Remote Sensing and IoT for Smart Learning Environments
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 24958
Interests: Internet of Things; big data analytics; machine learning; health data analytics
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; soft computing techniques; natural language processing; language acquisition and machine learning algorithms
Interests: blockchain technology; cryptography; big data; data mining; social networks; security and privacy; anonymity; graphs
Special Issues, Collections and Topics in MDPI journals
The educational industry has been continuously adapting to technological advancement since its inception. Access to digital space has increased huge opportunities for the learning world. Conservative models in learning have seen both success and failure over the years. Specialized approaches with personalized factors have become one of the important parts of the learning curve for students with the implementation of smart learning environment. There is a variety of smart learning cultures prevalent in the environment, as every institution or organization has their own approaches, procedures, techniques, and processes in the creation of their learning environment. Since all students have different abilities, inculcating smart learning methods may bring out hidden abilities. The failure in every learning system is the focus of human centered challenges. To overcome these challenges, more accurately advanced sensing technologies can be helpful. Identifying the various changes in the environment has become an easy way by using remote sensors
Advanced technologies like remote sensing and the Internet of Things (IoT) will be perfect for controlling various activities in a smart learning environment. Utilizing smart devices such as Smart Television, computing devices, mobile device apps, various tracking sensors, and many more in the learning environment can be used in the administering of smart learning. Also, integrating remote sensing and IoT can provide various opportunities for learners and teachers in conducting research and training to channel knowledge in schools, colleges, universities, or organizations. Moreover, enhancing educational innovations in physical spaces shall create a faster and more perfect learning curve. In addition, remote technologies can digitally connect academicians, teachers, counselors, and students in a single platform. Here, the consideration of implementing security and safety measures in these remote sensing technologies also acts as an added advantage of creating a quality learning environment. Currently, the smart learning environment is being equipped with the application of various sensing technologies like posture learning, emotion recognition, context-aware learning, augmented reality, ambient learning, etc.
However, concentrating on the areas of planning, framework, protocol, and algorithm for smart sensing can increase the high performance of hardware platform or software framework. The main aim of this Special Issue is to invite scholars, academicians, and professionals to submit their research works, ideas, and implementations related to remote sensing and IoT platforms for Smart Learning Environments
The scope of this Special Issue includes but is not limited to the following:
- Creating a ubiquitous learning environment using remote sensing and IoT
- Sensor data processing and integration for Smart Learning Environments
- Need of energy efficient protocols for remote sensing and IoT in smart environments
- Efficient network protocols for smart objects based on communication platforms
- A design-based thinking to adapt a framework for Smart Learning Environments
- Best practices in implementation of smart learning environments
- Need of smart sensing technologies for learning environments
- Remote sensing and IoT based pedagogical tools for supporting smart learning
- A study on policy-related issues for remote sensing and IoT based learning platforms
- Architectural frameworks for IoT based Smart Learning Environments
- Advanced sensor technologies used in learning environments: an overview
- Autonomous sensor networks for smart learning environments
Dr. Priyan Malarvizhi Kumar
Dr. Hari Mohan Pandey
Dr. Gautam Srivastava
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.