Using Edge Analytics to Improve Data Collection in Precision Dairy Farming

Kriti Bhargava, Stepan Ivanov, William Donnelly, Chamil Kulatunga

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Despite the numerous advantages of using Wireless Sensor Networks (WSN) in precision farming, the lack of infras-tructure in the remote farm locations as well as the constraints of WSN devices have limited its role, to date. In this paper, we present the design and implementation of our WSN based prototype system for intelligent data collection in the context of precision dairy farming. Due to the poor Internet connectivity in a typical farm environment, we adopt the delay-tolerant networking paradigm. However, the data collection capability of our system is restricted by the memory constraints of the constituent WSN devices. To address this issue, we propose the use of Edge Mining, a novel fog computing technique, to compress farming data within the WSN. Opposed to the conventional data compression techniques, Edge Mining not only optimizes memory usage of the sensor device, but also builds a foundation for future real-time responsiveness of the prototype system. In particular, we use L-SIP, one of the Edge Mining techniques that provides real-time event-driven feedbacks while allowing accurate reconstruction of the original sensor data, for our data compression tasks. We evaluate the performance of L-SIP in terms of Root Mean Square Error (RMSE) and memory gain using R analysis.
LanguageEnglish
Title of host publicationProceedings - Conference on Local Computer Networks, LCN
PublisherIEEE Computer Society
Pages137-144
Number of pages8
ISBN (Electronic)9781509023479
DOIs
Publication statusPublished - 14 Feb 2017
Event41st Conference on Local Computer Networks Workshops - Dubai, United Arab Emirates
Duration: 7 Nov 201610 Nov 2016

Publication series

NameProceedings - Conference on Local Computer Networks, LCN

Conference

Conference41st Conference on Local Computer Networks Workshops
Abbreviated titleLCN Workshops
CountryUnited Arab Emirates
CityDubai
Period7/11/1610/11/16

Fingerprint

Dairies
Wireless sensor networks
Data compression
Data storage equipment
Farms
Sensors
Fog
Mean square error
Internet
Feedback

Keywords

  • Wireless sensor networks
  • Data mining
  • Cows
  • Data compression
  • Data collection
  • Logic gates
  • Real-time systems

Cite this

Bhargava, K., Ivanov, S., Donnelly, W., & Kulatunga, C. (2017). Using Edge Analytics to Improve Data Collection in Precision Dairy Farming. In Proceedings - Conference on Local Computer Networks, LCN (pp. 137-144). (Proceedings - Conference on Local Computer Networks, LCN). IEEE Computer Society. https://doi.org/10.1109/LCN.2016.039

Using Edge Analytics to Improve Data Collection in Precision Dairy Farming. / Bhargava, Kriti; Ivanov, Stepan; Donnelly, William; Kulatunga, Chamil.

Proceedings - Conference on Local Computer Networks, LCN. IEEE Computer Society, 2017. p. 137-144 (Proceedings - Conference on Local Computer Networks, LCN).

Research output: Chapter in Book/Report/Conference proceedingChapter

Bhargava, K, Ivanov, S, Donnelly, W & Kulatunga, C 2017, Using Edge Analytics to Improve Data Collection in Precision Dairy Farming. in Proceedings - Conference on Local Computer Networks, LCN. Proceedings - Conference on Local Computer Networks, LCN, IEEE Computer Society, pp. 137-144, 41st Conference on Local Computer Networks Workshops , Dubai, United Arab Emirates, 7/11/16. https://doi.org/10.1109/LCN.2016.039
Bhargava K, Ivanov S, Donnelly W, Kulatunga C. Using Edge Analytics to Improve Data Collection in Precision Dairy Farming. In Proceedings - Conference on Local Computer Networks, LCN. IEEE Computer Society. 2017. p. 137-144. (Proceedings - Conference on Local Computer Networks, LCN). https://doi.org/10.1109/LCN.2016.039
Bhargava, Kriti ; Ivanov, Stepan ; Donnelly, William ; Kulatunga, Chamil. / Using Edge Analytics to Improve Data Collection in Precision Dairy Farming. Proceedings - Conference on Local Computer Networks, LCN. IEEE Computer Society, 2017. pp. 137-144 (Proceedings - Conference on Local Computer Networks, LCN).
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