skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Realtime optimization and management system (ROAM): A decision support system for digital agriculture systems
The growing disparity between food supply and demand requires innovative Digital Agriculture (DA) systems to increase farm sustainability and profitability. However, current systems suffer from problems of complexity stemming from the challenge of integrating diverse, often non-interoperable hardware and software components. In order to tackle these complexities to increase farm efficiency and understand the tradeoffs of these new DA innovations we developed Realtime Optimization and Management System (ROAM), which is a decision-support system developed to find a Pareto optimal architectural design to build DA systems. To find the Pareto optimal solution, we employed the Rhodium Multi-Objective Evolutionary Algorithm (MOEA), which systematically evaluates the trade-offs in DA system designs. Based on data from five live deployments at Cornell University, each DA design can be analyzed based on user defined objectives and evaluated under uncertain farming environments with ROAM. Paired with this, we develop a web interface that allows users to define personalized decision spaces and visualize decision tradeoffs. To help validate ROAM, it was deployed to a commercial farm where the user was recommended a DA architecture design method to increase farm efficiency. ROAM allows users to quickly make key decisions in designing their DA systems to increase farm profitability.  more » « less
Award ID(s):
1955125
PAR ID:
10511240
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
Elsevier, Science Direct
Date Published:
Journal Name:
Smart Agricultural Technology
Volume:
8
Issue:
100452
ISSN:
2772-3755
Page Range / eLocation ID:
1-12
Subject(s) / Keyword(s):
Digital agriculture Decision making under deep uncertainty Systems optimization Systems engineering Internet of things Sustainability
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, SSRN Electronic Journal)
    The growing disparity between food supply and demand requires innovative Digital Agriculture (DA) systems to increase farm sustainability and profitability. However, current systems suffer from problems of complexity. To increase farm efficiency and understand the tradeoffs of these new DA innovations we developed ROAM, which is a decision support system developed to find a Pareto optimal architectural design to build DA systems. Based on data from five live deployments at Cornell University, each DA design can be analyzed based on user defined metrics and evaluated under uncertain farming environments with ROAM. Paired with this, we develop a web interface that allows users to define personalized decision spaces and to visualize decision tradeoffs. To help validate ROAM, it was deployed to a commercial farm where the user was recommended a method to increase farm efficiency. ROAM allows users to quickly make key decisions in designing their DA systems to increase farm profitability. 
    more » « less
  2. ; ; ; ; (, USENIX Annual Technical Conference)
    This work is an experience with a deployed networked system for digital agriculture (or DA). Digital agriculture is the use of data-driven techniques towards a sustainable increase in farm productivity and efficiency. DA systems are expected to be overlaid on existing rural infrastructures, which are known to be less robust. While existing DA approaches partially address several infrastructure issues, challenges related to data aggregation, data analytics, and fault tolerance remain open. In this work, we present the design of Comosum, an extensible, reconfigurable, and fault-tolerant architecture of hardware, software, and distributed cloud abstractions to sense, analyze, and actuate on different farm types. FarmBIOS is an implementation of the Comosum architecture. We analyze FarmBIOS by leveraging various applications, deployment experiences, and network differences between urban and rural farms. This includes, for instance, an edge analytics application achieving 86% accuracy in vineyard disease detection. An eighteen-month deployment of FarmBIOS highlights Comosum’s fault tolerance. It was fault tolerant to intermittent network outages that lasted for several days during many periods of the deployment. We introduce active digital twins to cope with the unreliability of the underlying base systems. 
    more » « less
  3. ; ; ; ; ; ; (, Systems)
    Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically. 
    more » « less
  4. ; ; ; (, Applied geography)
    The demand for ‘local food’ by U.S. consumers has grown markedly over the last several decades, accompanied by confusion over how to define local food. Is ‘local’ food defined by the location of the farm, food processing factory, distribution warehouse, or all three? Is ‘local’ food defined by geographic, political, or biophysical boundaries? Is ‘local’ solely farm-to-table or can it include factories? This study evaluates food commodity flow ‘localness’ using jurisdictional boundaries and physical distance to investigate the potential for food system transformation and the tradeoffs inherent to ‘localizing’ food production. We take a supply chain approach by making data-driven distinctions between farm-based flows of food and industrial, energy and nonfood (IENF) crops, and manufacturing/distribution flows of food and agriculturally-derived industrial inputs. We analyze the diversity, distance (a proxy for environmental impact), political boundaries, population, weight, and price (net selling value) of food commodity flows. The diversity of a community's food supply has an optimal range of zero to four-hundred miles. We find tradeoffs between food system diversity and local food sourcing, sustainability, and self-sufficiency. As communities look to improve food system resilience, they will need to balance food-miles and the other values associated with local food. 
    more » « less
  5. ; ; ; ; (, USENIX Association)
    Given the fundamental tradeoff between run-time and recovery performance, current distributed systems often build application-specific recovery strategies to minimize overheads. However, it is increasingly common for different applications to be composed into heterogeneous pipelines. Implementing multiple interoperable recovery techniques in the same system is rare and difficult. Thus, today's users must choose between: (1) building on a single system, and face a fixed choice of performance vs. recovery overheads, or (2) the challenging task of stitching together multiple systems that can offer application-specific tradeoffs. We present ExoFlow, a universal workflow system that enables a flexible choice of recovery vs. performance tradeoffs, even within the same application. The key insight behind our solution is to decouple execution from recovery and provide exactly-once semantics as a separate layer from execution. For generality, workflow tasks can return references that capture arbitrary inter-task communication. To enable the workflow system and therefore the end user to take control of recovery, we design task annotations that specify execution semantics such as nondeterminism. ExoFlow generalizes recovery for existing workflow applications ranging from ETL pipelines to stateful serverless workflows, while enabling further optimizations in task communication and recovery. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email