TY - GEN
T1 - The 5th Artificial Intelligence of Things (AIoT) Workshop
AU - Zhang, Jian
AU - Tang, Jian
AU - Chen, Yiran
AU - Liu, Jie
AU - Ye, Jieping
AU - Wolf, Marilyn
AU - Narayanan, Vijaykrishnan
AU - Srivastava, Mani
AU - Jordan, Michael I.
AU - Bahl, Victor
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/8/14
Y1 - 2022/8/14
N2 - With advancement of recent network and chip technologies, IoT devices are becoming smarter with increasing compute power, bandwidth, and storage available on the device. This enables intelligent decision making and information transferring on the devices and unleashes the power of AIoT (Artificial Intelligence of Things) that supports applications such as smart city/agriculture/manufacturing/health care and self-driving scenarios. The AIoT Workshop is a forum for researchers, scientists, engineers, and practitioners to share and learn AI powered IoT solutions. The AIoT is a multi-disciplinary area, which include but not limited to IoT, AI/ML, embedded systems, networking, and stream analytics. The 5th AIoT workshop will be hosted in person in conjunction with the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2022).
AB - With advancement of recent network and chip technologies, IoT devices are becoming smarter with increasing compute power, bandwidth, and storage available on the device. This enables intelligent decision making and information transferring on the devices and unleashes the power of AIoT (Artificial Intelligence of Things) that supports applications such as smart city/agriculture/manufacturing/health care and self-driving scenarios. The AIoT Workshop is a forum for researchers, scientists, engineers, and practitioners to share and learn AI powered IoT solutions. The AIoT is a multi-disciplinary area, which include but not limited to IoT, AI/ML, embedded systems, networking, and stream analytics. The 5th AIoT workshop will be hosted in person in conjunction with the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2022).
UR - https://www.scopus.com/pages/publications/85137140373
UR - https://www.scopus.com/pages/publications/85137140373#tab=citedBy
U2 - 10.1145/3534678.3542911
DO - 10.1145/3534678.3542911
M3 - Conference contribution
AN - SCOPUS:85137140373
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 4912
EP - 4913
BT - KDD 2022 - Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
T2 - 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022
Y2 - 14 August 2022 through 18 August 2022
ER -