ABSTRACT
In this paper we introduce the Spatio Temporal Filtering Language (STFL), which is a language framework that aims to provide the primitives for easily defining rules and sequences of rules and constraints. These sequences of rules can be used to convert low-level streams of sensor data into higher-level semantics and provide triggers for actuation. Among others STFL provides support for heterogeneous types of sensors, composability and code reusability. Special emphasis is given on the support of different categories of users by providing different types of interfaces spanning from a natural-like language aiming at end-users to a regular scripting language aiming at system developers. The expressiveness and power of STFL is presented through an assisted living scenario.
- D. Abadi, Y. Ahmad, M. Balazinska, U. Cetintemel, M. Cherniack, J. Hwang, W. Lindner, A. Maskey, A. Rasin, E. Ryvkina, et al. The Design of the Borealis Stream Processing Engine. In Second Biennial Conference on Innovative Data Systems Research (CIDR 2005), Asilomar, CA, January, 2005.Google Scholar
- R. Balani, A. Singhania, S. Han, R. Rengaswamy, and M. B. Srivastava. Vire: Virtual reconfiguration framework for embedded processing in distributed image sensors, January - April 2007. NESL, UCLA Technical Report TR-UCLA-NESL-200701-01.Google Scholar
- A. Bamis, D. Lymberopoulos, T. Teixeira, and A. Savvides. Towards precision monitoring of elders for providing assistive services. In PETRA '08: Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments, pages 1--8, New York, NY, USA, 2008. ACM. Google ScholarDigital Library
- D. Lymberopoulos, A. Bamis, and A. Savvides. Extracting spatiotemporal human activity patterns in assisted living using a home sensor network. In PETRA '08: Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments, pages 1--8, New York, NY, USA, 2008. ACM. Google ScholarDigital Library
- D. Lymberopoulos, A. Bamis, and A. Savvides. A methodology for extracting temporal properties from sensor network data streams. In Proceedings of the 7th ACM/Usenix International Conference on Mobile Systems, Applications and Services (MobiSys '09), 2009. Google ScholarDigital Library
- D. Lymberopoulos, T. Teixeira, and A. Savvides. Macroscopic human behavior interpretation using distributed imager and other sensors. Proceedings of the IEEE, 96(10):1657--1677, Oct. 2008.Google ScholarCross Ref
- S. Madden, M. Franklin, J. Hellerstein, and W. Hong. TinyDB: an acquisitional query processing system for sensor networks. ACM Transactions on Database Systems (TODS), 30(1):122--173, 2005. Google ScholarDigital Library
- G. Mainland, M. Welsh, and G. Morrisett. Flask: A language for data-driven sensor network programs, May 2006. Harvard University Technical Report TR-13-06.Google Scholar
- R. Newton, G. Morrisett, and M. Welsh. The regiment macroprogramming system. In Proceedings of the 6th international conference on Information processing in sensor networks, pages 489--498. ACM Press New York, NY, USA, 2007. Google ScholarDigital Library
- H. Pigot, A. Mayers, and S. Giroux. The intelligent habitat and everyday life activity support. In Proc. of the 5th International conference on Simulations in Biomedicine, April, pages 2--4.Google Scholar
- R. Sugihara and R. Gupta. Programming models for sensor networks: A survey, January 2007. UCSD Technical Report CS2007-0881.Google Scholar
- M. Welsh and G. Mainland. Programming sensor networks using abstract regions. In First USENIX/ACM Symposium on Networked Systems Design and Implementation (NSDI '04), March 2004. Google ScholarDigital Library
- K. Whitehouse, C. Sharp, E. Brewer, and D. Culler. Hood: a neighborhood abstraction for sensor networks. In MobiSys '04: Proceedings of the 2nd international conference on Mobile systems, applications, and services, pages 99--110, New York, NY, USA, 2004. ACM. Google ScholarDigital Library
- K. Whitehouse, F. Zhao, and J. Liu. Semantic Streams: A Framework for Composable Semantic Interpretation of Sensor Data. LECTURE NOTES IN COMPUTER SCIENCE, 3868:5, 2006. Google ScholarDigital Library
- Y. Yao and J. Gehrke. The Cougar Approach to In-Network Query Processing in Sensor Networks. SIGMOD RECORD, 31(3):9--18, 2002. Google ScholarDigital Library
- A. S. Yu, A. Bamis, D. Lymberopoulos, T. Teixeira, and A. Savvides. Personalized awareness and safety with mobile phones as sources and sinks. In International Workshop on Urban, Community, and Social Applications of Networked Sensing Systems (UrbanSense08), 2008.Google Scholar
Index Terms
- STFL: a spatio temporal filtering language with applications in assisted living
Recommendations
Towards precision monitoring of elders for providing assistive services
PETRA '08: Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive EnvironmentsThe in-house monitoring of elders using intelligent sensors is a very desirable service that has the potential of increasing autonomy and independence while minimizing the risks of living alone. Because of this promise, the efforts of building such ...
Video-based activity level recognition for assisted living using motion features
ICDSC '15: Proceedings of the 9th International Conference on Distributed Smart CamerasActivities of daily living of the elderly is often monitored using passive sensor networks. With the reduction of camera prices, there is a growing interest of video-based approaches to provide a smart, safe and independent living environment for the ...
Concept and Design of a Video Monitoring System for Activity Recognition and Fall Detection
ICOST '09: Proceedings of the 7th International Conference on Smart Homes and Health Telematics: Ambient Assistive Health and Wellness Management in the Heart of the CityA video monitoring system is presented which aims to detect falls and other critical situations of people living single. Seniors are particularly likely to experience high-risk situations. If, for example, an elderly person falls and cannot call for help ...
Comments