Transactions of the Chinese Society of Agricultural Engineering,2015,Vol 31,No. 21
【Abstract】 With the process of industrialization, young workers pour into the city, the number of farm labor declines. The average age of farmers is increasing. The tractor, as a modern agricultural production machine, is one of the most important driving force sources of agricultural production. However, some drawbacks come with the manual control, such as, the uncomfortable working condition, the inaccurate routine and the operator fatigue. However, automated driving can improve the field operation standard, the utilization rate of the existing machinery, the mechanical efficiency and labor comfort. Therefore, designing a set of tractor automatic system has a significant meaning in terms of agriculture. At present, the majority of the tractor automated driving systems are designed for specified tractors. When a new type of tractor is used, the developers often need to upgrade their system in terms of software and hardware. And the monotonous work can be reduced by developing a universal system for all types of tractors. Professor Simon Blackmore has been working on a software system for tractors for more than 10 years, and this system can be used as a universal tractor control software system. However, a hardware system is still needed to cooperate with it. In the project, a distributed control system is developed for tractors. Raspberry Pi is used as electronic control unit (ECU) in this system, and transmission control protocol/internet protocol (TCP/IP) is used as the communication protocol in this system; laser distance sensors are used to monitor the environment of the tractor; a Heart Beat system is used to check every important part of this system to make sure the system runs properly. This system receives control commands from a Xbox wireless controller or SAFAR (software architecture for agricultural robot), and it responses to the control commands rapidly and correctly. The John Deere X534 tractor is transformed into automated tractor in the test, R2100 laser scanning distance sensor is selected to safeguard the security of information input system. Since John Deere X534 uses a light tractor CVT automatic transmission, the control strategy is to control the size of the throttle by a servo, and use a motor to control the tractor steering. Experimental results show that the system is stable and reliable. Due to high precision and high frequency, R2100 laser scanning sensor makes the security of the system greatly improved. In the test, when an object is close to the tractor, the tractor can timely stop to protect life and property safety. During the test, in the case of normal operation, disconnecting directly the TCP/IP interface, turning off the router and using other methods to make a fault in the system, the Heart Beat detection mechanism can immediately find the system fault, and Arduino Mega can make the speed set to 0 m/s and the steering angle set to 0 when other tractor control devices fail. The angle of the steering gear is changed in the experiment by changing the width of input signal (square wave signal, the frequency 50 Hz). The test results show that this system can response to the operator or SAFAR rapidly and correctly, and the response time is about 0.5 s, which is highly acceptable for an off-road vehicle system. The communication between 3 ECUs is stable, dependable and fast. The safety system works perfectly when any obstacle is found or any system error occurred. The experiment result shows that this system meets the requirement of this project significantly.
Geomatics and Information Science of Wuhan University,2017,Vol 42,No. 11
【Abstract】 An Unmanned Aerial Vehicle (UAV) is reusable, consisting of power system and unmanned autopilot controller; while an Unmanned Aircraft System (UAS) is a system controlled manually, automatically or independently to perform different kinds of tasks. This article summarizes and analyzes the characteristics of UAV and UAS in different historical stages; secondly, this article emphasizes UAV and UAS requirements for Artificial Intelligence technologies; finally, this article discusses potential influences on UAS. A UAS usually consists of UAV platforms, payloads for tasks, datalink devices, information processing devices, and integrated support equipment. Research on UAS and UAV started from the beginning of the 20 th century, and with the development of electronics, mechanics, material science, and computer science; UAS has rapidly developed over the last century, especially the latest thirty or forty years. With the rapid development of Artificial Intelligence over the first 20 years of the 21 st century ushered in a new stage of UAS and UAV development.
Foreign Affairs Review,2018,Vol 35,No. 01
【Abstract】 The advancements in deep learning algorithms help Artificial intelligence (AI) steer toward a new round of growth. With a massive increase in algorithm and computer processing speeds, AI has achieved technological industrialization and become the key driver of the fourth industrial revolution. The rapid development of AI will profoundly influence international relations. First, AI has been directly involved in the strategic decisions and international military interactions, further widening the gap among international actors and upsetting the balance of power. Second, automated production brought by AI will change the modes of economic and social production around the world and propel structural reforms of power at the distribution level inside international actors, thus triggering significant systemic influences on the international system. Third, the development of AI will change human modes of thinking in the new era and new ideological trends will gradually come into being as a result of continues debates. AI leads human to a new stage facing reforms and inequality, and China will also meet with her new opportunities and challenges.
