# Edge-Enabled Mobile App for Smart Agriculture Using Multi-Sensor Inputs and a Hybrid CNN–Vision Transformer Model

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/edge-enabled-mobile-app-for-smart-agriculture-using-multi-sensor-inputs-and-a/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Thomas Kinyanjui Njoroge,Rachael Kibuku,Kelvin Mugoye Sindu |
| Citations | 1 |
| DOI | 10.3991/ijim.v19i21.55919 |
| Fields | Agricultural and Biological Sciences,Environmental Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://online-journals.org/index.php/i-jim/article/download/55919/16695 |
| OpenAlex ID | https://openalex.org/W4415990609 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Thomas Kinyanjui Njoroge](https://scholariq.org/researchers/thomas-kinyanjui-njoroge/)
- [Rachael Kibuku](https://scholariq.org/researchers/rachael-kibuku/)

## 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/)
- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)
- [Plant Disease Management Techniques](https://scholariq.org/topics/plant-disease-management-techniques/)

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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.