ArticleSensors (Basel, Switzerland)2018
IoT-Based Strawberry Disease Prediction System for Smart Farming.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of IoT Solutions for Smart Farming.Sensors (Basel, Switzerland) · 2020Pooled it
- The role of induced resistance in mitigating postharvest fungal diseases in fruits and vegetables.Journal of advanced research · 2026Review
- Smart agriculture in Asia.Plant communications · 2025Review
- Monitoring Ambient Parameters in the IoT Precision Agriculture Scenario: An Approach to Sensor Selection and Hydroponic Saffron Cultivation.Sensors (Basel, Switzerland) · 2022Article
- A Cloud Enabled Crop Recommendation Platform for Machine Learning-Driven Precision Farming.Sensors (Basel, Switzerland) · 2022Article
- Secured and Deterministic Closed-Loop IoT System Architecture for Sensor and Actuator Networks.Sensors (Basel, Switzerland) · 2022Article
- Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario.Sensors (Basel, Switzerland) · 2022Article
- Video Slice: Image Compression and Transmission for Agricultural Systems.Sensors (Basel, Switzerland) · 2021Article
- Swarm-Intelligence-Centric Routing Algorithm for Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2020Article
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
Crop diseases cannot be accurately predicted by merely analyzing individual disease causes. Only through construction of a comprehensive analysis system can users be provided with predictions of highly probable diseases. In this study, cloud-based technology capable of handling the collection, analysis, and prediction of agricultural environment information in one common platform was developed. The proposed Farm as a Service (FaaS) integrated system supports high-level application services by operating and monitoring farms as well as managing associated devices, data, and models. This system registers, connects, and manages Internet of Things (IoT) devices and analyzes environmental and growth information. In addition, the IoT-Hub network model was constructed in this study. This model supports efficient data transfer for each IoT device as well as communication for non-standard products, and exhibits high communication reliability even in poor communication environments. Thus, IoT-Hub ensures the stability of technology specialized for agricultural environments. The integrated agriculture-specialized FaaS system implements specific systems at different levels. The proposed system was verified through design and analysis of a strawberry infection prediction system, which was compared with other infection models.
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.