Autonomous Agriculture: The Role of IoT, AI, and ML in Drone Operations

1. Introduction

Pesticides and fertilizers may be accurately applied by drones with spray systems, lowering the possibility of over or under-application, which might result in crop damage or decreased production. Yet, deploying drones in agriculture has drawbacks as well. The price of the technology, which may be a sizable investment for small-scale farmers, is one of the biggest obstacles. Drones also need experienced pilots who can control them safely and efficiently, understand data, and utilize it to make knowledgeable crop management choices. Lastly, the use of drones in agriculture may be constrained by legal considerations, such as airspace limitations and privacy problems (Ashton, 2009). The performance of agricultural drones is influenced by many important elements. The amount of space the drone can cover in a single flight is determined by one of the most important elements, flying duration. The drone's range and speed are also crucial since they affect how fast and precisely it can gather data and deliver treatments. The amount of product sprayed per unit area, as well as the spray pattern width for fertilizers and pesticides, may have an impact on how well the drone performs. Agricultural drones provide farmers with a number of advantages, such as better crop management and lower labour and time expenditures. Nevertheless, there are drawbacks to adopting this technology, including costs, operator skill requirements, and regulatory concerns. The performance of agricultural drones may be influenced by a number of important aspects, including as flight length, range, and application rates. Farmers may benefit from this technology to increase crop output and profitability by being aware of these elements and maximizing their usage of drones. Agricultural drone technology has the potential to revolutionize the way farmers manage their crops, providing a new level of precision and efficiency that was previously impossible with traditional farming methods (Sitaram et al., 2018). By utilizing advanced imaging sensors and software, drones can provide real-time information about the status of crops, allowing farmers to make informed decisions about planting, fertilization, irrigation, and pest control. In recent years, the adoption of agricultural drones has increased significantly, driven by advancements in technology, decreasing costs, and the growing demand for sustainable farming practices. Farmers around the world are now using drones to increase yields, reduce labour costs, and minimize the use of harmful chemicals that can harm the environment and human health. This paper will explore the benefits and challenges of using agricultural drones in farming and highlight the key factors that affect their performance. The various sensors and software used in agricultural drones, as well as the regulations and safety considerations that must be considered when using this technology. One of the most significant benefits of using agricultural drones is their ability to capture high-resolution imagery of crops, providing farmers with a detailed view of the health and growth patterns of their plants. This information can be used to create maps of the field, identifying areas that require attention and optimizing crop management practices (Mat et al., 2018). Drones equipped with multispectral or hyperspectral sensors can capture images at different wavelengths, providing data on plant stress, nutrient deficiencies, and other factors that can affect crop yield. Another key advantage of agricultural drones is their ability to reduce labour and time costs associated with traditional crop management practices. Drones can cover large areas of land quickly and accurately, allowing farmers to monitor crop growth and apply treatments efficiently. Drones equipped with spray systems can apply pesticides and fertilizers precisely, reducing the risk of over-application or under-application that can lead to crop damage or yield loss. Despite the many benefits of agricultural drones, their adoption also presents challenges for farmers. One of the most significant challenges is the cost of the technology, which can be a significant investment for small-scale farmers (Saha et al., 2018). Additionally, drones require skilled operators who can fly them safely and effectively, interpret data, and use it to make informed decisions about crop management. Regulatory issues also pose a challenge for the use of agricultural drones in farming. Airspace restrictions and privacy concerns can limit the use of drones in certain areas, and farmers must comply with regulations governing the use of drones in agriculture. Several key factors can affect the performance of agricultural drones, including flight time, range, and application rates. Flight time determines how much area the drone can cover in a single flight, while the range and speed of the drone affect how quickly and accurately it can collect data and apply treatments. The pesticide and fertilizer application rates and spray pattern width can also affect the drone's performance, as they determine how much product is applied per unit area (Santangeli et al., 2020). Farmers must carefully select the appropriate application rates and spray patterns for their crops to ensure optimal results. Agricultural drones offer a range of benefits to farmers, including improved crop management and reduced labour and time costs.