Activity Recognition in Smart Environments

Dear Colleagues,

The rapid development of smart environments is closely linked to the widespread adoption of modern technologies, especially with the rise of “Embodied Intelligence”, which has drawn increased attention to human-centered intelligent applications. This is particularly evident in areas such as smart homes, smart offices, intelligent public spaces, and smart healthcare facilities. Through these systems, people can more efficiently utilize their environments to achieve personalized interactions and experiences. Activity recognition technology is vital to these systems, relying on the deep integration of sensor networks, data fusion, and machine learning technologies.

The Internet of Things (IoT), big data analytics, and cloud computing are essential for the widespread application of activity recognition systems, enabling real-time behavior monitoring and future action prediction to provide personalized and seamless services. These systems are already widely used in healthcare, elderly care, and rehabilitation, where they help optimize care plans by tracking patient or elderly behavior. At the same time, privacy and ethical considerations are crucial, especially in sensitive environments like healthcare, where balancing user privacy with the advantages of intelligent systems is a key focus for both academia and industry. Therefore, future research should not only advance technological innovation but also ensure that privacy protection is effectively integrated into the system development process.

Our Special Issue will explore the core areas of activity recognition in smart environments by focusing on key technologies such as sensor integration, machine learning, and ambient intelligence. By leveraging diverse sensing modalities, including wearable devices, motion sensors, and environmental detectors, activity recognition systems can provide a comprehensive understanding of human behavior and interaction within intelligent spaces. Advanced algorithms in AI and data fusion are essential for processing these multi-source data streams, enabling human–computer interaction, real-time monitoring, and personalized adaptation in smart environments. Additionally, the integration of these technologies with the Internet of Things (IoT) and cloud computing facilitates seamless data communication, fostering smarter, more responsive environments.

For this Special Issue, we invite submissions that tackle the technical and ethical challenges of activity recognition in smart environments. Topics of interest include, but are not limited to, the following:

• Machine Learning and AI for Activity Recognition: Innovative algorithms and models designed to improve the accuracy and efficiency of activity recognition systems;
• Sensor Networks and Data Fusion: Methods for integrating data from diverse sensors to create comprehensive activity profiles;
• Human–Computer Interaction: Studies on how activity recognition can enhance user interaction with smart environments;
• Ambient Intelligence: Research on the integration of activity recognition into ambient intelligence systems for responsive and adaptive environments;
• Wearable Devices: Advances in the use of wearable technology for real-time activity monitoring and recognition;
• Ubiquitous Computing: Exploration of pervasive computing systems and their role in supporting activity recognition;
• Applications in Healthcare and Assisted Living: Case studies and applications that demonstrate the impact of activity recognition in healthcare, elderly care, and rehabilitation;
• Security and Privacy in Smart Environments: Addressing the challenges related to and solutions for maintaining security and privacy in activity recognition systems;
• Real-World Implementations: Practical examples and case studies of activity recognition systems deployed in smart homes, offices, or public spaces;
• Challenges and Future Directions: Critical reviews and discussions on current challenges and potential future developments in the field.

We look forward to both receiving your contributions to this Special Issue and the enriching discussions that will emerge from this collective effort.

Dr. Qimeng Li
Dr. Wen Qi
Dr. Fangmin Sun
Dr. Raffaele Gravina
Guest Editors

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• activity recognition
• smart environments
• machine learning
• human–computer interaction
• ubiquitous computing
• context-aware systems