title: Toward sensor-based context aware systems.
abstract: 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.
authors.affiliation: School of Information Environment, Tokyo Denki University, 2-1200 Muzai Gakuendai Inzai, Chiba, 270-1382, Japan. ysakurai@sie.dendai.ac.jp
authors.forename: Yoshitaka
authors.initials: Y
authors.lastname: Sakurai
authors.forename: Kouhei
authors.initials: K
authors.lastname: Takada
authors.forename: Marco
authors.initials: M
authors.lastname: Anisetti
authors.forename: Valerio
authors.initials: V
authors.lastname: Bellandi
authors.forename: Paolo
authors.initials: P
authors.lastname: Ceravolo
authors.forename: Ernesto
authors.initials: E
authors.lastname: Damiani
authors.forename: Setsuo
authors.initials: S
authors.lastname: Tsuruta
mesh_terms: D003657:Decision Making; D017143:Fuzzy Logic; D006339:Heart Rate; D006801:Humans; D008962:Models, Theoretical; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D035501:Uncertainty