## 1 Introduction  
Globally, strong efforts to develop new and more efficient agricultural solutions, with respect to conventional farming, must be made for several reasons. Firstly, the production of primary crops, that has had an increase equal to 53% between 2000 and 2019, will further increase [1]. Secondly, nowadays, agriculture is already facing pressure from climate change as current and conventional systems contribute actively to the release of pollutants into the atmosphere, such as GHG emissions and 10.7 billion tons of carbon dioxide equivalent in 2019 [2, 3]. In addition, the progressive reduction of arable lands questions the conventional field model since phenomena, such as urbanization and desertification, are expected to comprise between 1.8% and 4.6% of global lands by 2100 [4]. Finally, as the loss in crop yield is expected to range from 10% to 50% by 2030, it is pivotal to search for and optimize new agricultural models [5]. Farming models that differ from field farms in their location, such as urban areas, integrated into buildings, and in conditioned or unconditioned closed environments, have been discussed in the literature [6; 7]. Among them, indoor farms have many advantages, as their efficiency does not depend on seasonality and their usage does not exploit land area. However, a huge amount of energy is required due to high operating costs mainly related to lighting, but also to temperature and humidity control, and highly specialized labor [7; 8; 9]. In this context, huge effort must be devoted to developing automated systems with low energy consumption and possibly integrated with renewable resources such as solar or wind energy, according to the present European policy regarding energy consumption savings [10]. Among these, vertical farms have the most high-tech architecture, as they are fully indoor and often based on hydro or aeroponics systems [7; 9]. In vertical farms, light is provided only by artificial systems, mainly constituted by LED (Light-Emitting Diode) modules, tunable, and with a relative low energy demand under controlled conditions [11]. In fact, LEDs have become the main source of artificial light in indoor farms thanks to higher performance with respect to other artificial lights, e.g., HPS (High-Pressure Sodium) lamps [12]. LEDs have also a narrow wavelength band, useful for tunable light recipes that can be variated according to plants' needs [11]. Nevertheless, the optimization of artificial lighting in vertical farms is essential for their energetic and economic viability, as lighting costs could reach 80% of the electricity demand of a vertical farm [13]. In fact, it has been demonstrated that a clever employment of light, e.g., use of an intermittent light system that is implemented considering variation in electricity prices, could allow a cost reduction of nearly 22% [8]. However, this saving must be obtained without losing the quality or quantity of the final yield. In this sense, the implementation and maintenance of good sensors used for indoor agriculture are also pivotal to enhance energy use and economic return for growers [14]. Furthermore, current knowledge of plant growth is based mainly on natural sunlight [10; 15]. Therefore, there is not enough knowledge on the interaction between plants and artificial light, which would be essential to optimize both the quantity and quality of crop yield in indoor and vertical farms. Current studies separately consider different aspects of indoor conditioned farms, in order to improve the system's efficiency: the modeling of plants' evapotranspiration [16], the optimization of the environmental temperature regulation and measurement [17], and the effect of light intensity and wavelength [18; 19]. In addition, it must be noted that every kind of crop follows its own growth process, so every type of plant requires specific studies which define tailored growth conditions, also considering the different growth stages.