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On-the-Fly Olive Tree Counting Using a UAS and Cloud Services

Computer Architecture Department, UPC BarcelonaTECH, Esteve Terrades 7, 08860 Castelldefels, Spain
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Remote Sens. 2019, 11(3), 316; https://doi.org/10.3390/rs11030316
Received: 18 January 2019 / Revised: 2 February 2019 / Accepted: 3 February 2019 / Published: 5 February 2019
Unmanned aerial systems (UAS) are becoming a common tool for aerial sensing applications. Nevertheless, sensed data need further processing before becoming useful information. This processing requires large computing power and time before delivery. In this paper, we present a parallel architecture that includes an unmanned aerial vehicle (UAV), a small embedded computer on board, a communication link to the Internet, and a cloud service with the aim to provide useful real-time information directly to the end-users. The potential of parallelism as a solution in remote sensing has not been addressed for a distributed architecture that includes the UAV processors. The architecture is demonstrated for a specific problem: the counting of olive trees in a crop field where the trees are regularly spaced from each other. During the flight, the embedded computer is able to process individual images on board the UAV and provide the total count. The tree counting algorithm obtains an F 1 score of 99.09 % for a sequence of ten images with 332 olive trees. The detected trees are geolocated and can be visualized on the Internet seconds after the take-off of the flight, with no further processing required. This is a use case to demonstrate near real-time results obtained from UAS usage. Other more complex UAS applications, such as tree inventories, search and rescue, fire detection, or stock breeding, can potentially benefit from this architecture and obtain faster outcomes, accessible while the UAV is still on flight. View Full-Text
Keywords: UAS; UAV; image segmentation; tree counting; distributed services; cloud computing UAS; UAV; image segmentation; tree counting; distributed services; cloud computing
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MDPI and ACS Style

Salamí, E.; Gallardo, A.; Skorobogatov, G.; Barrado, C. On-the-Fly Olive Tree Counting Using a UAS and Cloud Services. Remote Sens. 2019, 11, 316. https://doi.org/10.3390/rs11030316

AMA Style

Salamí E, Gallardo A, Skorobogatov G, Barrado C. On-the-Fly Olive Tree Counting Using a UAS and Cloud Services. Remote Sensing. 2019; 11(3):316. https://doi.org/10.3390/rs11030316

Chicago/Turabian Style

Salamí, Esther, Antonia Gallardo, Georgy Skorobogatov, and Cristina Barrado. 2019. "On-the-Fly Olive Tree Counting Using a UAS and Cloud Services" Remote Sensing 11, no. 3: 316. https://doi.org/10.3390/rs11030316

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