Evidence map›Paper›PMID 41228974›Full record

ReviewSensors (Basel, Switzerland)2025

Secure and Intelligent Low-Altitude Infrastructures: Synergistic Integration of IoT Networks, AI Decision-Making and Blockchain Trust Mechanisms.

Yuwen Ye, Xirun Min, Xiangwen Liu, Xiangyi Chen, Kefan Cao, S M Ruhul Kabir Howlader, Xiao Chen

Abstract readReview
In one paragraph

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, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yuwen YeSchool of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0009-0007-2249-475X
Xirun MinSchool of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0009-0004-8623-3733
Xiangwen LiuSchool of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China.
Xiangyi ChenSchool of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China.
Kefan CaoSchool of Computing, Newcastle University, Newcastle NE1 7RU, UK.ORCID 0009-0003-9094-9008
S M Ruhul Kabir HowladerSchool of Computing Science and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0002-1232-2387
Xiao ChenSchool of Computing Science and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0002-3290-507X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The low-altitude economy (LAE), encompassing urban air mobility, drone logistics and sub 3000 m aerial surveillance, demands secure, intelligent infrastructures to manage increasingly complex, multi-stakeholder operations. This survey evaluates the integration of Internet of Things (IoT) networks, artificial intelligence (AI) decision-making and blockchain trust mechanisms as foundational enablers for next-generation LAE ecosystems. IoT sensor arrays deployed at ground stations, unmanned aerial vehicles (UAVs) and vertiports form a real-time data fabric that records variables from air traffic density to environmental parameters. These continuous data streams empower AI models ranging from predictive analytics and computer vision (CV) to multi-agent reinforcement learning (MARL) and large language model (LLM) reasoning to optimize flight paths, identify anomalies and coordinate swarm behaviors autonomously. In parallel, blockchain architectures furnish immutable audit trails for regulatory compliance, support secure device authentication via decentralized identifiers (DIDs) and automate contractual exchanges for services such as airspace leasing or payload delivery. By examining current research and practical deployments, this review demonstrates how the synergistic application of IoT, AI and blockchain can bolster operational efficiency, resilience and trustworthiness across the LAE landscape.

Indexed as

artificial intelligenceblockchainInternet of Thingslow-altitude economyunmanned aerial vehicles

Identifiers

PMID41228974
PMCPMC12609838

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.