The sensing capabilities of the infrastructure and devices surrounding our daily lives are improving and becoming more affordable by the day. Office buildings, transport infrastructure, and homes are increasingly instrumented with smart devices that can detect human presence and environmental conditions. In this month’s theme, we focus on the topic of pervasive sensing.
While this trend toward increasingly instrumented environments has continued for many years, there has been a parallel and much more rapidly growing trend in the deployment of mobile devices. For instance, mobile phones now include a variety of sensors, such as accelerometers, magnetometers, light sensors, GPS, microphones, and cameras, as well as wireless interfaces such as cellular, Bluetooth, and WiFi. Morgan Stanley Research estimates sales of smartphones will exceed those of PCs in 2012. As of February 2011, Gartner expected US sales of smartphones to grow from 67 million in 2010 to 95 million in 2011, making this the highest-selling consumer electronic device category.
The ubiquitous nature of the emerging sensing infrastructure opens the door to a plethora of new applications, ranging from energy and environmental monitoring through marketing and supply-process monitoring to human behavior, well-being, health, and social-interaction studies. Sensor data provides us with new capabilities — for example, new ways of supporting context awareness, activity recognition, and disaster management.
In this month’s theme, we provide an introduction to the field of pervasive sensing. We’ve drawn articles from a range of IEEE Computer Society publications, reflecting the widespread interest in sensing. These articles aren’t intended to be a tutorial on pervasive sensing — rather, as a collection, they provide an overview of the types of activities that are under way in this important field of research.
In addition to the articles listed below, we encourage readers to view the October–December 2011 issue of IEEE Pervasive Computing magazine on Large-Scale Opportunistic Sensing. This special issue includes numerous articles in this area, as well as a works-in-progress department that provides a snapshot of new, cutting-edge projects.
The first article, “Deploying a Wireless Sensor Network on an Active Volcano,” presents a seminal application of a fixed sensor network in environmental monitoring — a sensor network to support volcanic studies that required addressing the high data rates and high data fidelity these studies demand. Many other deployments of sensor networks for monitoring a range of natural resources, including animal habitats, followed this work.
In “The Rise of People-Centric Sensing,” the authors argue that the miniaturization of sensing devices has advanced the development of human-centric applications, where sensors on mobile phones work together with fixed sensors in the environment. The article also discusses the sharing of data among friends and communities, as well as opportunistic sharing of the sensing tasks.
“The Mobile Sensing Platform: An Embedded Activity Recognition System” introduces a mobile sensing platform that consists of a small-form-factor wearable device designed for embedded activity recognition. The platform aims broadly to support context-aware ubiquitous computing applications. The article reports on several real-world deployments and user studies, using the results to improve the hardware, software design, and activity-recognition algorithms.
While mobile sensing is an important and topical area of research, major developments in fixed sensing are also under way. As an example, we have selected “Disaggregated End-Use Energy Sensing for the Smart Grid,” which surveys existing and emerging disaggregation techniques for energy-consumption data. The article also highlights signal features that can be used to sense disaggregated data in an easily installed and cost-effective manner. The ultimate goal is to sense uses of energy to provide feedback at the individual device or appliance level.
Finally, “From Context Awareness to Socially Aware Computing” discusses how the new generation of smartphones will use sensor data to facilitate real-world applications involving more complex activity recognition. This will help with the move toward next-opportunistic recognition configurations and large-scale ensembles of networked subsystems interacting with user communities.
We hope you enjoy this month’s theme — leave a comment and let us know what you think.
Cecilia Mascolo is a Reader in Mobile Systems in the Computer Laboratory, University of Cambridge. More information about Cecilia is available at www.cl.cam.ac.uk/~cm542.
Nigel Davies is a professor of computer science at Lancaster University and editor in chief of IEEE Pervasive Computingmagazine.
