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  • Abstract: LeafSpec, a mobile distributed sensor for agricultural crop health measurement, Y1
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LeafSpec is the world's first handheld hyperspectral crop leaf imager developed at Purdue's ABE sensor lab. It takes the award winning device 5 seconds to scan a leaf to get unprecedented quality of hyperspectral image, and provide real-time geo-referenced crop measurement results. The sensor device works together with a cyber infrastructure currently under development called SACI for sensor data collection, processing, management, and dissemination.
SACI will be a scalable and flexible sensor data collection and analysis platform. The main goal of this system is to aid sensor data researchers to easily collect, process, store, and access large volumes of heterogeneous sensor data collected in the field. It will support real time data ingestion and processing pipelines using an open source software stack including RabbitMQ, Docker, Node.js, MongoDB, and HUBzero. The SACI system will be developed and deployed on JetStream and MyGeoHub ( and help plant phenotype researchers to collect and process plant health sensor data.
We would like to get help in the development and deployment of the SACI sensor data ingestion pipeline, REST APIs, and data access control using JetStream VMs and containers. We already developed a prototype sensor data database and ingestion endpoints. We would like to make it more scalable using a RabbitMQ and container based data processing pipeline on JetStream as well as integrating it with MyGeoHub for OAuth based data access control.

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