Toward Sensor-Based Context Aware Systems

Autor: Marco Anisetti, Kouhei Takada, Valerio Bellandi, Ernesto Damiani, Paolo Ceravolo, Yoshitaka Sakurai, Setsuo Tsuruta
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Computer science
Decision Making
Context (language use)
02 engineering and technology
computer.software_genre
Machine learning
lcsh:Chemical technology
Biochemistry
Fuzzy logic
Article
Analytical Chemistry
interpretation uncertainty
Fuzzy Logic
Heart Rate
0202 electrical engineering
electronic engineering
information engineering

sensor data interpretation
Humans
lcsh:TP1-1185
Electrical and Electronic Engineering
Instrumentation
Monitoring
Physiologic

Context model
Thesaurus (information retrieval)
SIMPLE (military communications protocol)
Business rule
business.industry
context-based systems
Uncertainty
Experimental data
020206 networking & telecommunications
Models
Theoretical

Atomic and Molecular Physics
and Optics

020201 artificial intelligence & image processing
Data mining
Artificial intelligence
business
computer
Zdroj: Sensors (Basel, Switzerland)
Sensors, Vol 12, Iss 1, Pp 632-649 (2012)
Sensors
Volume 12
Issue 1
Pages 632-649
ISSN: 1424-8220
Popis: This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.
Databáze: OpenAIRE