Wireless Sensor Networks (WSN)

Cyber Physical Systems (CPS)

Internet of Things (IOT)

Smart Cities

Smart and Connected Health and Wellness


John Stankovic, BP America Professor, Director of the Link Lab




Current Post Docs


Current Graduate Students

Meiyi Ma
Winston Chen
Sirat Samyoun
Sam Sun
Lahiru Nuwan
Ashley Gao
Arif Rahman

Research Partners Outside UVA

Karen Rose, Ohio State
Kristina Gordon, Univ. of Tennessee
Shan Lin, StonyBrook
John Lach, GWU
Donna Spruijt-Metz, USC
Kayla de la Haye, USC
Hengchang Liu, Univ. of Electronic Science and Technology, China
Niki Trigoni, Oxford
Gaia Maselli, Univ. of Rome
Desheng Zhang, Rutgers

It is now possible to develop large numbers of small smart components that combine computing power, wireless communication capabilities, and specialized sensors and actuators. These components or nodes may be deployed in thousands to achieve a common mission. They may be used to monitor poorly accessible or dangerous environments such as the ocean floor, neighborhoods of volcanic activities, hostile territories (e.g., behind enemy lines), disaster areas, and nuclearly active fields. They may also be deployed to accomplish interactive tasks such as finding and detonating enemy mines, looking for survivors of natural disasters, or containing and isolating oil spills to protect a nearby coastline. These wireless sensor devices are also useful for environmental monitoring, medical applications and smart homes, buildings, or cities. The new technology creates a different set of challenges arising from the fact that:

Nodes are embedded into a geographic landscape and interact tightly with the physical environment in real-time.
Nodes are smaller and less reliable than traditional network routers.
Nodes generate (and possibly store) data from sensors unlike traditional routers.
Nodes operate under severe constraints on power, computation, bandwidth and memory.
Nodes may be mobile.
Nodes may be subject to security attacks.

Our past work included developing MAC and routing layer solutions, group management protocols based on novel semantics, analysis and implementation techniques for achieving aggregate behavior, novel data services protocols including sensor net querying capabilities, development of a sophisticated event service for WSNs, protocols for power management, protocols for computer security, and developing new paradigms for sensor net programming. We worked with a testbed of MICA and XSM motes. We have built and evaluated a 203 node system at Fort MacDill AFB and Avon Park called VigilNet. This system was used for detection, tracking and classification with power management capabilities that extends the lifetime of the system significantly. We also extended the basic system and implemented a novel tripwire power management system. We presented many demonstrations of the improved system. Our research partners included CMU and the University of Illinois.

In the past we also completed a testbed for an environmental science application called Luster that mimics a system that requires both periodic monitoring and event based actions. The system measured the affect of sunlight on under brush growth. On this project we collaborated with the Environmental Sciences department at UVA. The system was deployed on the Eastern Shore of Virginia where various environmental studies have been ongong since the early 1980s. See also Luster and SeeMote.

Our more recent work is in smart and connected health and smart cities areas. In the smart health arena we built a testbed to emulate WSNs in assisted living facilities. This system is called AlarmNet and extended in a systems called Empath. We worked with the UVA medical school and Harvard. See also Wireless Networking for Assisted Living and Other Medical Applications. See also Hardware We Developed for Medical Applications. We also have developed many solutions based on wearables.

Various projects included: (i) a complete redesign of body sensor networks from silicon to the user (joint with the University of Michigan), (ii) a BSN for fall detetcion based on a context free grammar and area context sensors, (iii) a home health care system for early detection of depression, (iv) the Musical Heart smartphone system for controlling heart rate with music, (v) a general sound engine and app development environment (API) for smartphones, (vi) robust activity recognition that accounts for overlapped activities and missing sensor readings, (vii) runtime assurance techniques, (viii) use of multiple classifiers to detect faults and minimize the number of repair dispatches and nodes repaired, (ix) a system capable of inferring water events in a home, (x) various medical applications using the Kinect system, (xi) classifiers for detetcing mood from voice at a distance, (xii) a medical reminder system using a smart watch, and (xiii) detecting eating events using a smart watch in the wild. Papers below cover many aspects of these projects.

All this material is based, in part, upon work supported by the National Science Foundation under Grants No. CNS-0614870, CNS-0614773, CNS-0626616, and CNS-0626632.

Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

Best Paper Awards and Runner Ups


Other Awards

  • Entrepreneurial Vision Award, 4th Annual S.E.E.D. Spirit of Entrepreneurship and Enterprise Development - Venture Forum, Santa Barbara, Calif., Team Leader, Johns Hopkins, Team Members, Harvard and UVA.
  • Award, 2nd Best Emerging Company Investment Opportunity, 4th Annual S.E.E.D. Spirit of Entrepreneurship and Enterprise Development - Venture Forum, Santa Barbara, Calif., Team Leader, Johns Hopkins, Team Members, Harvard and UVA.
  • Best Demo Award, ACM Sensys, Nov. 2020.


Publicity (Partial List)

Selected Publications