Coconut Rhinoceros Beetle (CRB), Oryctes rhinoceros, was first discovered on Oahu in late 2013. Adults of this invasive beetle feed on a variety of host plants, including palms, bananas, and sugar cane. As the name of the beetle implies, the preferred host is the coconut palm (Cocos nucifera). CRB feeding results in large boreholes near the crown, introducing a route for infection by a variety of pathogens. CRB damage can easily be recognized by characteristic cuts and notches on fronds as they grow out, and in cases of severe damage, the tree can be completely defoliated and die.

To identify the beetle presence and inspect the infestation status, more than three thousand CRB traps are installed throughout the island of Oahu, each visually inspected at regular intervals (approximately once or twice per month, depending on location) by human operators. However, visual inspection is laborious, expensive, and time-consuming. Also, after field visits, manual data logging and processing are done to estimate the pest population density, which is tedious and might delay timely decisions for pest control.

There is a growing research interest in remote pest monitoring technologies, especially remote camera-equipped traps. A distant camera board uses communication network gateways to transmit the captured trap images to the server. Some papers report using onboard Wi-Fi-modules to connect with nearby Wi-Fi access points/Mesh networks; however, solutions relying on Wi-Fi have a short range, are less reliable, and generally transmit (and consume energy) continuously such that they require large batteries and local energy generation (i.e. PV panels) when deployed "off-grid", and the size of these systems can require more cumbersome and expensive mounting hardware. In implementations that do not use a solar panel, there is a need for a battery swap after a few days, adding to labor costs and defeating the purpose of a remote camera. Finally, there is the need to analyze collected imagery which itself can be very taxing on operations staff. Here we propose our energy-efficient automated remote camera board (Rem- Cam) and data management ecosystem to facilitate control operations for CRB (or any invasive pest).

Mohsen Paryavi started his Ph.D. at the University of Hawai'i (UH) in 2019, he is an electronics and biomedical engineer. His current research interest is using computer vision and internet of things tools to develop smart and energy-efficient camera boards for distributed surveillance, and designing a decision support ecosystem for the control of Coconut rhinoceros Beetle.