In recent years, intelligent sensor techniques have achieved significant attention in agriculture. It is applied in agriculture to plan the several activities and missions properly by utilising limited resources with minor human interference. Currently, plant cultivation using new agriculture methods is very popular among the growers. However, the aeroponics is one of the methods of modern agriculture, which is commonly practiced around the world. In the system, plant cultivates under complete control conditions in the growth chamber by providing a small mist of the nutrient solution in replacement of the soil. The nutrient mist is ejected through atomization nozzles on a periodical basis. During the plant cultivation, several steps including temperature, humidity, light intensity, water nutrient solution level, pH and EC value, CO₂concentration, atomization time, and atomization interval time require proper attention for flourishing plant growth. Therefore, the object of this review study was to provide significant knowledge about early fault detection and diagnosis in aeroponics using intelligent techniques (wireless sensors). So, the farmer could monitor several paraments without using laboratory instruments, and the farmer could control the entire system remotely. Moreover, the technique also provides a wide range of information which could be essential for plant researchers and provides a greater understanding of how the key parameters of aeroponics correlate with plant growth in the system. It offers full control of the system, not by constant manual attention from the operator but to a large extent by wireless sensors. Furthermore, the adoption of the intelligent techniques in the aeroponic system could reduce the concept of the usefulness of the system due to complicated manually monitoring and controlling process.

The global average potato (Solanum tuberosum L.) production is 17.4 t ha^-1. Even using the same potato varieties, there is a large gap between higher yields and lower yields among countries. Potatoes are a cash crop and a significant part of the global diet. Therefore, low soil fertility, soil-borne diseases, poor water quality, and pests seriously affect potato production in developing countries. To improve potato quality and production, it is necessary for the modern world to improve its potato cultivation techniques. Aeroponics cultivation is an alternative technology of soilless culture for effectively adapting to areas of the world where soil and water are in critical condition. In aeroponic systems, plant roots are suspended in the open air under controlled circumstances to replace the soil with artificially provided foam or plastic stents. Moreover, the nutrient solution is spread through atomization nozzles. This review provides insights into the potential use of aeroponics in complementing potato production in developing countries. Moreover, in most developing countries, this technology should be adopted after deliberate consideration to increase potato production.

Overview of the aeroponic agriculture – An emerging technology for global food security

Advanced computer vision (CV) and deep learning (DL) are essential for sustainable agriculture via automated vegetation management. This paper methodically reviews advancements in these technologies for agricultural settings, analyzing their fundamental principles, designs, system integration, and practical applications. The amalgamation of transformer topologies with convolutional neural networks (CNNs) in models such as YOLO (You Only Look Once) and Mask R-CNN (Region-Based Convolutional Neural Network) markedly enhances target recognition and semantic segmentation. The integration of LiDAR (Light Detection and Ranging) with multispectral imagery significantly improves recognition accuracy in intricate situations. Moreover, the integration of deep learning models with control systems, which include laser modules, robotic arms, and precision spray nozzles, facilitates the development of intelligent robotic mowing systems that significantly diminish chemical herbicide consumption and enhance operational efficiency relative to conventional approaches. Significant obstacles persist, including restricted environmental adaptability, real-time processing limitations, and inadequate model generalization. Future directions entail the integration of varied data sources, the development of streamlined models, and the enhancement of intelligent decision-making systems, establishing a framework for the advancement of sustainable agricultural technology.

The atomized nutrient solution droplet sizes and spraying intervals can impact the chemical properties of the nutrient solution, biomass yield, root-to-shoot ratio and nutrient uptake of aeroponically cultivated plants. In this study, four different nozzles having droplet sizes N1 = 11.24, N2 = 26.35, N3 = 17.38 and N4 = 4.89 µm were selected and misted at three nutrient solution spraying intervals of 30, 45 and 60 min, with a 5 min spraying time. The measured parameters were power of hydrogen (pH) and electrical conductivity (EC) values of the nutrient solution, shoot and root growth, ratio of roots to shoots (fresh and dry), biomass yield and nutrient uptake. The results indicated that the N1 presented significantly lower changes in chemical properties than those of N2, N3 and N4, resulting in stable lateral root growth and increased biomass yield. Also, the root-to-shoot ratio significantly increased with increasing spraying interval using N1 and N4 nozzles. The N1 nozzle also revealed a significant effect on the phosphorous, potassium and magnesium uptake by the plants misted at proposed nutrient solution spraying intervals. However, the ultrasonic nozzle showed a nonsignificant effect on all measured parameters with respect to spraying intervals. In the last, this research experiment validates the applicability of air-assisted nozzle (N1) misting at a 30-min spraying interval and 5 min of spraying time for the cultivation of butter-head lettuce in aeroponic systems.

Sustainable agriculture faces major issues with resource efficiency, nutrient distribution, and plant health. Traditional soil-based and soilless farming systems encounter issues including excessive water use, insufficient nutrient uptake, nitrogen deficiency, and restricted plant development. According to the previous literature, aeroponic systems accelerate plant growth rates, improve root oxygenation, and significantly enhance water use efficiency, particularly when paired with both low- and high-pressure misting systems. However, despite these advantages, they also present certain challenges. A major drawback is the inefficiency of nitrogen fixation, resulting in insufficient nutrient availability and heightened plant stress from uncontrolled misting, which ultimately reduces yield. Many studies have investigated plasma uses in both soil-based and soilless plant cultures; nevertheless, however, its function in aeroponics remains unexplored. Therefore, the present work aims to thoroughly investigate and review the integration of plasma-activated water (PAW) and plasma-activated mist (PAM) in aeroponics systems to solve important problems. A review of the current literature discloses that PAW and PAM expand nitrogen fixation, promote nutrient efficiency, and modulate microbial populations, resulting in elevated crop yields and enhanced plant health, akin to soil-based and other soilless systems. Reactive oxygen and nitrogen species (RONS) produced by plasma treatments improve nutrient bioavailability, root development, and microbial equilibrium, alleviating critical challenges in aeroponics, especially within fine-mist settings. This review further examines artificial intelligence (AI) and the Internet of Things (IoT) in aeroponics. Models driven by AI enable the accurate regulation of fertilizer concentrations, misting cycles, temperature, and humidity, as well as real-time monitoring and predictive analytics. IoT-enabled smart farming systems employ sensors for continuous nutrient monitoring and gas detection (e.g., NO₂, O₃, NH₃), providing automated modifications to enhance aeroponic efficiency. Based on a brief review of the current literature, this study concludes that the future integration of plasma technology with AI and IoT may address the limitations of aeroponics. The integration of plasma technology with intelligent misting and data-driven control systems can enhance aeroponic systems for sustainable and efficient agricultural production. This research supports the existing body of research that advocates for plasma-based innovations and intelligent agricultural solutions in precision farming.