Development of Safety Monitoring for an IOT-Enabled Smart Environment

Harshitha, A.; Srinivas, Manikanta Uma; Sai, M. Eswar; Kommuri, Krishnaveni; Krishna, Pravin

doi:10.1007/978-981-19-3045-4_11

Cited by 4 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where k x , k y and k z are the degree of nodes x, y and z respectively. Meanwhile, SCL(C i , C j ) can well depict the strength of connectivity between the communities C i and C j , which can be computed using Equations (7) or (8).…”

Section: Methods Equationsmentioning

confidence: 99%

“…AI is an important driving force in the new round of technological revolution and industrial transformation [2]. Here, AI refers to technology that simulates and possesses human-like cognitive functions on various machine carriers, and the related computing technologies include natural language processing, cloud computing, big data, and deep learning, such as intelligent robots, virtual personal assistants, autonomous driving, and voice recognition [3][4][5][6][7]. In the late 1990s, with the improvement of computer technology, AI technology also achieved rapid development.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on the Collaborative Innovation Relationship of Artificial Intelligence Technology in Yangtze River Delta of China: A Complex Network Perspective

Dong

Meng

2022

Sustainability

View full text Add to dashboard Cite

Artificial intelligence (AI), as a rapidly developing interdisciplinary field, is a key driver of future economic development. The Yangtze River Delta (YRD) is one of the most significant economic regions of China, which also has a leading role in the AI industry. In this study, based on the patent cooperation data of YRD in the past decade, we focus on studying the collaborative innovation relationship in the AI field of the YRD from the perspective of complex networks. In order to investigate the interprovincial, intra-city and inter-city collaborative innovation relationships, we construct the Yangtze River Delta AI collaborative innovation (YRD-AICI) network. Subsequently, to analyze the development status and collaborative innovation relationship of innovation bodies in the AI field of YRD, we construct the Yangtze River Delta AI patent cooperation (YRD-AIPC) network. Next, the basic characteristics and spatio-temporal evolution of these two networks are explored, and the research results are presented that: (1) Shanghai, Jiangsu Province, and Zhejiang Province have obvious leading advantages in the AI field of the YRD, and the development gap between cities is significant; (2) the pioneering innovation bodies in the AI industry of the YRD are identified using centrality measures, and their cooperative innovation relationship is revealed; (3) based on link prediction methods, future partnerships between cities and innovation bodies are predicted to provide the future development trend of the YRD. The results provide theoretical support for exploring the cooperation mechanism of collaborative innovation in the AI field of YRD and inspire future development planning.

show abstract

Section: Methods Equationsmentioning

confidence: 99%