Pervasive Agriculture: IoT-Enabled Greenhouse for Plant Growth Control
Abstract
We present Internet of Things (IoT) deployment in a tomato greenhouse in Russia. The IoT enabling technologies applied for this deployment comprise a wireless sensor network, cloud computing, and artificial intelligence. They are to help in monitoring and controlling of both plants and greenhouse conditions as well as predicting the growth rate of tomatoes.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
An AIoT system is set up in a tomato greenhouse, composed of a wireless sensor network and cloud computing center empowered by AI technologies, and deep reinforcement learning is used for obtaining the optimal control policy on the illumination, nutrition, and ventilation conditions in the greenhouse.
“For plant grow control, an AIoT system is set up in a tomato greenhouse [217], which is composed of a wireless sensor network and cloud computing center empowered by AI technologies. Deep reinforcement learning is used for obtaining the optimal control policy on the illumination, nutrition, and ventilation conditions in the greenhouse.”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [217]
The citation lists haven’t been fetched yet
References 16 · Cited by 78
- Authors
- Somov, A., Shadrin, D., Fastovets, I., Nikitin, A., Matveev, S., seledets, I., & Hrinchuk, O.
- Affiliations
- Skolkovo Institute of Science and Technology (RU)
- Skolkovo Institute of Science and Technology
- Venue
- IEEE Pervasive Computing
- Published
- 2018-10-01
- Volume
- 17
- Issue
- 4
- Pages
- 65-75
- ISSN
- 1536-1268 (ISSN-L)
- 1558-2590
- OpenAlex
- W2911446218
- Cited by
- 78
- References
- 16
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 5 · 2023: 12 · 2022: 14 · 2021: 20 · 2020: 14 · 2019: 7
- FWCI
- 9.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Pervasive Computing (publishedVersion)
- Funders
- Skoltech Next Generation Program
- Ministry of Education and Science of the Russian Federation (14.756.31.0001)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Greenhouse Technology and Climate Control
- Life Sciences › Agricultural and Biological Sciences › Aquatic Science › Innovations in Aquaponics and Hydroponics Systems
- Keywords
- Internet of Things, greenhouse monitoring, tomato cultivation, plant growth regulation, wireless sensor networks, cloud computing, artificial intelligence, crop growth prediction, smart agriculture
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
