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.
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Notes
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IoT and Prognostic Analytics for Predictive Maintenance - https://www.experfy.com/blog/iot-and-prognostic-analytics-for-predictive-maintenance.
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Si7020 – A10: http://www.mouser.com/ds/2/368/Si7020-272416.pdf
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Materials Science and Engineering – A First Course by V. Raghavan, Fifth Edition, Thirty-Fourth Print, April 2007 Edition, Prentice-Hall of India Pvt Ltd.
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Sensor Technology Handbook, Jon S. Wilson
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Correcting temperature and humidity forecasts using Kalman filtering: Potential for agricultural protection in Northern Greece - https://www.researchgate.net/publication/233997840_Correcting_temperature_and_humidity_forecasts_using_Kalman_filtering_Potential_for_agricultural_protection_in_Northern_Greece
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AVR RISC – Advanced Virtual reduced instruction set computer (http://www.atmel.com/products/microcontrollers/avr/)
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Arduino bootloader - https://www.arduino.cc/en/Hacking/MiniBootloader
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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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Kedari, S., Vuppalapati, J.S., Ilapakurti, A., Vuppalapati, C., Kedari, S., Vuppalapati, R. (2019). Precision Dairy Edge, Albeit Analytics Driven: A Framework to Incorporate Prognostics and Auto Correction Capabilities for Dairy IoT Sensors. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-030-03405-4_35
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