Orchard pest monitoring is typically conducted with traditional sticky traps that are checked weekly to evaluate changes in pest pressure to inform the timing of pest management activities. Trap counts provide a broad illustration of pest populations over a (typically) one week period, but fail to discern short, temporal bursts of insect activity in the field. Innovative cost-effective devices may facilitate real-time pest monitoring, allowing pest control advisors and growers to detect and respond to increased pest activity within hours rather than days or weeks.
UCCE Tulare County has developed a prototype device that can be used with traditional sticky traps for the remote sensing of insects, as well as the logging of temperature and humidity data. The device can be mounted in front of sticky traps and programmed to take images of the trap at specified intervals. The data can then be transferred remotely to the cloud for remote access.
Our prototype uses IoT (internet of things) technology. The ESP-32 CAM module IoT devices can be integrated with a SIM800L GSM module, powered by a 18650 lithium battery and managed via a TP4056 charging module. The device can transmit data remotely, is budget-friendly, and can be assembled by anyone, regardless of technical expertise. The device is designed to be mounted in front of sticky traps in the field and programmed to automatically capture images of the trap using the onboard OV2640 camera. It additionally logs temperature and humidity data using DHT11 sensors and remotely sends the image and data to the google cloud via a mobile network (GPRS). The device can be adjusted to take and send data over a period of 8 or 12 hours, as needed. Higher frequencies of data transmission will utilize more battery life. This powerful IoT solution may enable growers, researchers, and pest control advisors to monitor insect pests in real time without driving to the field site to check the traps.
Currently the device is semi-autonomous and can be used for remote pest monitoring; however, this device can be integrated with machine learning in the future. AI technology can be integrated into the system to quantify the number of targeted pests captured, thus eliminating the need for pest control advisors and growers to manually count the insects in images. Remote pest monitoring isn’t the future--it’s the present, and it’s becoming more accessible than ever.