Abstract

Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA) technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

Highlights

  • The combination of wireless sensors with the RFID technology [1,2] is emerging as an important segment of the first mile connectivity of a generation ubiquitous Internet where the informationSensors 2010, 10 will be accessed anywhere and anytime and by anyone and using anything

  • Devices are placed into the environment to sense what is happening and report to sink nodes via ubiquitous sensor networks (USNs)-bridges (2) A USN access networking layer where USN-bridges and sink nodes are used as an access network for the first-mile connectivity of a Generation Network (NGN) gateways (3) a USN middleware, residing inside or outside the gateway, used as an interface between the Next Generation Network (NGN) and the application layer and (4) different applications embodied into a USN applications layer to perform tasks related to logistics, structural health monitoring, agriculture control, disaster surveillance, military field surveillance, disaster/crisis management and many others

  • Building upon a common vision of pervasive computing, this paper presents a network management system for ubiquitous sensor networks and proposes a framework using the emerging situation awareness (ESA) technology to achieve situation recognition

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Summary

Introduction

The combination of wireless sensors with the RFID technology [1,2] is emerging as an important segment of the first mile connectivity of a generation ubiquitous Internet where the information. Derived from the Latin world ubique which denotes everywhere, ubiquitous computing— called pervasive computing and often related to as ambient intelligence—is a post-desktop model of human-computer interaction which considers a thorough integration of the information processing into our daily life by engaging heterogeneous computational devices and systems simultaneously into objects that we manipulate These objects and devices are used in our activities to deliver different services in a heterogeneous environment that involves a number of applications, protocols, operating systems, processors, and architectures. USN deployments involve thousands of nodes sensing/reading their environment and sending the sensor readings to a sink node playing the role of base station connected to a more powerful computing device called gateway where information is processed locally or disseminated to remote processing locations where appropriate decisions are taken concerning the environment to be monitored This process results in massive datasets that require appropriate processing to reveal hidden patterns used in situation recognition, prediction, reasoning and control and appropriate decision making.

The Ubiquitous Sensor Network System
The Situation Recognition System
An Intelligent USN Middleware
The Situation Recognition Framework
The ESA System Model
The Baysesian Learning Process
An Application to Outdoor Environment Monitoring
Overview of Experiments
Applying a Deterministic Model
Experiment 1
Experiment 2
Applying the Probabilistic Model
Experiment1
Experiment2
Findings
Conclusions and Future Work
Full Text
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