Artificial Intelligence and Deep Learning for Smart Sensor and Smart Mobility
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 September 2025 | Viewed by 190
Special Issue Editors
Interests: radar signal processing; non-cooperative target recognition; machine learning and artificial intelligence
Interests: artificial intelligence; machine learning and deep learning; embedded system; computer engineering and education
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) and Deep Learning (DL) play a crucial role in smart sensors and smart mobility due to their ability to process large volumes of data, improve decision-making, and enhance automation.
Smart sensors collect vast amounts of real-time data, while AI/DL efficiently make sense of these data.
- Data Processing and Analysis: AI can analyze sensor data in real time to detect patterns, anomalies, or predict failures.
- Predictive Maintenance: Deep learning models can predict sensor failures, reducing downtime and improving reliability.
- Edge AI for Real-time Processing: AI enables on-device processing, reducing the need for cloud communication and improving speed.
- Multimodal Data Fusion: AI can integrate data from multiple sensors (e.g., vision, LiDAR, radar) for better decision-making.
Smart mobility relies on AI and DL to enhance transportation systems, reduce congestion, and improve safety.
- Autonomous Vehicles: Deep learning models process sensor data (LiDAR, cameras, radar) for perception, path planning, and decision-making.
- Traffic Optimization: AI-based models analyze traffic patterns to optimize signal timings and reduce congestion.
- Accident Prevention: AI predicts hazardous situations, alerting drivers or autonomous systems to take preventive action.
- Personalized Mobility: AI enables intelligent route planning and ride-sharing services based on real-time demand and user preferences.
- Vehicle-to-Everything (V2X) Communication: AI facilitates efficient communication between vehicles, infrastructure, and pedestrians for improved safety.
We invite you to contribute to this Special Issue, which is dedicated to advancing research on artificial intelligence and deep learning in smart sensor and smart mobility.
Dr. In-Sik Choi
Dr. Ji-Hoon Bae
Dr. Min-Suk Kim
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence (AI)
- deep learning (DL)
- machine learning (ML)
- autonomous vehicles (AV)
- reinforcement learning (RL)
- sensor fusion
- IoT sensors
- smart sensor networks
- intelligent transportation systems (ITSs)
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