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Precision Dairy Edge, Albeit Analytics Driven: A Framework to Incorporate Prognostics and Auto Correction Capabilities for Dairy IoT Sensors

  • Santosh KedariEmail author
  • Jaya Shankar Vuppalapati
  • Anitha Ilapakurti
  • Chandrasekar Vuppalapati
  • Sharat Kedari
  • Rajasekar Vuppalapati
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 887)

Abstract

Oxford English Dictionary defines Prognostics as “an advance indication of a future event, an omen”. Generally, it is confined to fortune or future foretellers, more have subjective or intuition driven. Data Science, on the other hand, embryonically enables to model and predict the health condition of a system and/or its components, based upon current and historical system generated data or status. The chief goal of prognostics is precise estimation of Remaining Useful Life (RUL) of equipment or device. Through our research and through industrial field deployment of our Dairy IoT Sensors, we emphatically conclude that Prognostics is a vital marker in the lifecycle of a device that can be deduced as inflection point to trigger auto-corrective, albeit edge analytics driven, in Dairy IoT Sensors so that the desired ship setting functions can be achieved with precision. Having auto-corrective capability, importantly, plays pivotal role in achieving satisfaction of Dairy farmers and reducing the cost of maintaining the Dairy sensors to the manufacturers as these sensors are deployed in geographically different regions with intermittent or network connectivity. Through this paper, we propose an inventive, albeit, small footprint, ML (Machine Learning) dairy edge that incorporates supervised and unsupervised models to detect prognostics conditions so as to infuse auto-corrective behavior to improve the precision of dairy edge. The paper presents industrial dairy sensor design and deployment as well as its data collection and certain field experimental results.

Keywords

Dairy sensors Precision sensors Prognastics Dairy Precision dairy edge Prognosis approach Open system architecture for condition based monitoring OSA-CBM Hanumayamma Innovations and Technologies 

Notes

Acknowledgments

We truly thank management team of Hanumayamma Innovations and Technologies, Inc. and its subsidiaries for providing Dairy IoT Sensors and special thank you to their team personnel who were instrumental in capturing and sharing the field data.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Santosh Kedari
    • 1
    Email author
  • Jaya Shankar Vuppalapati
    • 1
  • Anitha Ilapakurti
    • 2
  • Chandrasekar Vuppalapati
    • 2
  • Sharat Kedari
    • 2
  • Rajasekar Vuppalapati
    • 2
  1. 1.Hanumayamma Innovations and Technologies Private LimitedHyderabadIndia
  2. 2.Hanumayamma Innovations and Technologies, Inc.FremontUSA

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