Use Case

Multi-Sourced Data Analytics to Improve Food Production & Security

K. McCurdy (Sedgwick Reserve, University of California, Santa Barbara Natural Reserve System) with B. Roberts, B. Sethuramasamyraja (California State University, Fresno), B. Liu (California State Polytechnic University, San Luis Obispo), C. Krintz, R. Wolski (UC Santa Barbara)

What?

  • Interdisciplinary analysis of data from a wide variety of sources, including the general public, to study and improve ecological outcomes

Why Aristotle?

  • Scalable and portable infrastructure
  • Access to multiple data sources, many of which are already in public and private clouds

Accomplishments

  • Completed large-scale Google TensorFlow training and parallel image classification runs on Aristotle for the "Where's the Bear?" camera trap application analysis project (20 training runs using 2000 cores hours per run and a classification run using 1800 core hours to classify a test sample of 10,000 images prior to classifying 240,000 images from a single camera).
  • Used soil moisture sensing devices, edge computing, and Aristotle to schedule vineyard irrigation (saved 66% of the water used previously).
  • Installed hardware and software to instrument almond trees in a Fresno, CA test orchard to see how much water can be saved by irrigating the different sides of the root stock in proportion to its dryness.
  • Developed innovative analytics with a minimally invasive instrumentation footprint for an Exeter, CA citrus test orchard to get highly accurate temperature readings at night when frost could form.
  • Progress was made developing a low-power, low-cost, multi-tier IoT deployment for citrus frost prevention and the differential irrigation of almond trees.
  • The Sedgwick Reserve "Where’s the Bear" project is using the Pacific Research Platform’s Kubernetes and containers environment to train image recognition models in conjunction with Aristotle.
  • A new use case called Citrus Under Protective Screening (CUPS) was initiated. CUPS is a potential remedy for citrus greening which has devastated citrus in FL and is now threatening CA. Aristotle will serve the data hosting service for CUPS.
  • 8 new publications (including a Best Student Paper award) and 2 keynote presentations were produced in PY4.
  • Installed cameras and weather sensors at the UCSB Edible Campus farm site and developed the data acquisition system hosted on Aristotle.
  • Installed sensors inside and outside the Citrus Under Protective Screening facility and deployed an IoT system that provides both real-time measurements via a visualization tool developed by Aristotle REU student Kareme Celik and a prototype frost alerting system.

Plans

  • Develop a hybrid machine-learning and CFD model to support Citrus Under Protective Screening (CUPS) spraying operations and frost prevention.
  • Enhance REU student Kerem Celik's telemetry data visualizer which works either as a local tool or as a service hosted in Aristotle.
  • Develop sustainable land use practices at Sedgwick that employ livestock as part of the management lifecycle and install new monitoring infrastructure.
  • Provide the instrumentation and analytics necessary to evaluate the first CUPS installation (at scale) in California. Aristotle will be providing the computational infrastructure to the team that is necessary to analyze the effects of CUPS on citrus production.
  • Developed the Aristotle AWS Pricing Tool to help users compare Aristotle resources to various AWS alternatives based on performance, cost, and price-performance.

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