# Real-Time Remote Sensing of the _Lobesia botrana_ Moth Using a Wireless Acoustic Detection Sensor
## 1 Introduction  
In the last years, sustainable and smart agriculture has been an important issue in worldwide research. The Food and Agriculture Organization (FAO) defines on its perspectives for the year 2030 that the use of technologies such as integrated pest and nutrient management, conservation agriculture and organic agriculture could contribute to making agriculture more sustainable [1]. On the other hand, ONU directives for sustainability puts an important objective into the optimization of the resources used in agriculture [2, 3]. In order to achieve those goals, the implementation of smart farming in terms of introducing technology to improve different agricultural processes has been pointed out as a key aspect [4, 5]. When we talk about sustainability and the optimization of resources, pest management is one of the critical issues. On this perspective, the use of technology to detect and control pests will play an important role at the time of pesticide applications, reducing its indiscriminate use and, in that way, reducing the negative environmental and health effects [1, 6]. This has led to many studies that use different technologies in order to identify insects or to achieve an early detection of a possible pest in different fruit and vegetables [7, 8]. Pest control and management using technology is, therefore, an important decision making and action-oriented tool. In particular, the Chilean government has placed smart agriculture under its priority foci of development through a smart industry program [9] for the years between 2017 and 2025. Chile is well known for its wine and grape production. For this reason, pest management and control of this industry could have an important impact for the production. In the last years, a new pest--the _Lobesia botrana_ or grapevine or vineyard moth--has been detected on Chilean soil [10]. _Lobesia botrana_ is a pest of economic importance in vineyards, which can cause damage to flowers and developing grapes [11; 12; 13]. Therefore, the Chilean government, through its Ministry of Agriculture, has put this pest under a special plan of surveillance, control and quarantine, encouraging strategies for its late detection and eradication [14]. Currently, traditional in-field insect traps are used for the early detection and monitoring of the grapevine moth pest on vineyards [14]. The use of these traps has a significant cost in terms of the people involved for installation and counting as well as decision making. For example, the use of this traditional method can imply a late application of insecticides due to the late detection of the reproductive peak of the insect, which can harm the production. In order to make the detection autonomous, several studies have been developed in the last years. Different techniques such as image processing-based detection [15; 16; 17; 18; 19; 20], capacitive sensors [21; 22], radar techniques [23], optoelectronics [24], electrophysiological signals [25] and acoustic- and optoacoustic-based detection methods [26; 27; 28; 29; 30; 31] have been proposed and tested in the field. Nevertheless, most of these technologies use post-processing in order to detect the pest and only a few of them use real-time processing of the information acquired and energy optimization for field conditions [21; 22; 32; 33]. The use of remote sensing using a wireless sensor in the field and real-time processing could save significant time and costs as well as improving decision making in terms of the pesticide used (quantity and period of application). For the case of flying insect pests, the location, time, movement and weather conditions of the field at the moment of sensing are also important statistical information in order to understand the behavior and propagation of the pest.