Intelligent Environmental Control in Plant Factories: Integrating Sensors, Automation, and AI for Optimal Crop Production

The growing global challenges of environmental degradation and resource scarcity demand innovative agricultural solutions. Intelligent environmental control systems integrating sensors, automation, and artificial intelligence (AI) optimize crop production and sustainability in vertical farming. This review explores the critical role of these technologies in monitoring and adjusting key environmental parameters, including light, temperature, humidity, nutrient delivery, and CO₂ enrichment. Intelligent environmental control systems use real-time data from sensor networks to continuously maintain optimal growing conditions. Sensors measure changes in the environment, such as light intensity and humidity levels. Automation enables tasks to be performed without human intervention, ensuring consistent adjustments to environmental conditions. AI predicts plant responses and enables proactive management strategies in this context. The review also examines how these technologies integrate, highlighting successful case studies and addressing challenges like energy management, scalability, and system harmonization. Looking ahead, AI's potential in predictive maintenance and emerging trends in vertical farming highlight the transformative role of intelligent environmental control in enhancing agricultural efficiency and sustainability.

The global agricultural sector confronts major challenges, including climate change, which disrupts growing seasons and reduces crop yields through unpredictable weather patterns and extreme events; resource scarcity, such as diminishing water supplies and shrinking arable land, limiting food production capacity; and the pressure to feed a rapidly growing population, which necessitates innovative approaches to ensure food security (Abbass et al. 2022; Heimenrath 2022). Traditional farming, which often relies on intensive resource use, is increasingly inadequate for addressing both current and future agricultural challenges (Maja and Ayano 2021). 

The limitations of conventional agriculture are compounded by unpredictable weather patterns, soil degradation, and inefficient water and fertilizer use, which are exacerbated by climate change. Climate change leads to altered precipitation patterns and increased evaporation rates, resulting in water scarcity and making it difficult to maintain optimal soil moisture levels. Additionally, higher temperatures can affect nutrient availability and uptake, further jeopardizing food security and agricultural resilience (Roychowdhury et al. 2020; FAO 2021; Ahmed et al. 2023). In response to these challenges, intelligent environmental control systems in plant factories offer a promising solution by integrating advanced technologies, such as sensors, automation, and artificial intelligence (AI), to precisely monitor and control environmental factors like temperature, humidity, light, and nutrient levels. 

These systems enable continuous optimization of growing conditions, resulting in increased productivity, efficient resource use, and reduced dependency on external environmental conditions, making them particularly effective in addressing the limitations of conventional agriculture (Ragaveena, Shirly Edward, and Surendran 2021; Bersani et al. 2022). These systems integrate sensors, automation, and AI to create controlled environments that enhance plant growth and resource efficiency (Maraveas 2022).

Intelligent environmental control systems are crucial for their precise monitoring and adjustment of critical parameters such as light, temperature, humidity, and nutrient levels. This precision ensures that crops are grown under optimal conditions, leading to increased yield and improved quality (Wani et al. 2024). For instance, optimizing the intensity and duration of light exposure can enhance photosynthetic efficiency, leading to greater biomass accumulation and higher yields (Kula-Maximenko et al. 2021). Moreover, these systems enhance resource use efficiency, reducing input costs associated with water, fertilizers, and energy, thereby making agriculture more sustainable and economically viable (Difallah et al. 2018; Saraswathi et al. 2018; Maraveas 2022). They also mitigate climate challenges, such as unpredictable temperature fluctuations, prolonged droughts, and excessive rainfall, by maintaining stable growing conditions within plant factories. 

These systems achieve this through precise monitoring and automated control of environmental parameters, ensuring consistent food production regardless of external weather conditions. This stability is particularly valuable in regions prone to extreme weather events like droughts, floods, or heat waves, which can severely disrupt traditional agriculture (Chen, Chen, et al. 2023; Moghaddam et al. 2024).


Plant factories depend mainly on the ability to control the internal growth conditions for their efficiency. Current tools help to control and set up the right processes of lighting, temperature, humidity, and the appropriate amounts of nutrients. Sensors are essential in providing real-time information on the growing environment and the status of the vegetation so that changes can be made within the growing environment (Ataei Kachouei, Kaushik, and Ali 2023). For instance, optical sensors in systems such as PLANTSENS are applied to monitor water stress through measuring light penetration and temperature of the leaves, allowing proper time assessment in watering, thereby boosting plant health and the use of the resource (Rojek et al. 2023). Light sensors can further help increase photosynthesis by regulating artificial lighting to meet the plant's needs (Durmus 2020).

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