TY - GEN
T1 - Social edge intelligence
T2 - 1st IEEE International Conference on Cognitive Machine Intelligence, CogMI 2019
AU - Wang, Dong
AU - Zhang, Daniel
AU - Zhang, Yang
AU - Rashid, Md Tahmid
AU - Shang, Lanyu
AU - Wei, Na
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - In this vision paper, we propose a new concept, 'Social Edge Intelligence (SEI)', where the artificial intelligence (AI) and human intelligence (HI) are tightly integrated to address a set of critical research challenges in edge computing applications. The SEI concept is motivated by two technical trends: 1) the recent rapid advancement of AI techniques in many edge and mobile applications (e.g., mobile sensing, smart homes, intelligent transportation systems), and 2) the emergence of the crowdsourcing platforms (e.g., Amazon MTurk, Waze) that are used to explore the wisdom of common individuals. We envision that an unprecedented opportunity has been unleashed to integrate AI with human intelligence at the edge of the network to obtain the best of both worlds. In this vision paper, we will review several real-world applications under the SEI vision and discuss the fundamental research challenges in implementing SEI in those applications. We also observe that approaches originated from multiple disciplines (e.g., information theory, machine learning, AI, statistics) are desirable to address the emerging challenges in SEI applications. Finally, we conclude the paper by outlining a few research directions for future work in this exciting direction.
AB - In this vision paper, we propose a new concept, 'Social Edge Intelligence (SEI)', where the artificial intelligence (AI) and human intelligence (HI) are tightly integrated to address a set of critical research challenges in edge computing applications. The SEI concept is motivated by two technical trends: 1) the recent rapid advancement of AI techniques in many edge and mobile applications (e.g., mobile sensing, smart homes, intelligent transportation systems), and 2) the emergence of the crowdsourcing platforms (e.g., Amazon MTurk, Waze) that are used to explore the wisdom of common individuals. We envision that an unprecedented opportunity has been unleashed to integrate AI with human intelligence at the edge of the network to obtain the best of both worlds. In this vision paper, we will review several real-world applications under the SEI vision and discuss the fundamental research challenges in implementing SEI in those applications. We also observe that approaches originated from multiple disciplines (e.g., information theory, machine learning, AI, statistics) are desirable to address the emerging challenges in SEI applications. Finally, we conclude the paper by outlining a few research directions for future work in this exciting direction.
KW - Artificial Intelligence
KW - Edge Computing
KW - Human Intelligence
KW - Social Sensing
UR - http://www.scopus.com/inward/record.url?scp=85081259886&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081259886&partnerID=8YFLogxK
U2 - 10.1109/CogMI48466.2019.00036
DO - 10.1109/CogMI48466.2019.00036
M3 - Conference contribution
AN - SCOPUS:85081259886
T3 - Proceedings - 2019 IEEE 1st International Conference on Cognitive Machine Intelligence, CogMI 2019
SP - 194
EP - 201
BT - Proceedings - 2019 IEEE 1st International Conference on Cognitive Machine Intelligence, CogMI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 December 2019 through 14 December 2019
ER -