected pest at the site.

An insect monitoring system (ISM) and related e-commerce system are provided. The ISM includes an insect attracting light, an intake, an exhaust, an airflow conduit between intake and exhaust, an insect collecting mesh in the conduit, a fan for generating airflow in the airflow conduit, and one or more cameras pointed on the insect collecting mesh. The insect attracting light and the fan are activated such that insects are drawn into the intake and trapped against the insect collecting mesh. The images of the insect collecting mesh are processed and analyzed using a machine learning algorithm to recognize a type and number of insects. Recommendations are provided based on the analysis. In some aspects, the insect monitoring system is connected to electronic client devices over a communication network. The electronic devices are provided with an e-commerce application for sale of products and services responsive to the recommendations.

A mosquito surveillance device includes one or more mosquito traps having a camera capable of taking images of mosquitos and transmitting the images electronically to a receiver. Suitable traps include an ovitrap, for example. Images may be transmitted from inside or outside the trap to a receiver using low bandwidth cellular phone networks. The images are processed and displayed using software forming mosquito data. The images may be analyzed and the number of live mosquitos identified, the number of dead mosquitos identified, the species of mosquitos identified, or mapped vector densities in real time identified preferably at high resolution.

An intelligent Forcipomyia taiwana monitoring and management system comprises: a catching mechanism grabbing a to-be-identified target; a database storing a datum comprising pictures of a flying insect category; a model training module using the pictures to establish a training model; an image capture module shooting an image including the target; an identifying module selecting a first segmented region including the target by using YOLO detection framework technology, extracting a first identification feature from the target, and inputting the feature into the training model for deep learning to identify a flying insect category to which the target belongs and produce an identification result; a counting module recording a number of the target into the database; and a predictive tracking module obtaining a marked object based on the result marked with the target identified in the image, and using a Monte-Carlo category algorithm to track and predict the object.

Disclosed are real-time insect surveillance sensor devices and methods that use a colorimetric readout for detecting insect disease vectors (such as mosquitoes which can transmit pathogens such as DENV, CHIKV, and ZIKV). The method involves an attractive or feeding solution combined with detector conjugates. The conjugate can specifically detect proteins present in insect saliva and/or proteins specific to mosquito-borne pathogens.