Recipient Organization
IOWA STATE UNIVERSITY
2229 Lincoln Way
AMES,IA 50011
Performing Department
ANIMAL SCIENCE - CALS/AES
Non Technical Summary
The U.S. swine industry is facing increasing challenges, includinglabor shortages andthe needfor improved animal health and welfare, and farm profitability. While new precision livestock technologies, such as wearable sensors and computer vision,offer promising solutions, swine producersare hesitant toadopt thembecause theylacka value proposition and farm suitability information. To bridge this gap between innovation and farm adoption, our project will develop testing strategies and evaluation tools for swine producers. This project will developdedicated technology transfer centersequipped with the required network and computer infrastructureto test and evaluate technologies, simulating real farm conditions. We will also develop a standardevaluation processto guide the properassessmentof accuracy, reliability, and implementabilityof new technologies. Results of this projectwill be shared widely through factsheets, online resources, and industry events to increase swine producers' awareness and adoption of new technologies.This project is critical to influence and accelerate the adoption of smart farming tools in commercial swine barns, enhancing production efficiency and improving system sustainability.
Animal Health Component
60%
Research Effort Categories
Basic
10%
Applied
60%
Developmental
30%
Goals / Objectives
The overall objectiveof this project is to influence and accelerate the adoption ofPrecision Livestock Farming (PLF) technologies in commercial swine farms by developing standardizedtechnology evaluation processes and centers for technology transfer. To accomplish this, our project includes the following objectives:Objective 1: Develop a Standard Technology Evaluation Process (STEP) tailored to commercial swine farms. A structured andrepeatable evaluation frameworkwill be developedto assess the accuracy, reliability, and implementability of new technologies. TheSTEP framework will be demonstrated throughcase studies evaluating computer vision systems for the early identification ofpost-weaning fall-behind pigs and estimation ofpig weights. In addition, wearable sensors will be evaluated for their effectiveness in monitoring sow farrowing events.Objective 2: Establish technology evaluation centers across key phases of pig production. We willretrofit and equip existing university-affiliated swine research farms to serve as technology evaluation centers that simulate commercial settings. These centers will include 1) anursery barn to evaluate technologies thatdetect early signs of post-weaning stress and fallout pigs; 2) a grow-finish barn to assess the accuracy and reliability of computer vision systems for daily weight estimation and growth monitoring; and 3) a sow farrowing barn to validate wearable sensors for monitoring sow health and farrowing complications.Objective 3:Increase awareness and adoption of new technologies suitable for swine farms.Evaluation outcomes will be disseminatedthrough factsheets, producer-friendly summaries, podcasts, and presentations at industry conferences. We will also conductadoptability tests toidentify the value propositions that maximize the likelihood of adoption of new technologies in swine farms.
Project Methods
We will develop three STEP evaluation frameworks for: 1) computer vision systems to identify fallout weaned pigs, 2) computer vision systems to estimate pig weights, and 3) wearable sensors that monitor farrowing events. The frameworkswill include a review of the infrastructure requirements, a cost-benefit analysis, methods to assess the accuracy (e.g., >95% weight estimation accuracy), and methods to determine the reliability (>90% uptime for pig weight data).These frameworks will be evaluated by swine producers and technology developers throughfeedback on usability and value of STEP, and by academic researchersin peer-reviewed journals.Establishing technology evaluation centers by retrofitting existing nursery, grow-finish, and farrowing barns to support technology testing. Enhancements include extending the internet and electrical infrastructure, and installingcameras and servers to enable continuous video monitoring and data collection. A centralized database will be developed to collect and manage real-time data from both evaluation centers. This system will support automated data transfer, secure backups, and advanced analytics, enabling comprehensive evaluation of PLF technologies.Three comprehensive technology testswill be conducted in the nursery, grow-finish, and farrowing phases.At Iowa State University, computer vision systems will be evaluated for the earlyidentification of fall-behindweaned pigs and estimation of body weights. The accuracy of the system will be validated against caretaker observations and video footage over four production cycles. Computer vision to estimate daily pig weights of pigs will be compared to scale measurements across four cycles.At the University of Missouri, wearable sensors will be evaluated during farrowing events to predict complications. Sensor data (e.g., heart rate, temperature, movement) will be validated against video recordings and caretaker observations over four farrowing cycles.Dissemination of the project outcomeswill employ a multi-channelstrategy targeting swine producers, veterinarians, and industry stakeholders. In collaboration with the Iowa Pork Industry Center at Iowa State University, we will develop fact sheets detailing the STEP framework and technology evaluations, popular press articles, and peer-reviewed summaries shared via digital platforms.We aim to produce digital factsheets and podcasts and measure user engagement.We will conduct adoptability studies using varied training approaches, including (i) no training or unsupervised, (ii) self-directed online training, (iii) in-person group training, and (iv) on-farm individual training. These studies will assess producer feedback on the value of technical features and potential benefits of the technologies.