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This paper studies the general architecture and key technologies of the Agricultural Internet of Things and summarizes the latest progress of the Internet of Things system model. On this basis, a general system architecture model suitable for the Agricultural Internet of Things is initially established, and the key technologies of the Agricultural Internet of Things are expounded to provide a reference for the in-depth application and development of the Agricultural Internet of Things. Aiming at the problem that the energy consumption of each node in the network is uneven in the process of monitoring agricultural production environment by wireless sensor network, which leads to the failure of some nodes in the network too fast, an event-driven wireless routing algorithm for agricultural production environment monitoring is proposed. By reducing the number of pieces of control information sent in the cluster, the algorithm selects the next hop forwarding node from candidate nodes according to the forwarding cost function to shorten the data transmission distance, reduce energy consumption, and improve the life cycle of the entire network. The experimental results show that the algorithm in this paper effectively avoids the waste of node energy consumption caused by the active transmission mode and at the same time better balances the overall energy consumption of the network and prolongs the life cycle of the network. The platform satisfies the needs of a local garden bureau to integrate comprehensive landscaping business information and display comprehensive landscaping information in a comprehensive, timely, and dynamic manner. At the same time, it has made useful explorations in the development and integration of landscaping business data interfaces and GIS data interfaces. All system functions of the smart garden information management platform project are reasonably designed and completely correct and basically meet the software function requirements specified in the requirements specification. Some functions were found not realized during the test. After rectification, various systems have been improved. All system interfaces of the smart garden information management platform project have reasonable layout, simple operation, and good ease of use. The smart garden information management platform project meets the business logic requirements and fulfills the requirements of the information construction of the Garden and Greening Administration. All systems of the smart garden information management platform project are simple to install and easy to operate and meet the user’s requirements after installation. The system has a strict permission setting function. People with different permissions can only see the content of the fields that they have permission to access, which effectively ensures the security of the data.

To improve the effect of urban agricultural garden landscape planning and design, this paper combines the agricultural Internet of Things technology to construct a smart garden planning and design system. Moreover, this paper selects the LEACH protocol that can support monitoring for a long time according to actual application needs, introduces the latest swarm intelligence optimization algorithm, the gray wolf algorithm, to optimize some of the problems in the LEACH protocol, and conducts simulation experiments on the improved algorithm. The simulation experiment results show that the improved algorithm has obvious advantages in cluster head selection, data transmission within the cluster, and route maintenance. After constructing a smart garden planning system based on the agricultural Internet of Things, the effect of the agricultural Internet of Things data processing in this paper is evaluated. Finally, this paper constructs a garden simulation system and analyzes the performance of the system. The results verify that the agricultural Internet of Things has a good effect in the planning and design of smart gardens.

The problem of module discrimination and identification in the field of landscape design is the focus of researchers. Based on multimodal intelligent computing, this paper constructs a landscape design system based on deep neural network. The article first uses a deep neural network to train multimodal garden landscape images, and then performs pooling and convolution operations on garden landscape images on the multimodal training model of convergence speed on the edge and solve the problem of low model accuracy. In the simulation process, the neural network module of MATLAB software is used to extract the spatiotemporal features of the dynamic garden landscape image from the three directions of the bottom block of the garden to achieve feature complementarity. This method only uses 15% of the features of the original feature set. The complexity of the recognition system also reduces the recognition error rate. The experimental results show that by adopting the design of feature series fusion, maximum value fusion, and multiplicative fusion in the score layer, the feature series fusion achieves a high accuracy rate under the multiplicative fusion of the three modalities, reaching 77.1%, and the test error is within 0.118, which effectively improves the multimodal characteristics of the integrated landscape and makes the modeling results more accurate.

Urban green ecological space is an important manifestation of the environmental characteristics of a green city. The research results show that the urban green ecological space has obvious cooling and humidity effects, which are very important for reducing the urban heat island effect. Remote sensing technology describes the slow-release effects of urban green parks in different seasons from the two perspectives of thermal slow-release intensity and thermal slow-release distance. In this paper, UAV remote sensing is used to extract the internal and external factors of the urban green environment characteristics and to identify the main factors that affect the slow-release heat effect and seasonal changes of the urban green environment. In addition, it analyzes the factors that affect the urban environmental temperature within the environmental temperature slow-release range of urban green space, establishes a model to predict the environmental temperature within the thermal slow-release range outside the park, and realizes the largest thermal slow release in the urban greening ecological space. These are new technologies created in the context of digitization, which include image understanding and synthesis, which involve the use of computer graphics and image processing technology to convert data into graphics or images displayed on the screen to achieve an interactive process.

At present, China is at an essential stage in the progress of social civilisation. At the same time, China's current economic level is developing rapidly and the level of urbanisation is also increasing. However, the uncontrolled development of urban space and excessive consumption of land resources have led to many urban ecological and environmental problems. As a result, there is an urgent need to improve the urban habitat. Plant landscaping is an important part of the urban environment. In addition, plant landscaping is also a crucial part of the visual arts and plays a key role in the shaping of urban spaces. In the context of the urban construction boom, people are increasingly demanding quality in the urban environment. Spatial scale, as a vital factor influencing the visual effect of planting, is gradually becoming a focus of landscape design. Urban greening based on plant landscape can not only improve the urban ecological environment and enhance people’s quality of life but also resolve the contradiction between the demand for urban green space and the continuous reduction of urban greening land. Therefore, plant landscaping is recognised as a key step towards global sustainable development. However, according to current research and application practice, the development of urban greenery is limited and hindered by the value of plant landscaping and its applications. In addition, no comprehensive theoretical system has yet been established at the plant scale. In other words, there are still problems of scale in plant landscaping, such as unreasonable density, disproportion, and unclear hierarchy. Therefore, this paper begins with the definition of plant spatial scale in the city and analyses plant spatial types and scale characteristics from multiple perspectives, so as to establish an overall knowledge of plant landscaping. After that, through a study of the current situation of plant landscaping in cities, a quantitative analysis of the visual scale of plant space in urban squares is carried out to address the issues of plant scale design in this research. The focus of the analysis is on the scale of plants in relation to related elements. Furthermore, this study explores the influence of visual aesthetic scale and psychological scale on planting based on the functional scale of plant elements. Finally, the above quantitative analyses are applied to derive some relative data criteria and to summarise the design strategies for the spatial scale of planting in the city. The findings of this study can provide some guiding suggestions and references for the future construction of urban greenery, thus promoting the orderly development of plant landscaping in cities.