ReviewSensors (Basel, Switzerland)2025
The IoT and AI in Agriculture: The Time Is Now-A Systematic Review of Smart Sensing Technologies.
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 22 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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Sustainable smart sensing and AI-driven platforms for real-time detection and monitoring of mycotoxins across the food supply chain.Mycotoxin research · 2026Pooled it
- Mechanisms and Research Progress of Phosphate-Solubilizing Microorganisms in Promoting Sustainable Crop Production.Microorganisms · 2026Review
- Artificial intelligence-driven advancements in agricultural biotechnology.Journal, genetic engineering & biotechnology · 2026Review
- Sensor-Based Pasture Quality Monitoring: Supporting Grazing Management and Preventing Nutritional and Metabolic Disorders in Ruminants.Sensors (Basel, Switzerland) · 2026Review
- From detection to action: artificial intelligence in integrated pest and invasive plant management.Advanced biotechnology · 2026Review
- AI and IoT in Sugar Beet Systems: A Review of Monitoring, VOC Sensing, and Post-Harvest Applications.Sensors (Basel, Switzerland) · 2026Review
- Probabilistic Communication-State Inference for Agricultural Robots Under Wireless Degradation.Sensors (Basel, Switzerland) · 2026Article
- Advancing occupational and environmental safety in greenhouse agriculture: an extended elaboration likelihood model of safety technology adoption.Scientific reports · 2026Article
- Embodied Intelligence for Soil Health toward Sustainable Smart Agriculture: Sensing the Soil with Flexible Geotextiles Sensors.Global challenges (Hoboken, NJ) · 2026Review
- Magnetometry for Agriculture and Animal Systems: From Classical Sensors to Quantum-Enabled Biosensing.Biosensors · 2026Review
- Deep learning and IoT-based framework for sesame plant identification and weed detection.Scientific reports · 2026Article
- RiceBlock-0.2: secured precision rice farming framework using blockchain technology.Scientific reports · 2026Article
- A Three-Year Multimodal Holistic Dataset For Horticultural Tomato Cultivation.Scientific data · 2026Article
- Traceability and Anti-Counterfeiting in Agri-Food Supply Chains: A Review of RFID, IoT, Blockchain, and AI Technologies.Sensors (Basel, Switzerland) · 2026Review
- Artificial Intelligence (AI) in Detection of Abiotic Stress in Plants: A Review.Sensors (Basel, Switzerland) · 2026Review
- Precision Farming with Smart Sensors: Current State, Challenges and Future Outlook.Sensors (Basel, Switzerland) · 2026Review
- AI-enabled smart farming framework for sustainable date palm cultivation in arid regions using machine learning and IoT integration.Scientific reports · 2026Article
- Artificial intelligence in soil microbiome-driven agriculture: from practical limits to a translational roadmap.Frontiers in microbiomes · 2026Review
- Optimized YOLO architectures for efficient Kiwi detection in precision agriculture on embedded systems.Scientific reports · 2025Article
- Review
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 the Internet of Things (IoT) and artificial intelligence (AI) has reshaped modern agriculture by enabling precision farming, real-time monitoring, and data-driven decision-making. This systematic review, conducted in accordance with the PRISMA methodology, provides a comprehensive overview of recent advancements in smart sensing technologies for arable crops and grasslands. We analyzed the peer-reviewed literature published between 2020 and 2024, focusing on the adoption of IoT-based sensor networks and AI-driven analytics across various agricultural applications. The findings reveal a significant increase in research output, particularly in the use of optical, acoustic, electromagnetic, and soil sensors, alongside machine learning models such as SVMs, CNNs, and random forests for optimizing irrigation, fertilization, and pest management strategies. However, this review also identifies critical challenges, including high infrastructure costs, limited interoperability, connectivity constraints in rural areas, and ethical concerns regarding transparency and data privacy. To address these barriers, recent innovations have emphasized the potential of Edge AI for local inference, blockchain systems for decentralized data governance, and autonomous platforms for field-level automation. Moreover, policy interventions are needed to ensure fair data ownership, cybersecurity, and equitable access to smart farming tools, especially in developing regions. This review is the first to systematically examine AI-integrated sensing technologies with an exclusive focus on arable crops and grasslands, offering an in-depth synthesis of both technological progress and real-world implementation gaps.
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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.