ReviewSensors (Basel, Switzerland)2025
The Potential of Low-Cost IoT-Enabled Agrometeorological Stations: A Systematic Review.
Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Low-cost IoT real-time environmental monitoring and one-hour LSTM forecasting for small-scale agricultural applications.Scientific reports · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of Internet of Things (IoT) technologies in agriculture has facilitated real-time environmental monitoring, with low-cost IoT-enabled agrometeorological stations emerging as a valuable tool for climate-smart farming. This systematic review examines low-cost IoT-based weather stations by analyzing their hardware and software components and assessing their potential in comparison to conventional weather stations. It emphasizes their contribution to improving climate resilience, facilitating data-driven decision-making, and expanding access to weather data in resource-constrained environments. The analysis revealed widespread adoption of ESP32 microcontrollers, favored for its affordability and modularity, as well as increasing use of communication protocols like LoRa and Wi-Fi due to their balance of range, power efficiency, and scalability. Sensor integration largely focused on core parameters such as air temperature, relative humidity, soil moisture, and rainfall supporting climate-smart irrigation, disease risk modeling, and microclimate management. Studies highlighted the importance of usability and adaptability through modular hardware and open-source platforms. Additionally, scalability was demonstrated through community-level and multi-station deployments. Despite their promise, challenges persist regarding sensor calibration, data interoperability, and long-term field validation. Future research should explore the integration of edge computing, adaptive analytics, and standardization protocols to further enhance the reliability and functionality of IoT-enabled agrometeorological systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.