Progress 07/01/22 to 06/30/23
Outputs
Target Audience: We have reached out to U.S. dairy industry personnel who serve as supporting advisors to dairy farmers on topics relating to heat stress, heat abatement, and ventilation, including dairy consultants, nutritionists, veterinarians, extension educators, and fan/ventilation-system manufacturers and distributors. These audiences were reached through both in-person workshops and webinars delivered by Co-PI Van Os. A senior capstone design team in the Biological Systems Engineering (BSE) Department developed and tested a controlled environmental monitoring system based on the IoT-based wireless data acquisition unit. We have been reaching out to the producers via the BSE extension specialists and the veterinarian school faculty and staff. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In Year 2, three PhD students, one MS student, and four undergraduate students participated in the project. Graduate students were closely co-advised by PI Kim and Co-PI Choi. ECE graduate students: Embedded system hardware and software design. Computer vision and machine learning. Complete UWB system planning and setup. Camera setup and power supply wiring. BSE graduate students: CFD modeling. Preparation of wearable and cow in-body sensor devices. Microclimate monitoring. Wearable device design, testing, and construction. Field/ barn experiment planning and setup. ECE undergraduate students: Sensor system design, deployment, and evaluation. BSE undergraduate students: Assist field experiment with dairy cows, data acquisition, and analysis. How have the results been disseminated to communities of interest?In addition to the publications reported, Hanwook Chung, a participating PhD student, gave a talk on the current research works under the title "Development of a Continuous, Low-Power, Wireless Core Body Temperature Monitoring System to Detect Heat Stress of Dairy Cows in Real Time" at 2023 American Society of Agricultural and Biological Engineers (ASABE) Annual International Meeting (AIM). What do you plan to do during the next reporting period to accomplish the goals?In Year 3, we will focus on analyzing the data collected in summer 2023 to understand how their physiological and behavioral signatures change under heat stress. The multimodal dataset newly collected in Year 2 will further improve the model. Various machine learning techniques, including computer vision and time-series prediction, will be used to understand and model the data. Specific goals include: Optimize the UWB system in terms of both anchor location and deployment, ear tag size wearable device, efficient and accurate position analysis from the raw data. Develop a ventilation control system that can integrate the multimodal dataset that we are building. Continue to develop a compact, lightweight ear tag unit. Conduct field studies with dairy cows with the developed and laboratory-tested system. Carry out computational simulations to mitigate heat stress. We will also continue investigating cattle cooling system optimization using computational fluid dynamics (CFD).
Impacts
What was accomplished under these goals?
In Year 2 of the project, we deployed and tested the sensor system developed in Year 1. In summer 2022, we deployed wearable temperature sensors for temperature monitoring at the Dairy Cattle Center (DCC) at UW-Madison to collect subcutaneous and vaginal temperatures. The design of the sensor has been published at the ACM International Conference on Mobile Computing and Networking (MobiCom), and the comparison results are accepted for publication in the Biosystems Engineering Journal. In summer 2023, we developed a new sensor system that includes core body temperature sensing, localization, direction and elevation sensing. We also installed multiple time-lapse cameras for collecting visual data. The system was deployed at the Dairy Research Farm at UW Madison. These data will be used to understand and model heat stress-related signatures in dairy cattle.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Seunghyeon Jung, Hanwook Chung, and Christopher Y. Choi. 2023. Assessment of Airflow Patterns Induced by a Retractable Baffle to Mitigate Heat Stress in a Large-Scale Mechanically Ventilated Barn, Agriculture, 13, no. 10.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Hien Vu, Hanwook Chung, Christopher Choi, and Younghyun Kim. 2023. eTag: An Energy-Neutral Ear Tag for Real-Time Body Temperature Monitoring of Dairy Cattle, International Conference on Mobile Computing and Networking (MobiCom).
- Type:
Journal Articles
Status:
Accepted
Year Published:
2023
Citation:
Hanwook Chung, Hien Vu, Younghyun Kim, and Christopher Y. Choi. 2023. "Subcutaneous Temperature Monitoring through Ear Tag for Heat Stress Detection in Dairy Cows," Biosystems Engineering.
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Progress 07/01/21 to 06/30/22
Outputs
Target Audience: We have reached out to U.S. dairy industry personnel who serve as supporting advisors to dairy farmers on topics relating to heat stress, heat abatement, and ventilation, including dairy consultants, nutritionists, veterinarians, extension educators, and fan/ventilation-system manufacturers and distributors. These audiences were reached through both in-person workshops and webinars delivered by Co-PI Van Os. We have interacted with a local IT entrepreneur who is interested in integrating dairy welfare with their block-chain based dairy product supply chain management. This audience was reached through both in-person and online meetings by PI Kim and Co-PI Van Os. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In Year 1, three PhD students, one MS student, and four undergraduate students participated in the project. Graduate students were closely co-advised by PI Kim and Co-PI Choi. ECE graduate students:Embedded system hardware and software design. RFID and wireless power transfer circuit design.Computer vision and machine learning. BSE graduate students:CFD modeling. Wearable device design for field experiments with dairy cows.Microclimate monitoring. Embedded system software design for field experiments with dairy cows. ECE undergraduate students:Cloud computing. Embedded software design. BSE undergraduate students:Field experiment with dairy cows, data acquisition, and analysis. How have the results been disseminated to communities of interest? Co-PI Van Os delivered talks at in-person workshops and webinars. Other products are under preparation for dissemination through conference and journal papers in Year 2. What do you plan to do during the next reporting period to accomplish the goals?In Year 2, we will complete the evaluation part of Objective 1, and focus on Objective 2 based on the data collected through Objective 1. More specifically, the following research tasks will be performed. Analyze cattle behavior under heat stress: In our experiment planned for this summer, we will make a video recording of the cattle's behavior as we measure CBT using the developed sensors. The video will capture individual behavior of the cattle (such as standing/lying time and eating/drinking amount) as well as their herd behavior (such as location of and distance between the cows). We will analyze the correlation between CBT and the behavioral indications that can be used to infer heat stress without directly measuring CBT of all cows. Analyze response to subcutaneous sensor: The recorded video will also reveal how the cows respond to the subcutaneous temperature sensors and the wearable reader. Although the injection of subcutaneous devices for animal identification, the reader will be slightly heavier than normal ear tags, and its acceptance by the cows will be systematically studied by analyzing their behaviors. Design heat stress assessment models: Based on the collected data and CFD simulations, we will build microclimate and heat stress assessment models that can help the decision making of the farmers during the design and operation of barns. This will also be used for automated CFD-based cooling optimization in Objective 3.
Impacts
What was accomplished under these goals?
Measuring the cow's CBT in real time is the key to enable the proposed cyber-physical system (CPS) for heat stress management. In Year 1, we focused on the development of the implementable temperature sensor, which is Objective 1 of the project. Specifically, we have achieved the goal of designing a CBT sensor and behavioral and environmental sensors. The wearable CBT sensor is the first wearable RFID reader device with wirelessly charging capability. The details of the design is described in the "Other Products" section of this report. We are currently at the stage of validation and optimization of the sensors. We also have made progress in Objective 3 where the goal is to optimally design dairy barns based on CFD. In Year 1, we developed a CFD model of a dairy barn, which will be utilized for the optimal management of dairy barns in the later part of this project.
Publications
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