Smart Backyard Chicken Goes Rural: AI/ML for Sustainable Flocks

Project Overview

FNE26-154
Project Type: Farmer
Funds awarded in 2026: $30,000.00
Projected End Date: 11/30/2029
Grant Recipient: Shomron Farm
Region: Northeast
State: Pennsylvania
Project Leader:
Joseph Litvak
Shomron Farm

Commodities

  • Animals: poultry
  • Animal Products: eggs, meat

Practices

  • Animal Production: free-range, grazing - rotational
  • Farm Business Management: labor/employment
  • Sustainable Communities: community development, new business opportunities

    Proposal summary:

    This project focuses on developing autonomous agricultural technologies that support rural community development, regenerative land management, and experiential learning. Its primary objective is to design, test, and evaluate an autonomous, mobile chicken coop capable of continuous seven-day operation with minimal supervision, while examining its contributions to animal welfare, soil health, and household and community economic resilience. A secondary objective is to generate transferable knowledge to scale the system for larger agricultural operations through a subsequent Smart Rural Chicken model.

    The plan of work centers on engineering and prototyping the Smart Backyard Chicken system and integrating AI/ML-enabled monitoring to track soil conditions, feed usage, flock health indicators, water quality and availability, and all aspects of coop functionality. Field trials will incorporate rotational grazing principles to assess impacts on soil aeration, nutrient cycling, vegetation recovery, and biodiversity. Soil testing, operational measurements, and performance data will jointly inform a technical and scientific evaluation of the system's regenerative and economic potential. Insights from this first phase will guide the design of a scalable autonomous system for mid-sized rural farms.

    Outreach is central to the project's mission. High school students, Penn State undergraduate and graduate students, local farmers, and community partners will participate in hands-on design activities, demonstrations, and data-centered workshops. These engagement efforts will strengthen agricultural literacy, foster innovation, and build community capacity for regenerative and autonomous farming practices. Through this integrated approach, the project will assess how autonomous small-scale systems can improve household well-being, promote soil regeneration, and support long-term rural economic revitalization.

    Project objectives from proposal:

    The Smart Backyard Chicken project aims to develop, test, and evaluate an autonomous, mobile poultry management system that strengthens soil health, promotes animal welfare, reduces labor burdens, and enhances the viability of small and mid-scale farms in the Northeast. The technology will also promote sustainable homesteading, and contribute to communities' mental and physical health, and food security. The following objectives describe, in specific and measurable terms, what this project intends to achieve during the implementation period.

    Objective 1: Design and construct a fully functional autonomous mobile chicken coop capable of operating continuously for seven days with minimal human intervention.
    This objective will be met by engineering a mobile coop platform equipped with automated watering, feed delivery, ventilation, and environmental controls, as well as structural elements appropriate for rotational grazing. The finished prototype will be field-ready and documented through system specifications, engineering drawings, and operational logs.

    Objective 2: Develop and implement an AI/ML-enabled monitoring system that tracks soil conditions, feed usage, water availability, flock health indicators, and coop-level functionality in real time.
    This system will be built collaboratively with Penn State faculty and student researchers. Measurable outputs include validated data streams from sensors, functioning algorithms capable of detecting anomalies or irregularities, and dashboards or data summaries supporting management decisions. Success will be measured by system accuracy, reliability, and usability in field settings.

    Objective 3: Evaluate the system's impact on soil health and pasture regeneration through structured rotational grazing trials.
    This includes pre- and post-grazing soil assessments measuring compaction, nutrient availability, organic matter levels, ground cover, and moisture retention. The objective will be met when quantitative comparisons document soil response under autonomous coop movement relative to existing manual practices.

    Objective 4: Assess animal welfare outcomes-including access to clean water, feed stability, behavioral indicators, mortality, and predator exposure-under autonomous management conditions.
    This objective will be evaluated using measurable welfare indicators tracked through manual observations and monitoring data. Documentation will include flock health records, predator incidents, and overall performance of the autonomous system relative to traditional management.

    Objective 5: Quantify labor savings, operational efficiencies, and economic impacts associated with autonomous coop deployment.
    This includes tracking labor hours saved, reductions in feed and water waste, improvements in productivity, and estimated cost impacts. Data will be collected through time-use logs, resource consumption measurements, and cost-benefit analyses conducted with support from collaborating faculty and students.

    Objective 6: Train and engage undergraduate and graduate students in AI/ML-driven sustainable agriculture research under the supervision of Penn State faculty.
    Success will be measured by the number of students participating, training modules completed, analytic tools developed, and contributions to field data collection, modeling, and evaluation.

    Objective 7: Develop and deliver outreach programming-including workshops, demonstrations, and community presentations-to share project findings with farmers, rural residents, high school students, and agricultural educators.
    This objective will be achieved through documented events, attendance counts, educational materials developed, and participant feedback surveys evaluating usefulness and relevance.

    Together, these objectives create a coherent pathway for testing autonomous poultry management practices, generating rigorous data, engaging the community, and advancing sustainable agriculture across the Northeast.

    Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and should not be construed to represent any official USDA or U.S. Government determination or policy.