Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Implementation of Edge Computing Platform for Smart Farm using MQTT and Kafka

Journal of System and Management Sciences · 2022

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Summary

This paper presents the technical implementation of an edge computing platform designed for smart farm operations, utilising MQTT and Kafka as core messaging and data streaming protocols. The work addresses the infrastructure and computational architecture required for real-time farm data management and integration. Whilst the paper contributes to precision agriculture technology, it is primarily focused on computational systems architecture rather than agronomic outcomes or farm performance metrics.

UK applicability

The technical framework may be applicable to UK farm digitalisation initiatives, though applicability depends on compatibility with existing UK farm systems and regulatory requirements for agricultural data management. Adoption would require consideration of UK broadband infrastructure variability and data protection compliance (GDPR).

Key measures

Edge computing platform performance metrics, MQTT and Kafka integration efficacy, data transmission and processing efficiency

Outcomes reported

The study likely describes the technical implementation and performance of an edge computing platform using MQTT and Kafka protocols for real-time farm data collection and processing. The focus appears to be on the architecture and operational feasibility of the system rather than agronomic or health outcomes.

Theme
Measurement & metrics
Subject
Agricultural informatics and digital farming infrastructure
Study type
Research
Study design
Technical implementation study / Case study
Source type
Peer-reviewed study
Status
Published
System type
Mixed / General smart farming systems
DOI
10.33168/jsms.2022.0112
Catalogue ID
NRmo9rin9c-0v9

Topic tags

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