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AUTOMATIC FAULT DETECTION IN DIGITAL BUILDING ENVIRONMENT

IP.com Disclosure Number: IPCOM000250402D
Publication Date: 2017-Jul-11
Document File: 7 page(s) / 867K

Publishing Venue

The IP.com Prior Art Database

Related People

Srikanth Mangala Krishnamurhty: AUTHOR [+3]

Abstract

A solution is presented by which fault detection and correction in a smart building Internet of Things (IoT) environment can be automated using semantic technologies to provide quicker service and cost savings by removing most of the manual intervention.

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Copyright 2017 Cisco Systems, Inc. 1

AUTOMATIC FAULT DETECTION IN DIGITAL BUILDING ENVIRONMENT

AUTHORS: Srikanth Mangala Krishnamurhty

Ganesh Sankarapandiyan Madhusudhan Bhadri

CISCO SYSTEMS, INC.

ABSTRACT

A solution is presented by which fault detection and correction in a smart building

Internet of Things (IoT) environment can be automated using semantic technologies to

provide quicker service and cost savings by removing most of the manual intervention.

DETAILED DESCRIPTION

State of art “Smart Building Management (SBM)” systems run an IoT middleware

to interact with galore of smart devices, a cloud based management server and different

applications running on it. IoT middleware is usually distributed across an IoT Gateway,

network and cloud management servers. The SBM system has following main architectural

components and architecture as shown in FIG. 1 below.

FIG. 1

Copyright 2017 Cisco Systems, Inc. 2

One of the important architectural component is a “resource store” based on a

resource model. The resource model provides abstractions to logically model different

devices and concepts in the building management environment. Such a resource model

provides the interfaces to interact with the various devices, usually in a domain independent

way.

Domain agnostic resource modelling limits the ability of the application to provide

useful services/applications as most of the domain specific context is not represented well

in such a resource model. A solution is presented herein that assumes that the IoT

middleware is running a domain aware, relationally rich “Semantic Resource Model”. The

semantic resource model stores all the domain based information about the building

management system: devices, functionality of the devices, relationship between devices

and concepts, nature of relationship, etc., using ontologies.

This solution involves the following architectural components for implementing

automatic fault detection in a smart building management environment, as depicted in

FIG. 2 below:

• Semantic Fault detector with knowledge base

• Statistical Analysis to recognize a pattern and notify any deviation

FIG. 2

Copyright 2017 Cisco Systems, Inc. 3

Semantic Fault Detector

The Semantic Fault Detector has following architectural components, as shown in

FIG. 3 below:

• Semantic Encoder: Semantic representation of fault handling in a building

management system embedded onto smart building ontology (OWL2) using

domain ontology.

• Semantic Rules Engine: Resource Description Framework (RDF) rules to

detect the fault using SPARQL Inferencing Notation (SPIN) rules engine.

• Semantic Fault detector Engine: Runs the rules engine on RDF formatted raw

data.

FIG. 3

Semantic Encoder: Fault representation in building management ontology

The SBM can be modelled around any available building management ontology in

the Internet domain. Such an ontology represents the knowledge about the various entities

in the SBM domain. FIG. 4 below shows a sample portion of onto...