Internet of Remote Things for Remote Sensing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: closed (21 September 2021) | Viewed by 22915
Special Issue Editors
Interests: wireless communications; aerospace; IoT communications; CPS; smart farming
Special Issues, Collections and Topics in MDPI journals
Interests: wireless networks; satellite communication; wireless communications; Internet of Things; artificial intelligence; neural networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Internet of Things (IoT) is a key paradigm in Industry 4.0 scenarios. Beyond those, the potential shown by the use of IoT solutions is significant also in a plethora of different application fields. Recently, the use of IoT has been proposed also in satellite-based scenarios, giving birth to the so-called Internet of Remote Things (IoRT). Thus, the combination of remote sensing, as enabled by aerospace solutions such as satellites and unmanned aerial vehicles (UAVs) that are proving increasingly indispensable for remote sensing, and IoT sensing on the ground can provide a new and powerful tool to make services more profitable and competitive. Thus, it is essential to deepen the investigation on the potential provided by joint solutions, and by long-range solutions (such as LoRa that is consolidating as a one-way solution from ground to space). IoRT can be further enhanced by techniques like distributed and federated learning for object recognition and anomaly detection. Typical scenarios are agricultural, maritime, monitoring, and surveillance.
This Special Issue seeks to cover the state-of-the-art in IoRT solutions in different application fields. Specific topics include but are not limited to:
- Satellite solutions for remote sensing as complemented by terrestrial sensing;
- Aerial solutions, such as flying ad-hoc networks (FANETs), for remote sensing as complemented by terrestrial sensing;
- Space and ground integrated networks for sensing purposes;
- IoT and IoRT-based architectures for remote sensing;
- Agricultural, maritime, monitoring, surveillance, and other scenarios;
- Development, integration, and testing of new and emerging solutions, paradigms, and architectures for IoT and IoRT;
- Federated and distributed learning for object recognition and anomaly detection;
- Real testbeds.
Dr. Manlio Bacco
Dr. Alberto Gotta
Dr. Pietro Cassara
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Remote Sensing 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 2700 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
- Internet of Things
- satellite
- UAV
- system architecture
- system integration
- federated learning
- distributed learning
- object recognition
- testbed
- space information networks
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