Basic Information of the Micro-Major

Major Category: Environmental Science and Engineering (0825)

Major Code: 082503

Chinese Major Name:智慧环境

English Major Name: Smart Environments

Duration of Study: 3 semesters

I. Professional Advantages and Features

Relying on cutting-edge technologies in unmanned aerial vehicle (UAV) technology, environmental internet of things (IoT), and intelligent management, this micro-major closely aligns with the national needs for ecological civilization construction and smart city development. It aims to cultivate interdisciplinary and practical compound talents. The curriculum system covers core skills such as UAV operation and application, sensor deployment, big data analysis, and intelligent decision-making, emphasizing the integration of theory and practice. Leveraging the platform of national first-class undergraduate majors and leading enterprises in the industry, the major provides abundant practical opportunities and employment support. Graduates possess significant competitiveness in fields such as smart environmental monitoring and smart environmental management.

II. Training Objectives

This major is committed to cultivating high-quality applied talents with all-round development of morality, intelligence, physical fitness, aesthetics, and labor education. These talents should be equipped with UAV operation and environmental monitoring technologies, IoT application capabilities, and professional literacy in smart environmental management. Approximately 2 years after graduation, students are expected to achieve the following goals in fields like smart environmental monitoring, smart city planning, and smart ecological governance:

Technical Competence: Proficiency in applying UAV, IoT, and big data technologies to solve complex environmental monitoring and management problems.

Interdisciplinary Thinking: Possessing interdisciplinary collaboration capabilities to participate in multi-field environmental planning and intelligent decision-making.

Application Capability: Being able to independently undertake environmental monitoring projects and propose innovative solutions.

Professional Ethics: Demonstrating sound professional ethics and playing an active role in environmental management and ecological protection.

III. Curriculum System Composition and Credit Requirements for Each Module

The program consists of 5 courses, including Introduction to Smart Environments, UAV Aerial Photography Technology, UAV Spatial Data Acquisition and Analysis, Environmental IoT and Sensor Technology, and Smart Environmental Planning and Management, with a total of 12 credits.

IV. Core Courses and Descriptions

(1) Environmental IoT and Sensor Technology

This is an applied course that deeply integrates interdisciplinary theoretical systems and practices. With integrated environmental automatic monitoring theory, remote sensing model technology principles, and Internet of Things (IoT) devices as the core knowledge foundation, the course constructs a multi-scale environmental monitoring technology paradigm: at the micro level, it focuses on the in-situ intelligent perception system of multi-medium environmental (atmosphere, water, soil, etc.) parameters and sensor network deployment; at the macro level, it strives to develop large-scale remote sensing inversion models and numerical prediction systems to realize the dynamic deduction of environmental evolution trends. Ultimately, a heterogeneous data fusion platform is established through the IoT, forming an air-space-ground integrated environmental decision support platform with functions of real-time aggregation of multi-source heterogeneous data and spatio-temporal collaborative analysis. Meanwhile, the course innovatively introduces the industry-university-research collaborative innovation mechanism, building a connection channel between engineering practice platforms and industrial application scenarios, enabling students to apply the independently developed environmental decision support platform to corresponding industries through customized industry training projects. This course not only strengthens students' technology transformation capabilities and systems engineering thinking but also expands the dimensions of students' career development through innovative achievement transformation paths, providing strong support for the cultivation of compound technical talents and the construction of an industrial innovation ecosystem.

(2) UAV Aerial Photography Technology

As a basic compulsory course for the Smart Environments micro-major, its main content includes: the working principle of UAV systems, basic operations and flight skills, flight planning and mission execution, as well as UAV applications in high-precision mapping. Studying this course enables students to gain a comprehensive understanding of the basic knowledge of UAV aerial photography, field control, and image information acquisition. It helps consolidate students' basic knowledge in UAV photogrammetry, cultivate their grasp of the basic concepts and principles of UAV photogrammetry, master the methods of planning and executing UAV aerial photography missions, and improve their practical ability to acquire spatial data using photogrammetry knowledge.

(3) UAV Spatial Data Acquisition and Processing

This is a basic compulsory course for the Smart Environments micro-major. Its main content includes: the acquisition and processing of UAV data, the applications and cases of UAVs in environmental fields (atmospheric monitoring, water quality monitoring, soil remediation, ecological environment, etc.), and project report generation. Studying this course allows students to fully understand the applications of UAVs in environmental fields, helps them grasp the development trends and application prospects of smart environments under the background of artificial intelligence and informatization, effectively addresses the skill barriers students face in job hunting, and bridges the "last mile" of students' employment.

(4) Introduction to Smart Environments

As a basic course for environment-related majors, it aims to enable students to understand the concept, development history, current status, and future trends of smart environments. The course content covers the basic principles, key technologies, application scenarios, and challenges of smart environments. Through studying this course, students will gain a comprehensive understanding of smart environments, laying a solid foundation for subsequent professional learning and practice.

(5) Smart Environmental Planning and Management

This is an applied course that interdisciplinary integrates the theories and practices of environmental science, artificial intelligence, big data, GIS, and urban planning. Taking environmental issues as the entry point, the course addresses challenges such as pollution diffusion and resource regulation, constructing an environmental decision support system based on multi-source data integration, machine learning prediction, spatial analysis, and intelligent regulation. The specific content includes: multi-source data acquisition and environmental database construction, integrating meteorological, traffic, industrial emission and other data; the application of machine learning models in pollution trend prediction, smog early warning, and water quality deterioration simulation; data analysis and statistical methods for pollution source localization to provide decision support for precise governance; GIS-based green infrastructure planning and sponge city design, including schemes such as ventilation corridors and ecological wetlands; the construction of intelligent regulation systems to realize optimal resource regulation such as smart water management, garbage classification, and carbon footprint analysis, while involving real-time early warning and disposal of sudden environmental events and evaluation of environmental policy effects. Relying on prerequisite courses such as Introduction to Smart Environments, UAV Theory, UAV Applications, and Environmental IoT and Sensor Technology, this course provides students with basic knowledge such as automatic environmental monitoring, data acquisition, and sensor technology. Students need to possess certain environmental science knowledge, programming skills, and data analysis capabilities to deeply understand and practice the course content. Through theoretical learning, experimental operations, and internship practice, the course aims to cultivate students' interdisciplinary integration capabilities and engineering practice capabilities, delivering compound technical talents to fields such as smart cities, green infrastructure construction, and environmental data governance.