ReviewiScience2024
A transformative framework reshaping sustainable drought risk management through advanced early warning systems.
Review in iScience, 2024. 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.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In light of the increasing vulnerability to drought occurrences and the heightened impact of drought-related disasters on numerous communities, it is imperative for drought-sensitive sectors to adopt proactive measures. This involves the implementation of early warning systems to effectively mitigate potential risks. Guided by Toulmin's model of argumentation, this research proposes a framework of eight interconnected modules introducing Fourth Industrial Revolution technologies to enhance drought early warning capabilities. The framework emphasizes the Internet of Things, drones, big data analytics, and deep learning for real-time monitoring and accurate drought forecasts. Another key component is the role of natural language processing in analyzing data from unstructured sources, such as social media, and reviews, essential for improving alerts, dissemination, and interoperability. While the framework optimizes resource use in agriculture, water, and the environment, overcoming impending limitations is crucial; hence, practical implementation and amendment of policies are necessary.
Indexed as
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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.