In this position paper we brie y introduce SmartEnv ontology which relies on SEmantic Sensor Network (SSN) ontology and is used to represent di erent aspects of smart and sensorized environments. We will also talk about E-carehome project aiming at providing an IoT-based health-care system for elderly people at their homes. Furthermore, we refer to the role of SmartEnv in Ecarehome and how it needs to be further extended to achieve semantic interoperability as one of the challenges in development of autonomous health care systems at home.
In the era of the Internet of Things (IoT) and advances in sensor technology,
smart environments and their applications are becoming more ubiquitous. By
smart environments we mainly refer to sensorized environments that provide
domestic monitoring and cognitive assistance services for their inhabitants. The
Semantic Sensor Network (SSN) ontology developed by the W3C Semantic
Sensor Networks Incubator Group (SSN-XG) is a generic representation model to
describe sensors, observations and their related concepts [
In this work which is a position paper, we brie y introduce the SmartEnv
ontology which relies on SSN, as a model suggested to represent di erent
aspects of smart environments. We then discuss why and how SmartEnv needs
to be extended to achieve semantic interoperability in the health domain. It is
worth mentioning that the SmartEnv ontology has been published as an ontology
description article [
After a brief introduction to SmartEnv, we also introduce E-carehome project as one of the use cases of SmartEnv in the health care domain. A current vision in the area of ICT-supported independent living of the elderly involves populating the home with electronic devices i.e. sensors and actuators, and linking them to the Internet. In E-carehome creating such an Internet-of-Things (IoT) infrastructure is done with the ambition to provide automated information gathering and processing on top of which e-services can be built. At the end, we suggest how SmartEnv can be extended to provide semantic interoperability which is required to bring health care services to patients' homes. 2
In order to support the use of arti cial intelligence techniques for automating the
provision of di erent services in smart environments, it is necessary to describe
the capabilities of the various aspects of such environments. These descriptions
that have been studied in the literature [
Objects Physical objects are also directly or indirectly the target of the observation process in order to recognize activities in a smart environment. We represent objects to answer questions about their state (being in a speci c situation), locations, or the events or activities in which they are involved. Network set-up In order to set-up a smart environment a sensor network deployment related to the observation process, is indispensable. A network representation model is used to answer any question regarding the hardware and software con guration of a network, its components and their locations.
Geometry
se-geometry:SpatialObject hasSpatialRelation geop:hasGeometry
geop:Geometry Place se-place:Section ⊑ dul:PhysicalPlace
dul:hasPart se-p⊑lacdeu:lS:PmhayrstiEcnavlPirlaocnement ⊑ sosa:Platform ssn:inDeployment
Legend
Time
Interval ⊑ owl-time:Interval ⊑ dul:TimeInterval
Object
TemporalEntity ⊑ owl-time:TemporalEntity ⊑ owl-Intitmerev:Ianlterval
TemporalDistance se-object:Object ⊑ dul:Object se-object:NodeHolder ⊑ sosa:Platform
se:object-SmartObject dul:hasLocation se-object:MobileObject se-object:Agent ⊑ dul:Agent dul:isObservableAt
Event dul:hasParticipant Manifestation dul:isEventIncludedIn dul:isObservableAt
Event ⊑ dul:Event
EventCondition dul:hasPrecondition ComplexEvent
dul:isSettingFor sosa:FeatureOfInterest ssn:hasProperty ssn:Property
Sduitl:uisaExtpiorenssedBy ssn:forProperty
Situation ⊑ dul:Situation dul:isExpressedBy ⊑ dul:InfoSrmtaatetionObject Network
Network ⊑ ssn:System ssn:hasDeployment NetworkModule
⊑ ssn:System ⊑ sDsne:pDloeypmloeymntent
sosa:hosts ssn:hasSubSystem
NodeStation ssn:hasSubSystem SenderNodeStation
Node sosa:hasFeatureOfInterest
Sensing
Observation ⊑ sosa:Observation sosa:madeObservation
Sensor ⊑ sosa:Sensor ssn:hasSubSystem sosa:observedProperty ConfigurationProcedure ⊑ sosa:Procedure ssn:implements Ontology Pattern OWL Class External Class
SubSumption
Object Property (based on existential restriction or cardinality)
Spatial aspect Any physical entity such as objects, agents, and places in a smart environment has a geometrical aspect based on which their spatial relations with the environment can be represented.
Temporal aspect Similar to spatial aspects, the temporal aspects are the main basis of an observation process. A temporal representation model is used to answer questions such as when the occurrence of an activity is realized. It also allows us to de ne activities based on the temporal relations with their preconditions.
