# An End to End Indoor Air Monitoring System Based on Machine Learning and SENSIPLUS Platform

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/an-end-to-end-indoor-air-monitoring-system-based-on-machine-learning-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Mario Molinara,Marco Ferdinandi,G. Cerro,Luigi Ferrigno,Ettore Massera |
| Citations | 41 |
| DOI | 10.1109/access.2020.2987756 |
| Fields | Engineering,Environmental Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/8948470/09064782.pdf |
| OpenAlex ID | https://openalex.org/W3017029694 |
| Type | article |
| Year | 2020 |

## Paper authors

- [G. Cerro](https://scholariq.org/researchers/g-cerro/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

- [Air Quality Monitoring and Forecasting](https://scholariq.org/topics/air-quality-monitoring-and-forecasting/)

## Paper topics

- [Air Quality Monitoring and Forecasting](https://scholariq.org/topics/air-quality-monitoring-and-forecasting/)
- [Fire Detection and Safety Systems](https://scholariq.org/topics/fire-detection-and-safety-systems/)
- [Advanced Chemical Sensor Technologies](https://scholariq.org/topics/advanced-chemical-sensor-technologies/)

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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.