Paper Abstract and Keywords |
Presentation |
2019-08-08 14:20
An energy efficient plant monitoring system on drones with edge AI module. Tomoki Kobayashi, Tomoyuki Yokogawa, Nao igawa (Okayama Prefectual Univ.), Satoshi Fujii (National Institute of Tech., Okinawa College), Kazutami Arimoto (Okayama Prefectual Univ.) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, the collaboration with drone technology has been expanded in various fields. Among them, expert drone system is expected. The current object detection system using drone transfers captured images to the host PC. Therefore, there is a problem that overheads such as resources of wireless communication and power consumption of the host PC become large.
We Suggest an energy efficient plant monitoring system on drones with edge AI module to solve this problem. In this paper, we evaluate the performance of edge AI modules embedded on Raspberry-Pi and FPGA. In addition, we suggest to select transfer data to reduce traffic. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
drone / an energy efficient / embedded AI / SSD / MobileNets / RaspberryPi / FPGA / |
Reference Info. |
ITE Tech. Rep., vol. 43, no. 25, IST2019-42, pp. 53-58, Aug. 2019. |
Paper # |
IST2019-42 |
Date of Issue |
2019-08-01 (IST) |
ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
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