## 1 Introduction  
Precision agriculture (PA), also called precision farming, is defined as a system that uses GPS technology, including satellites and sensors, and big data management applied to agriculture [1]. The aim of PA is to achieve better efficiency, productivity and sustainability of agri-food chain. One of the most important aims for agriculture is to reduce the distribution of plant protection products (PPPs) both to reduce environmental impact, to improve product quality and for better economic management [2; 3; 4]. Therefore, precision agriculture plays a crucial role in doing this through sensors, device connection and data elaboration [5]. There are lot of published works focused on environmental sustainability of PA both for reduction of greenhouse gas emissions [6], for example, using LCA analysis [7], and a better quality of water and food [8; 9]. Grapevine powdery mildew (GPM) and downy mildew (GDM), caused by _Erysiple reactor_ and _Plasmpora viticola_, respectively, represent two of the main constraints of European viticulture. _Vitis vinifera_ evolved separately from GPM and GDM causal agents [10; 11], resulting in being highly susceptible to these pathogens. Consequently, their management requires many treatments with chemical fungicides throughout the season, especially in organic farming, where the use of curative compounds is not allowed. PA involves all agri-food chain phases, and so, it is important to analyze specifically the distribution control of agrochemicals in vineyards or orchards, which requires several treatments. The European Union has been paying attention to sustainability in agri-food chain. The reduction of PPPs used in agriculture represents one of the pillars of the farm-to-fork strategy, and one of the main goals is \"to reduce the overall use and risk of chemical pesticides by 50% and the use of more hazardous pesticides by 50% by 2030\" [12]. For these reasons, the distribution of PPPs should be adjusted according to field needs [13; 14]. According to [PERSON] et al. [15] and [PERSON] et al. [16], pesticides distribution could be reduced in three ways: reduced number of treatments, low doses of application and exclusive distribution on targets. In the first case, crop yield can be compromised; in the second case, genetic resistance can be promoted. Instead, the exclusive distribution on targets represents the best strategy on which the site-specific application is based to carry out a precise management of inputs [7]. The distribution control of agrochemicals can be applied in an espalier system, such as in vineyard or orchards managed with similar systems, through automatic section control of the sprayer or smart sprayer assembled with robots. Every smart sprayer needs specific real-time sensors and a control system to detect the tridimensionality of plants and modulate the distribution of agrochemicals; sensors include an infrared sensor system, ultrasonic sensor system, LiDAR sensor system, machine vision system and sensor fusion system [17]. LiDAR, short for Light Detection and Ranging, is a special sensor that uses pulsed light to measure the distance between the source and the object [18; 19]; the system produces a large data set, known as point clouds, and consists of millions of points [20]. There are two types of LiDAR systems: ALS, stands for airborne lidar or airborne laser scanning, refers to a laser on board an aircraft (including unmanned aerial vehicles), and ground-based lidar, divided into TLS (terrestrial laser scanning) and MLS (mobile laser scanning) systems [19]. LiDARs can be divided into 1D, 2D and 3D sensor scanning, respectively, one axis, two axes (X, Y) and three axes (X, Y, Z). In particular, 2D LiDAR rotates 180 or 360 degrees to collect the horizontal distance to the targets [18]. Recently, LiDAR technology has become widespread thanks to improvements in range detection performance, accuracy, scanning angle and other features [21]. According to [PERSON] et al.