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Advanced Sensor-Based Sorting & Control: Perspectives and Potentials for Securing Valuable Raw Materials
This special issue belongs to the section “Environmental Sensing“.
Special Issue Information
Dear Colleagues,
In recent years, the accelerating pace of digitalization has enabled the broader exploitation of both existing and novel data streams. This development has driven innovations in plant optimization, sensor-based sorting and the processing of material flows across various applications in the mining and recycling industry. The integration of machine learning and advanced sensing technologies, encompassing material monitoring as well as plant-wide monitoring, control and optimization, has greatly improved the detection, classification, and monitoring of material flows in real time and thus expanded the possibilities for process control, enhancing efficiency in both primary and secondary raw material sectors.
This Special Issue aims to address a crucial challenge for our generation and those to come: the mindful and sustainable utilization of finite resources within planetary boundaries. This is particularly important for the mining and recycling sectors, where sensor technologies and data-driven methods have catalyzed significant advancements over the past decades.
This Special Issue is closely linked to the 11th expert conference titled Sensor-Based Sorting & Control, which will take place from March 17 to 18, 2026, in Aachen. Representatives from industry and academia will submit abstracts and present the latest developments and applications in automated separation and sensor-based sorting, as well as innovative approaches for material monitoring and process optimization and control within the entire process chains of recycling and mineral processing.
Selected contributions from the conference will have the opportunity to be published as full papers in this Special Issue. In addition, this Special Issue also welcomes regular submissions that explore emerging technologies and their applications. Potential topics include, but are not limited to, the following:
- Advancements in multi-sensor systems;
- Improvements in single-particle detection;
- Methods of data processing and particle analysis;
- Deployment of sensors for online monitoring and process control;
- Utilization of data and information for increased plant efficiency;
- Optimization of peripheral processes.
Prof. Dr. Tobias Vraetz
Prof. Dr. Kathrin Greiff
Guest Editors
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-blind 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
- sensor-based sorting
- process control
- hyperspectral imaging
- particle analysis
- machine learning
- multi-sensor systems
- real-time monitoring
- recycling of waste streams
- light weight packaging waste
- metal waste
- construction and demolition waste
- paper and wood waste
- raw materials
- mineral processing
- mine optimization
- advanced analytics in mineral processing

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