Recent Advances in Sensors and Machine Learning Methods in IoT for Automatic Detection and Classification
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 612
Special Issue Editors
Interests: sensors; electronics engineering; instrumentation; IoT
Interests: breath analysis; electronic nose; biosensors; VOCs; cancer detection
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; deep learning; artificial intelligence; data science; computer science
Special Issue Information
Dear Colleagues,
Sensors serve as the eyes and ears for a computing infrastructure that analyzes and responds to the information gathered from the sensors. They connect the physical world to the logical world by measuring things such as pressure, force, acceleration, temperature, chemical, humidity, level, proximity, touch, and optical properties.
However, with recent advancements in communication and sensor fabrication technology, sensors also play a pivotal role in the internet of things (IoT), allowing for the creation of an ecosystem for collecting and processing data about a specific environment, allowing it to be monitored, managed, and controlled more easily and efficiently.
Additionally, the integration of artificial intelligence (AI)-based data analytics via machine learning or deep learning approaches, which provides the automatic detection and classification of the sensor data, is further enhanced by IoT infrastructures connected with various sensors. In the near future, such data can be made available to the cloud server.
This Special Issue showcases the most recent and upcoming advancements in sensor development as well as the use of machine learning techniques with sensor data to evaluate the physical world by taking into account the fact that sensors are integrated with IoT and AI. As a result, we invite papers on a variety of sensors and machine learning research for aided systems, including but not limited to: sensors, sensor data applications, artificial intelligence, machine learning, deep learning, IoT, data analytics, and predictive analytics.
Dr. Md Mehedi Masud
Dr. Manohar Prasad Bhandari
Dr. Tahir Mehmood
Guest Editors
Manuscript Submission Information
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Keywords
- sensors
- sensor data applications
- artificial intelligence
- machine learning
- deep learning
- IoT
- data analytics
- predictive analytics
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