A Conceptual Framework for the Development of Data Acquisition and Integration System for the Dairy Industry

Mohit Malik, Vijay Kumar Gahlawat*, Rahul S Mor*, Kumar Rahul, Vijay Dahiya

*Corresponding author for this work

Research output: Contribution to Book/ReportChapterpeer-review

Abstract

Data acquisition and integration are vital aspects of circular industrial initiatives and help industries develop balanced coordination with other stakeholders and commitment to circular standards. Small and medium-sized enterprises hesitate to implement the necessary automation and information collection process because of high investment issues. The dairy industry does have a growing need for precise process information. The literature points toward the need for proper data management. This research aims to develop a conceptual model for data acquisition and integration for the dairy industry. A theoretical framework is proposed for data acquisition and integration in the dairy industry based on Big Data Analytics (BDA) and the Internet of Things (IoT). The model will help monitor, collect, manage, and analyze information flow in the dairy supply chain. It gives the industry direct access to IoT technology for collecting real-time data on essential quality parameters like pH, temperature, etc. The model will also help improve the data management process in the internal and external context of data sharing. Implementation of such a system is necessary nowadays to improve food safety and quality, especially in the Indian context. The findings indicate that effective implementation of the developed model will transform the dairy industry including enhancement of dairy operations, transparent supply chain, effective data management, forecasting, and many other value additions in dairy management.
Original languageEnglish
Title of host publicationScience, Engineering Management and Information Technology (SEMIT 2023)
EditorsAmir Mirzazadeh, Zahra Molamohamadi, Bahram Erdebilli, Ebrahim Babaee Tirkolaee, Gerhard-Wilhelm Weber
PublisherSpringer Nature
Chapter1
Pages3-16
Number of pages14
Volume2199
ISBN (Electronic)978-3-031-72287-5
ISBN (Print)978-3-031-72286-8
DOIs
Publication statusPublished - 12 Sept 2024

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer Cham
Volume2199

Bibliographical note

We acknowledge the National Institute of Food Technology Entrepreneurship and Management (NIFTEM-K), Kundli, Sonepat, Haryana, India, for supporting this study. NIFTEM-K communication number: NIFTEM-P-2024-45.

Keywords

  • Big Data Analytics
  • Dairy industry
  • Data acquisition and integration
  • Internet of Things (IoT)
  • Optimization

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