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Using Accelerometers and AI to Improve Animal Welfare on Farms – Prof. Suresh Neethirajan (Pt1)

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Manage episode 445077101 series 2790247
内容由paresearcher提供。所有播客内容(包括剧集、图形和播客描述)均由 paresearcher 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

"Can AI predict health problems in farm animals before they even show symptoms?"
In this fascinating episode, Dr. Olli Tikkanen welcomes Professor Suresh Neethirajan, an expert in digital agriculture and animal welfare, to explore how artificial intelligence and accelerometer data are revolutionizing the way we care for farm animals. Prof. Neethirajan shares how his team uses AI models, combining accelerometer data with other health metrics, to predict issues like lameness in cows weeks before symptoms appear. This early detection could transform farm management by enabling preventative care, improving animal welfare, and enhancing farm productivity.

The episode also dives into the practical challenges of collecting data from various farm animals, including cows, sheep, and chickens, and how accelerometers and AI models can provide insights into their behavior and health. Prof. Neethirajan explains how activity data is used to assess movement patterns, stress indicators, and even predict metabolic disorders in animals. If you’re curious about how technology is being applied to improve animal welfare and farm management, this episode offers a compelling look into the future of agriculture.

________________________

This podcast episode is sponsored by Fibion Inc. | Better Sleep, Sedentary Behavior and Physical Activity Research with Less Hassle

---

Collect, store and manage SB and PA data easily and remotely -

Discover ground-breaking Fibion SENS.

---

SB and PA measurements, analysis, and feedback made easy - Learn more about Fibion Research.

---

Learn more about Fibion Sleep and Fibion Circadian Rhythm Solutions.

---

Fibion Kids - Activity tracking designed for children.

---

Explore our Wearables, Experience sampling method (ESM), Sleep, Heart rate variability (HRV), Sedentary Behavior and Physical Activity article collections for insights on related articles.

---

Refer to our article "Physical Activity and Sedentary Behavior Measurements" for an exploration of active and sedentary lifestyle assessment methods.

---

Learn about actigraphy in our guide: Exploring Actigraphy in Scientific Research: A Comprehensive Guide.

---

Gain foundational ESM insights with "Introduction to Experience Sampling Method (ESM)" for a comprehensive overview.

---

Explore accelerometer use in health research with our article "Measuring Physical Activity and Sedentary Behavior with Accelerometers ".

---

For an introduction to the fundamental aspects of HRV, consider revisiting our Ultimate Guide to Heart Rate Variability.

---

Follow the podcast on Twitter https://twitter.com/PA_Researcher

Follow host Dr Olli Tikkanen on Twitter https://twitter.com/ollitikkanen

Follow Fibion on Twitter https://twitter.com/fibion

Check us on YouTube: https://www.youtube.com/@PA_Researcher

  continue reading

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Artwork
icon分享
 
Manage episode 445077101 series 2790247
内容由paresearcher提供。所有播客内容(包括剧集、图形和播客描述)均由 paresearcher 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

"Can AI predict health problems in farm animals before they even show symptoms?"
In this fascinating episode, Dr. Olli Tikkanen welcomes Professor Suresh Neethirajan, an expert in digital agriculture and animal welfare, to explore how artificial intelligence and accelerometer data are revolutionizing the way we care for farm animals. Prof. Neethirajan shares how his team uses AI models, combining accelerometer data with other health metrics, to predict issues like lameness in cows weeks before symptoms appear. This early detection could transform farm management by enabling preventative care, improving animal welfare, and enhancing farm productivity.

The episode also dives into the practical challenges of collecting data from various farm animals, including cows, sheep, and chickens, and how accelerometers and AI models can provide insights into their behavior and health. Prof. Neethirajan explains how activity data is used to assess movement patterns, stress indicators, and even predict metabolic disorders in animals. If you’re curious about how technology is being applied to improve animal welfare and farm management, this episode offers a compelling look into the future of agriculture.

________________________

This podcast episode is sponsored by Fibion Inc. | Better Sleep, Sedentary Behavior and Physical Activity Research with Less Hassle

---

Collect, store and manage SB and PA data easily and remotely -

Discover ground-breaking Fibion SENS.

---

SB and PA measurements, analysis, and feedback made easy - Learn more about Fibion Research.

---

Learn more about Fibion Sleep and Fibion Circadian Rhythm Solutions.

---

Fibion Kids - Activity tracking designed for children.

---

Explore our Wearables, Experience sampling method (ESM), Sleep, Heart rate variability (HRV), Sedentary Behavior and Physical Activity article collections for insights on related articles.

---

Refer to our article "Physical Activity and Sedentary Behavior Measurements" for an exploration of active and sedentary lifestyle assessment methods.

---

Learn about actigraphy in our guide: Exploring Actigraphy in Scientific Research: A Comprehensive Guide.

---

Gain foundational ESM insights with "Introduction to Experience Sampling Method (ESM)" for a comprehensive overview.

---

Explore accelerometer use in health research with our article "Measuring Physical Activity and Sedentary Behavior with Accelerometers ".

---

For an introduction to the fundamental aspects of HRV, consider revisiting our Ultimate Guide to Heart Rate Variability.

---

Follow the podcast on Twitter https://twitter.com/PA_Researcher

Follow host Dr Olli Tikkanen on Twitter https://twitter.com/ollitikkanen

Follow Fibion on Twitter https://twitter.com/fibion

Check us on YouTube: https://www.youtube.com/@PA_Researcher

  continue reading

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