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Mapping Agricultural Soil in Greenhouse Using an Autonomous Low-Cost Robot and Precise Monitoring

doi: 10.3390/su142315539
Our work is focused on developing an autonomous robot to monitor greenhouses and large fields. This system is designed to operate autonomously to extract useful information from the plants based on precise GPS localization. The proposed robot is based on an RGB camera for plant detection and a multispectral camera for extracting the different special bands for processing, and an embedded architecture integrating a Nvidia Jetson Nano, which allows us to perform the required processing. Our system uses a multi-sensor fusion to manage two parts of the algorithm. Therefore, the proposed algorithm was partitioned on the CPU-GPU embedded architecture. This allows us to process each image in 1.94 s in a sequential implementation on the embedded architecture. The approach followed in our implementation is based on a Hardware/Software Co-Design study to propose an optimal implementation. The experiments were conducted on a tomato farm, and the system showed that we can process different images in real time. The parallel implementation allows to process each image in 36 ms allowing us to satisfy the real-time constraints based on 5 images/s. On a laptop, we have a total processing time of 604 ms for the sequential implementation and 9 ms for the parallel processing. In this context, we obtained an acceleration factor of 66 for the laptop and 54 for the embedded architecture. The energy consumption evaluation showed that the prototyped system consumes a power between 4 W and 8 W. For this raison, in our case, we opted a low-cost embedded architecture based on Nvidia Jetson Nano.
- CY Cergy Paris University France
- University of Paris-Saclay France
- University of Sharjah United Arab Emirates
- Université Paris-Saclay (Maison du Doctorat) France
- Université de Rennes 1 France
GPS localization, real-time, [SDV.SA.STA] Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculture, TJ807-830, TD194-195, autonomous robot, Renewable energy sources, greenhouses, multi-sensor fusion, GE1-350, Environmental effects of industries and plants, embedded architecture, [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO], multispectral camera, Environmental sciences, autonomous robot; greenhouses; GPS localization; energy; multispectral camera; embedded architecture; multi-sensor fusion; real-time, [SDE.IE] Environmental Sciences/Environmental Engineering, energy
GPS localization, real-time, [SDV.SA.STA] Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculture, TJ807-830, TD194-195, autonomous robot, Renewable energy sources, greenhouses, multi-sensor fusion, GE1-350, Environmental effects of industries and plants, embedded architecture, [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO], multispectral camera, Environmental sciences, autonomous robot; greenhouses; GPS localization; energy; multispectral camera; embedded architecture; multi-sensor fusion; real-time, [SDE.IE] Environmental Sciences/Environmental Engineering, energy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).8 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
