# Energy-Efficient IoT-Based Light Control System in Smart Indoor Agriculture
## 1 Introduction  
Technological adoption in agriculture is slow in comparison to other industrial sectors and varies widely depending on the type of the cultivation method and the region. In fact, many agricultural tasks still rely on manual labor and traditional low-tech methods, resulting in low productivity. In general, the current situation is still far from satisfying the goals of Agriculture 4.0 [1], which aims to transform agriculture into an efficient, data-driven industry that uses the latest technologies to optimize production and promote sustainability [2]. That being said, there are several recent research advancements in the agricultural sector that provide a positive outlook aligning with the vision of Agriculture 4.0. For instance, there is the increasing use of sensing technologies and data analytics to make informed decisions in agriculture. Furthermore, numerous companies are developing groundbreaking products and services that exploit recent technologies; when these improve in terms of accessibility and affordability, their adoption in the agricultural sector will increase [2]. These technologies comprise internet of things (IoT) [3; 4; 5; 6], robotics [7; 8],artificial intelligence (AI) [9; 10], blockchain [11], remote sensing technologies [12; 13; 14], image processing [15; 16], and vertical farming [17; 18]. The objectives are to automate the production process and build decision support systems [19] that use sensors to collect data on environmental conditions, soil condition, and plant growth, in addition to devices that control irrigation, fertilization, lighting, and other tasks. IoT plays a paramount role in smart agriculture as it ensures connectivity and data exchange between the different devices that collect, send, process, and use data in the monitoring and control of various agricultural processes [20; 21]. The benefits of this technology appear in large-scale farms where huge numbers of data on different agricultural products need to be collected and processed in a central server according to the user's requirements. AI can be used in decision support systems [19] to analyze the collected data, find the relation between the variables of interest [22], and make predictions [15; 23]. It can also be used in robots to automate tasks such as planting, irrigation, and harvesting [10; 24], which reduces labor, waste, and time consumption and improves efficiency and precision. Blockchain can be used in agriculture to ensure that the food is produced ethically, improves transparency, and reduces fraud [11]. New sensing technologies and image processing methods improve accuracy in data acquisition and reduce the need for destructive analyses [25; 26]. Vertical farming consists of growing plants vertically on shelves in controlled indoor environments with artificial lighting. It increases land use efficiency, supports circular economy, and reduces environmental impacts [17]. In this way, farmers and stakeholders can make informed and optimized decisions, adapt tasks to specific products, increase productivity and profitability, conserve resources, and plan future productions. This revolution in agriculture is an exciting opportunity to address the most pressing challenges of food security, resource depletion, and climate change that are currently facing the world [2]. Motivated by the above considerations, the case studied in this article is the distributed remote lighting control in large-scale vertical farms or plant factories where artificial lights are used to provide the optimal light intensities needed by plants throughout their life. Light-emitting diodes (LEDs) are proven to be the best artificial light source used in indoor agriculture [27]. In this study, it is supposed that three types of LEDs are used to provide different portions of the light spectrum, the light in the PAR (photosynthetically active radiation) region, the far-red light, and the UV (ultraviolet) light.