## 1 Introduction  
As agricultural communication technologies continue to advance, the limitations of traditional systems have become increasingly apparent. Issues such as limited coverage, low field operation accuracy, high power consumption, and latency make these systems inadequate for the demands of large-scale agricultural operations [1]. Modern agriculture is gradually transitioning toward mechanization, automation, and standardization. The development of cloud platforms provides an efficient solution that lowers labor costs and enables centralized management of agricultural machinery [2]. The rapid growth of autonomous agricultural machinery is further transforming modern farming by improving operational efficiency, reducing reliance on human labor, and enhancing the precision of fieldwork [3]. However, to fully unlock the potential of these systems, robust communication technologies are essential. These technologies must support low-bandwidth environmental data transmission (e.g., soil moisture, temperature, and weather monitoring) while also enabling high-bandwidth, low-latency functions such as vehicle control and path planning. Traditional communication systems, such as 4G and Wi-Fi, fall short in large-scale agricultural scenarios due to limited coverage, high power consumption, and latency issues, underscoring the urgent need for more efficient communication solutions and next-generation platform designs [4].  
To address these challenges, this paper proposes an Internet of Things (IoT)-based cloud platform that seamlessly integrates Narrowband Internet of Things (NB-IoT) and 5G technologies to establish a dual-channel communication system for autonomous agricultural machinery. As shown in Figure 1, NB-IoT is utilized for low-power, wide-area communication, enabling the transmission of sensor data such as soil information, temperature, and weather conditions. Meanwhile, 5G supports high-bandwidth, low-latency communication, facilitating real-time task scheduling and path tracking for autonomous vehicles. By combining these two communication technologies, the system optimizes data transmission and enhances device coordination, ensuring greater accuracy and stability in agricultural operations. Additionally, the platform incorporates a multi-machine collaborative scheduling mechanism and a multi-objective optimized path tracking method to address challenges such as agricultural resource allocation optimization and precision operation control. This approach significantly improves overall operational efficiency and system reliability. The ultimate objective of this study is to provide a scalable and reliable communication solution for the future of smart agriculture, ensuring that real-time decision-making and task scheduling play a pivotal role in large-scale agricultural operations.  
The structure of this paper is as follows: Section 2 reviews related research, including autonomous agricultural machinery, agricultural machinery scheduling algorithms, IoT-based agricultural systems, and communication technologies such as NB-IoT and 5G. Section 3 provides a detailed introduction to the proposed IoT-based cloud platform  
Figure 1: Schematic diagram of smart farm.  
architecture, focusing on the integration of NB-IoT for sensor data collection and the application of 5G for real-time control. Section 4 explores three key technologies that support the system: a multi-machine collaborative scheduling mechanism based on an improved Harris hawk optimization (IHHO) algorithm, a multi-objective optimization adaptive path-tracking predictive control method for agricultural machinery, and the design and integration strategy of the agricultural cloud platform. Finally, Section 5 summarizes the research findings and outlines future research directions.