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Cited by 319

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A model for smart agriculture using IoT

Patil, K. A., Kale, N. R.·2016·2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC)

Abstract

Climate changes and rainfall has been erratic over the past decade. Due to this in recent era, climate-smart methods called as smart agriculture is adopted by many Indian farmers. Smart agriculture is an automated and directed information technology implemented with the IOT (Internet of Things). IOT is developing rapidly and widely applied in all wireless environments. In this paper, sensor technology and wireless networks integration of IOT technology has been studied and reviewed based on the actual situation of agricultural system. A combined approach with internet and wireless communications, Remote Monitoring System (RMS) is proposed. Major objective is to collect real time data of agriculture production environment that provides easy access for agricultural facilities such as alerts through Short Massaging Service (SMS) and advices on weather pattern, crops etc.

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Crossref · 10.1109/icgtspicc.2016.7955360

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Metadata

Authors
Patil, K. A., & Kale, N. R.
Venue
2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC)
Publisher
IEEE
Published
2016-12
Pages
543-545
OpenAlex
W2719814673
Cited by
319
References
3
FWCI
52.61
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: A model for smart agriculture using IoT. https://app.cochat.ai/papers/10.1109/icgtspicc.2016.7955360
The paper
Patil, K. A., & Kale, N. R. (2016). A model for smart agriculture using IoT. 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC). https://doi.org/10.1109/icgtspicc.2016.7955360

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.