AI-Enhanced Sensor Data Integration and Processing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 15 October 2026 | Viewed by 3370
Editor
Special Issue Information
Dear Colleagues,
The rapid proliferation of high-resolution sensor observations presents unprecedented opportunities for environmental and oceanic sciences, while simultaneously imposing greater computational demands on numerical modeling. This Special Issue focuses on the critical challenge of efficiently assimilating diverse sensor data into dynamical models under acceptable computational costs. We invite contributions that explore AI-driven approaches to enhance data assimilation processes, addressing fundamental bottlenecks in computational efficiency and the mismatch between model physics and observational variables. We particularly focus on addressing two fundamental challenges:
- Computational bottlenecks
Sensor data assimilation requires multiple runs of PDE solvers in each optimization iteration. The high flux of sensor observations, e.g., high-resolution satellite data, demands numerical 1 models to generate comparable volumes of state variables for correspondence, making forward computation the primary cost source.
- Observation-to-state variable mapping
Sensor measurements Z(x, t) do not directly correspond to the state variables U(x, t) solved by numerical models. Creating effective linkages that allow observational data to constrain and inform the physical system dynamics requires sophisticated mappings that current empirical approaches handle inadequately, limiting assimilation effectiveness.
We invite researchers to contribute innovative solutions that leverage artificial intelligence to bridge these gaps and advance state-of-the-art technologies in environmental data assimilation.
Dr. Jun Li
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- machine learning surrogate models for accelerating forward operators
- neural network-based observation operators for sensor data
- deep learning approaches for variational data assimilation
- AI-driven ensemble data assimilation techniques
- hybrid physics-AI models for environmental prediction
- multi-sensor fusion using AI techniques
- real-time processing of high-resolution sensor streams
- quality control and bias correction of sensor observations
- uncertainty quantification in sensor data assimilation
- adaptive sensor placement and observation strategies
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
