TY - GEN
T1 - An exchange-based AIoT platform for fast AI application development
AU - Liang, Yu-Cheng
AU - Wu, Kun-Ru
AU - Tong, Kit-Lun
AU - Ren, Yi
AU - Tseng, Yu-Chee
N1 - Funding Information: Y.-C. Tseng’s research is co-sponsored by ITRI and NSTC, Taiwan. This work is also financially supported by “Center for Open Intelligent Connectivity” of “Higher Education Sprout Project” of NYCU and MOE, Taiwan. The research of Yi Ren was supported in part by EPSRC EP/T022566/1, EP/T024593/1, and the Royal Society IEC\R3\213100.
PY - 2023/10/30
Y1 - 2023/10/30
N2 - AIoT is the combination of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. While IoT emphasizes more on scalable and efficient communications, AI focuses more on reproducing human capabilities such as recognition and forecasting. An efficient AIoT platform may not be obtained directly from integrating existing IoT and AI serving platforms by considering the AIoT service reproduction and evolution. In this work, we propose an AIoT platform that empowers developers to build sophisticated and scalable applications. Our platform is derived based on exchange-based RabbitMQ broker and Advanced Message Queuing Protocol (AMQP) to facilitate the communications among heterogeneous data sources and AI models. By incorporating an AMQP broker, it supports diverse data exchanges, AI models chaining, and flexible message routing and processing. AI models can be deployed efficiently through containerization with flexible and shared data paths to facilitate computations. Hence, developers can focus on service and application requirements. We also present a case study in smart healthcare to validate our design.
AB - AIoT is the combination of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. While IoT emphasizes more on scalable and efficient communications, AI focuses more on reproducing human capabilities such as recognition and forecasting. An efficient AIoT platform may not be obtained directly from integrating existing IoT and AI serving platforms by considering the AIoT service reproduction and evolution. In this work, we propose an AIoT platform that empowers developers to build sophisticated and scalable applications. Our platform is derived based on exchange-based RabbitMQ broker and Advanced Message Queuing Protocol (AMQP) to facilitate the communications among heterogeneous data sources and AI models. By incorporating an AMQP broker, it supports diverse data exchanges, AI models chaining, and flexible message routing and processing. AI models can be deployed efficiently through containerization with flexible and shared data paths to facilitate computations. Hence, developers can focus on service and application requirements. We also present a case study in smart healthcare to validate our design.
KW - advanced message queuing protocol (amqp)
KW - ai models chaining
KW - aiot
KW - application platform
KW - service configuration
KW - service-oriented architecture
UR - http://www.scopus.com/inward/record.url?scp=85178358786&partnerID=8YFLogxK
U2 - 10.1145/3616391.3622770
DO - 10.1145/3616391.3622770
M3 - Conference contribution
T3 - Q2SWinet 2023 - Proceedings of the 19th ACM International Symposium on QoS and Security for Wireless and Mobile Networks
SP - 105
EP - 114
BT - Proceedings of the 19th ACM International Symposium on QoS and Security for Wireless and Mobile Networks
PB - Association for Computing Machinery (ACM)
ER -