Review on Chinese artificial intelligence research in the past decade: analysis of bibliometric and knowledge map during 2008–2017
Technology Economics,2018,Vol 37,No. 10
【Abstract】 This paper analyzed the distribution pattern of publication time, author, research topic and discipline of artificial intelligence (AI) academic papers, based on the bibliographical retrieval of 4938 research papers during the period of 2008–2017 in SCI, EI, Chinese Core Collection and CSSCI categories in CNKI database, with “artificial intelligence” as the key word. To clarify research hotspots and future research trends, it conducted the concurrence analysis and the visualization analysis of key words and paroxysmal words. The results showed as follows. The research of artificial intelligence in China increases rapidly, with the rapid spread from core disciplines in artificial intelligence to peripheral disciplines, as well as the discipline of economics and management rapidly joining the upsurge of research. Innovation study has a quite broad and promising prospect in the research of artificial intelligence, however, the overall research level of current studies is not high, which leaves a large number of research gaps to be explored in the future.
Analysis of the innovation governance of emerging technology from the perspective of responsible innovation: lessons from artificial intelligence
Technology Economics,2018,Vol 37,No. 01
【Abstract】 This paper begins with “responsible innovation,” the emerging creative paradigm and focuses on the innovation governance of artificial intelligence technology. It constructs the analytical framework of artificial intelligence technological innovation governance under the responsibility innovation paradigm (including technical dimension, economic dimension, ethical dimension and social dimension) and systematically reviews the duality of artificial intelligence technological innovation in theory and practice, which provides reference for the sustainable development of artificial intelligence technological innovation.
Labor substitution effect of artificial intelligence in the era of population aging: evidence from panel data across countries and panel data at provincial level in China
Chinese Journal of Population Science,2018,No. 06
【Abstract】 Based on panel data across countries and panel data at provincial level in China, this study explores how population aging induces the application of artificial intelligence (AI) and how the application of AI affects economic growth with the two-stage least squares model. It investigates whether the application of AI substitutes labor force, and if yes, how such a substitution effect works. The results show that, the shortage of labor force caused by population aging would push an economy to apply more AI in production. Population aging is conductive to the development of AI. The application of AI has positive effects on local gross production and hence partially offsets the negative impact of population aging on economic growth. AI plays an important role in reacting to population aging. The development of AI is induced innovation driven by population aging, thus it is the complementary substitution for labor force rather than the crowding-out substitution. With these mechanisms, AI is expected to contribute greatly to the economy in the era of population aging.
Brain Cognition and Spatial Cognition: On Integration of Geospatial Big Data and Artificial Intelligence
Geomatics and Information Science of Wuhan University,2018,Vol 43,No. 12
【Abstract】 The 21st century is an age of data explosion growth. In the era of big data, it is urgent to enhance the timeliness and intelligence level of the geospatial information science. Artificial intelligence is applied to geospatial information science, enhancing the perception and cognition ability of geospatial information processing, and realizing the three processes of perception, cognition and action of geospatial information science. Through the integration of geospatial big data and artificial intelligence (AI), the macroscopic, mesoscopic and microscopic scale of the earth space, earth observation brain (EOB), smart city brain (SCB) and smartphone brain (SPB) are proposed. EOB, SCB and SPB are highly intelligent systems in the geospatial information science. The concept model and the key technologies of EOB, SCB and SPB needed to be solved are introduced in detail, and a case is given to illustrate the process of perception, cognition and action in the primary stage of the EOB, SCB and SPB. In the future, EOB, SCB and SPB can observe when, where, what object, what change to push these right information to right person at the right time and right place.
Journal of Beijing Sport University,2018,Vol 41,No. 04
【Abstract】 With the rapid advances of computing technology, artificial intelligence (AI) has been developed from research to application, and starts to revolutionize sports. The concept of artificial sports trainer is explored based on the research of applications of AI in sports; it evaluates functional movement and sports techniques based on related data, and establishes the training mode of multi-objective feedback to help the athletes improve the training level. Four key topics of development of artificial sports training system are elaborated in the paper, including functional movement assessment and training, sports technique evaluation and improvement, real-time feedback in training, and assistant robot trainer.
Chances and challenges for development of surveying and remote sensing in the age of artificial intelligence
Geomatics and Information Science of Wuhan University,2018,Vol 43,No. 12
【Abstract】 Artificial intelligence (AI) will affect various fields and professions. Geoinformatics and remote sensing are closed to the field of artificial intelligence. Our discipline will have a good development chance, also face a big challenge. This paper firstly introduces the domain of AI and the fields related geoinformatics and remote sensing, then presents the progresses of photogrammetry and remote sensing applications based on computing vision and machine learning. Finally, some research progresses involving perceive and reasoning based on space-time big data have revealed the application prospect in sensing, perceive and reasoning for the nature and society based on space-time data from geoinformatics and remote sensing. A desire is to push the quick development of geoinformatics and remote sensing in AI era.