AI, Sensors, and Robotics for Smart Agriculture

1. Introduction

Agriculture plays a crucial role in development, especially in low-income countries where the sector is large in terms of both aggregate income and total labor force [1]. However, marred by poor supply chains, low productivity, degraded land, decreased soil fertility, firm reliance on inorganic fertilizers, dwindling water tables, and emerging pest resistance, traditional agriculture is leading to unsustainable agricultural practices [2] Furthermore, with continuous progress in modern society, the traditional agricultural production model has not been able to meet the needs of modern civilization [3]. Problems such as reduction, hollowing out, and aging in rural areas emerge in an endless stream. Therefore, smart agriculture is gradually applied to production processes all over the world. Smart agriculture aims to improve the efficiency of agricultural production, change traditional agricultural production and management methods, implement green production methods, and improve the ecological environment [4], thus promoting long-term agricultural viability. Artificial Intelligence (AI), sensors, and robotics accompanied with IoT, data management technology, intelligent decision-making algorithms, and advanced mechanisms are indispensable parts of smart agriculture, enabling young engineers and scientists to make the agriculture process effortless, intelligent, cost-effective, highly productive, time-efficient, sustainable, and healthy, resulting in a wealthy society [5].

2. Artificial Intelligence (AI)

The application of AI has widely been considered as one of the most viable solutions to adapt to the development of smart agriculture [6]. Artificial Intelligence involves enabling machines to think and process problems like humans. It refers to the ability of computer programs to obtain some human-like intelligence, including perception, learning, and reasoning skills, using data to support intelligent decision making. AI techniques are widely used to solve a variety of problems in agriculture, including precision farming, autonomous machinery, crop monitoring, predictive analytics, and so on. AI can be introduced to agriculture through other technological advances, including big data analytics, robotics, the Internet of Things, the availability of cheap sensors and cameras, drone technology, and even wide-scale internet coverage on geographically dispersed fields [7]. By utilizing AI-driven solutions, farmers can optimize resource allocation, monitor crop health, and mitigate the risks associated with unpredictable environmental conditions. With the aid of AI, smart agriculture plays a pivotal role in agriculture sustainability [8]. Apparently, AI has become a research hotspot to optimize production and operation processes in the field of agriculture.

3. Sensors

In recent years, intelligent sensor techniques have received significant attention in the agricultural sector [9]. Agricultural sensors, including soil moisture sensors, temperature and humidity sensors, light sensors, nutrient sensors, weather sensors, and crop health sensors, can be applied to different stages of crop production from pre-planting to post-harvest [10]. Additionally, agricultural robots are equipped with various sensors and advanced technologies that enable them to autonomously perform a wide range of tasks. Agricultural sensors have entered the agricultural field in an all-round way, providing sufficient power for the development of agricultural robots. Thanks to sensors [11], it is possible to eliminate the limitations of natural factors such as the weather; realize the remote scientific monitoring of fields, greenhouses, aquatic products, and animal husbandry; and effectively reduce labor consumption [12]. Combining agricultural sensors with a scientific analysis makes it easier for the entire agricultural sector to resist disasters and risks and improve productivity [13]. Therefore, sensor technology has been sought after by most agricultural workers. Using sensor technology, it is possible to achieve precise control and scientific management of the production and operation process, realize the intelligent control of agricultural cultivation, and promote the transformation of agricultural development to an intensive and large scale, elevating the future of agriculture to a new level. Agricultural sensors have moved traditional agricultural production towards intelligent, automated, and remote-controlled smart agricultural development.

4. Robotics

Agricultural robotics has been a popular subject in recent years from both academic and commercial points of view [14] because it can accelerate plant breeding and advance data-driven precision farming with significantly reduced labor inputs by providing task-appropriate sensing and actuation at fine spatiotemporal resolutions [15]. Agricultural robots still belong to the scope of robots. They not only involve a simple combination of machinery and electronics, but also an interdisciplinary and comprehensive integration of automatic control technology, fine mechanical technology, and computer technology [16]. Traditionally, various agricultural activities can be grouped into subsections: land preparation before planting, sowing/planting, plant treatment, harvesting and yield estimation, and phenotyping. Therefore, there are various types of robotic system applications in individual agricultural environments [17]. The characteristics of agricultural production require robots in agricultural areas to possess considerable intelligence and flexible production capabilities to adapt to complex non-structural environments [18], such as discrimination and obstacle avoidance. Confronted with these obstacles, experts have shifted their research focus from the mechanical part to machine vision and artificial intelligence, striving to solve the intelligent problem of agricultural robots. The development of agricultural robots needs to be actively promoted to overcome limitations, increase the improvement of existing agricultural robots [19], design agricultural robots that adapt to the specific national conditions of various countries, and create production conditions for the improvement of agricultural production levels, thereby improving the world.

5. Conclusions

AI sensors and robotics are driving the transformation of agriculture towards smart and sustainable practices. AI enables sensors to work as smart sensors, and the advent of robotics has resulted in the development of very useful tools in the field of agriculture by making different types of sensor-based equipment and devices available [20]. The combination of AI, sensors, and robotics enables farmers to take a data-driven approach to collect and analyze data to monitor the real-time statuses of plans and crops to improve production yield quality [21]. In smart agriculture, the field environment will pose challenges in sometimes rapidly varying light, wind, and temperature conditions, as well as combinations of multiple stresses. Therefore, specific work on robustness, the selection of sensors, environmental parameters, and the design of suitable smart sensors needs to be carried out in the future.