# IoT Framework for Measurement and Precision Agriculture: Predicting the Crop Using Machine Learning Algorithms

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/iot-framework-for-measurement-and-precision-agriculture-predicting-the-crop/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Kalaiselvi Bakthavatchalam,B. Karthik,V. Sanjay Thiruvengadam,Sriram Muthal,Deepa Jose,Ketan Kotecha,V. Vijayakumar |
| Citations | 131 |
| DOI | 10.3390/technologies10010013 |
| Fields | Agricultural and Biological Sciences,Computer Science,Environmental Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2227-7080/10/1/13/pdf?version=1642679704 |
| OpenAlex ID | https://openalex.org/W4207044822 |
| Type | article |
| Year | 2022 |

## Paper authors

- [V. Vijayakumar](https://scholariq.org/researchers/v-vijayakumar/)

## Paper primary topic

- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)

## Paper topics

- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Water Quality Monitoring Technologies](https://scholariq.org/topics/water-quality-monitoring-technologies/)
- [IoT and Edge/Fog Computing](https://scholariq.org/topics/iot-and-edge-fog-computing/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.