Recent years have seen an explosion in the use of data science and AI as a central tenant in numerous computing applications, products, research, and innovation. Examples of the success of data science abound—applying new machine-learning techniques to problems such as vision and speech recognition and translation has achieved commonplace levels of performance that would have seemed impossible a few years ago.
In parallel, developments in pervasive computing increasingly enable us to instrument our physical environment with complex sensors and actuators and create an interconnected world that generates huge volumes of data. The importance of these trends can be seen in the growing momentum of exemplars such as the Internet of Things (IoT), smart environments, and smart cities. These applications demand a new focus on how we capture, process, and use data in pervasive environments.
Beyond the hype, it is clear that our world is becoming increasingly datacentric, in which both physical and electronic services depend on the collection, analysis, and application of large volumes of heterogeneous data.
This special issue focuses on work at the intersection of data science/AI and pervasive computing. In particular, we solicit contributions that focus on the following aspects of pervasive data science:
- New hardware and software to support data collection in pervasive environments.
- Ownership, trust, and provenance of pervasive data.
- Privacy and consent in highly instrumented pervasive environments.
- New techniques for data processing and inference in pervasive and IoT environments.
- Adaptation and optimization of data processing algorithms for use on pervasive and IoT devices.
- The use of data science and AI to support ubiquitous computing in challenges such as localization and activity recognition.
- Decision making and actuation based on data from pervasive and IoT environments.
- Application areas for data science and AI in pervasive computing and the IoT—for example, autonomous vehicles, augmented cognition, smart cities, and digital health.
- Using pervasive data science and AI in robotics.
For examples of additional challenges in the field, see Nigel Davies and Sarah Clinch, “Pervasive Data Science,” IEEE Pervasive Computing, vol. 16, no. 3, 2017, pp. 50–58; doi.org/10.1109/MPRV.2017.2940956.
The guest editors invite original and high-quality submissions addressing all aspects of this field, as long as the connection to pervasive computing and/or the IoT is clear and central to the paper. Review or summary articles—for example, critical evaluations of the state of the art, or an insightful analysis of established and upcoming technologies—may be accepted if they demonstrate academic rigor and relevance.
- Nigel Davies, Lancaster University
- Nic Lane, Oxford University
- Mirco Musolesi, University College London
For more information, contact the guest editors at email@example.com.
Articles submitted to IEEE Pervasive Computing should not exceed 6,000 words, including all text, the abstract, keywords, bibliography, biographies, and table text. The word count should include 250 words for each table and figure. References should be limited to at most 15 citations (30 for survey papers).
Note that the magazine always welcomes submissions into its regular queue that cover the role of computing in the physical world—as characterized by visions such as the IoT and ubiquitous computing. Topics of interest include hardware design, sensor networks, mobile systems, human–computer interaction, industrial design, machine learning, data science, and societal issues such as privacy and ethics. Simply select the “Regular” option when submitting at https://mc.manuscriptcentral.com/pc-cs (no need for prior abstract by email).