Autonomous Cellular-Networked surveillance system for coconut rhinoceros beetle

Abstract

A biological invasion of the Coconut Rhinoceros Beetle (CRB; Oryctes rhinoceros) to the island of Oahu was discovered in late 2013, posing a threat to palm trees on the island and potential for accidental export to other Hawaiian Islands and sub-tropical palm growing regions of California and Florida. Delineation of populations by physical trapping in remote, undeveloped areas is a critical part of the program for containment and eradication. Continuous surveillance near ports of entry is especially important to eliminate incipient populations rapidly and mitigate the risk of human-assisted transport. Traditional trap monitoring for the CRB is labor-intensive, costly, and temporally inadequate. We have developed an autonomous trap surveillance system framework using electronic sensors and front and backend remote cloud systems for monitoring the CRB trap contents. The customized surveillance system incorporates a camera and digital microphone, and communicates data through a cellular network using Category-M (CAT-M) Low-Power Wide-Area Network (LPWAN) with an integrated GNSS chip for precise geolocation of catches. Hourly monitoring data from early deployments of the system have demonstrated that adult CRB have a crepuscular behavior, with over two-thirds of catches occurring after sunset within three hours of twilight, and fewer than 1% occurring unambiguously during daylight. The system represents a significant advance for trap monitoring, and can prove valuable for identifying biological behaviors that might be exploited for more effective control.