Automated Remote Insect Surveillance at a Global Scale and the Internet of Things

Abstract

Abstract:The concept of remote insect surveillance at large spatial scales for many serious insect pests of agricultural and medical importance has been introduced in a series of our papers. We augment typical, low-cost plastic traps for many insect pests with the necessary optoelectronic sensors to guard the entrance of the trap to detect, time-stamp, GPS tag, and-in relevant cases-identify the species of the incoming insect from their wingbeat. For every important crop pest, there are monitoring protocols to be followed to decide when to initiate a treatment procedure before a serious infestation occurs. Monitoring protocols are mainly based on specifically designed insect traps. Traditional insect monitoring suffers in that the scope of such monitoring: is curtailed by its cost, requires intensive labor, is time consuming, and an expert is often needed for sufficient accuracy which can sometimes raise safety issues for humans. These disadvantages reduce the extent to which manual insect monitoring is applied and therefore its accuracy, which finally results in significant crop loss due to damage caused by pests. With the term 'surveillance' we intend to push the monitoring idea to unprecedented levels of information extraction regarding the presence, time-stamping detection events, species identification, and population density of targeted insect pests. Insect counts, as well as environmental parameters that correlate with insects' population development, are wirelessly transmitted to the central monitoring agency in real time and are visualized and streamed to statistical methods to assist enforcement of security control to insect pests. In this work, we emphasize how the traps can be self-organized in networks that collectively report data at local, regional, country, continental, and global scales using the emerging technology of the Internet of Things (IoT). This research is necessarily interdisciplinary and falls at the intersection of entomology, optoelectronic engineering, data-science, and crop science and encompasses the design and implementation of low-cost, low-power technology to help reduce the extent of quantitative and qualitative crop losses by many of the most significant agricultural pests. We argue that smart traps communicating through IoT to report in real-time the level of the pest population from the field straight to a human controlled agency can, in the very near future, have a profound impact on the decision-making process in crop protection and will be disruptive of existing manual practices. In the present study, three cases are investigated: monitoring Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) using (a) Picusan and (b) Lindgren trap; and (c) monitoring various stored grain beetle pests using the stored-grain pitfall trap. Our approach is very accurate, reaching 98-99% accuracy on automatic counts compared with real detected numbers of insects in each type of trap.

Affordable Bimodal Optical Sensors to Spread the Use of Automated Insect Monitoring

“…We envision that low-cost plastic traps upgraded with low-budget optical sensors and wireless communication will form a network of uniquely addressable objects transmitting insect counts, wingbeat snippets, and environmental parameters to a cloud server over vast expanses of land. This information will be visualized in GIS (geographical information system) compatible format so that monitoring will be a continuous process that will keep an eye on infestations, perform posttreatment analysis, and establish a link with predictive analytics [29].…”

In-Vivo Acoustic Surveillance of Trees in the Context of IoT

“…The server is described in [18] and manages the data collection and time-stamping, GPS registration and storage process of submitted audio recordings (see Fig. 5).…”

“…Our contribution is a special case in our [18][19][20], among others [21,22]; it is our long lasting goal to establish automated insect surveillance at global scale. This work is about a novel accelerometerbased sensor that transmits short vibration clips stemming from an internal part of the tree to a remote server (e.g.…”

Comparison of Two Traps for Monitoring California Red Scale (Hemiptera: Diaspididae)

“…Recently there has been growing interest in using digital sensors to monitor agricultural pest insects (Potamitis et al 2017;Zhu et al 2017;Ahmad et al 2018). One approach is to use digital sensors to create self-counting insect traps (Doitsidis et al 2017).…”

“…One approach is to use digital sensors to create self-counting insect traps (Doitsidis et al 2017). These traps (now referred to as "internet of things" traps or IOT traps) can then be wirelessly networked, integrated across large areas, and accessed remotely (Potamitis et al 2017). This approach could provide users with pest data in near real-time, thereby expediting pest management decisions and implementation.…”