The aforementioned aspects have been modeled in the form of 8 ontology
patterns shown in Figure 1. In the following subsections, we brie y introduce
each pattern whose representational details can be found in [
The Time pattern6 represents any temporal entities that we may use to represent
things in a smart environment. In order to represent the temporal aspect of
such environments, this pattern has been designed as an extension of the
OWLTime ontology, a W3C recommendation for describing temporal concepts [
The OWL-Time ontology provides precise representation for temporal entities in the form of either time instant or temporal duration. In the context of smart environments, we, however, require more speci c temporal representation that allows us to also represent relative temporal distance (for example, between an event and its preconditions). For this, we have extended the OWL-Time ontology and introduce it as our Time ontology pattern. In this pattern, we de ne three types of temporal entities representing time instants, time intervals and temporal distances. 2.2
Apart from the temporal aspect, in a sensorized environment, speci cally when
there are mobile agents such as robots, the representational model needs to also
cover the spatial aspects of entities including the topology of objects, rooms,
etc. For this, we have designed a pattern called Geometry7 relying on the
upper level spatial-related ontology GeoSPARQL [
A \situation" illustrates a speci c state of a \feature of interest" (e.g., the temperature of the living room is warm)8. By feature of interest we refer the concept de ned in the SSN ontology as an object which is the interest of the observation process. Although states are usually time dependent, we decided to keep the representation of a situation as abstract as possible for the sake of generality. The concept of situation can be augmented with the concept of time in other patterns such as event-related patterns which are associated with temporal properties. 2.4
A sensing process is simply de ned as the process of monitoring a speci c property of a feature of interest using a sensing device. In order to represent such concept, we have designed the pattern Sensing9 which is highly relying on the SSN ontology allowing us to model establishment of a sensing process. 2.5
The meaning of a place in the context of smart environments is twofold. First, by a place we mean the entire smart environment which holds the deployment
of a sensor network and might also be composed of several sections. The second meaning of a place refers to each section of the main place with a speci c identity that can be as such seen as a location for di erent objects. Given this preliminary de nition, the pattern Place10 de nes a place as a specialization of the class dul:PhysicalPlace. 2.6
A network in a smart environment is de ned as a system containing di erent types of devices such as nodes and node stations. By node, we mean a communication module that indicates either a sending or a receiving data module in a network. It is worth mentioning that the current design of the Network Pattern only supports the request/response communication paradigm.
Each node depending on its type can be a part of a node station representing another type of device that contributes in establishing a network. Each node station contains a node along with other things including a sensor, power supplies, batteries etc.
The whole process of a network set-up regardless of its exact technical details is represented by a non-physical concept called deployment. The pattern Network11 uni es the representation of environment automation installations that can be found in di erent systems. 2.7
The pattern Object12 allows us to de ne objects based on their important features or abilities in the context of smart environments. The class dul:PhysicalObject provides a suitable representational basis for the objects' taxonomy, which we have categorized into two types of smart objects and node holders. By smart object we refer to those objects that are the interest of an observation process (i.e, feature of interest). Due to the usual di culties of installing sensors in a smart home, it is common to use some other objects (i.e. node holders) to host sensors. This separation provided by this pattern is specifically useful for other computational modules such as a con guration planner one of whose tasks is checking the status/functionality of sensors by sending a robot to their locations.
Each smart object (or a feature of interest) has at least a property to be observed. Another categorization of smart objects that has been considered in the object pattern, is about their mobility. An objects is considered as mobile only if its location as one of its properties, can change. In order to also be able to re ect the spatial relations between objects (e.g., the \fridge is connected to the cupboard"), or between an object and a place (e.g., \the bed is located at the left side of the bedroom"), it is required to de ne objects in a smart environment also as a se-geometry:SpatialObject de ned in the pattern Geometry. 10 https://w3id.org/smartenvironment/patterns/place.owl 11 https://w3id.org/smartenvironment/patterns/network.owl 12 https://w3id.org/smartenvironment/patterns/object.owl
The pattern Event13 is an extension of the representation of events in DUL. In
this extension we have de ned two di erent types of events including a
manifestation and complex event. By manifestation, we refer to those events that can
be directly captured from sensor data and represent the occurrence of a smart
home situation through a sensing process. However, the latter event type, as its
name indicates, represents more complicated events whose occurrence depends
on several preconditions [
One of the challenges in E-care@home is to achieve semantic interoperability that allows the monitoring system to combine sensor data with background information about the patient in order to provide di erent services for the patient. These services include recognizing the current situation that the patient is in, the cause of some events, and the best action for the system to take next. The background information can be health reports created by the patient or maybe the patients informal caregivers that are stored in the personal health record (PHR) system or notes from the home care service, primary health care center or hospital that are stored in the electronic health record (EHR) systems. For this to be achieved, the heterogeneity of the services, devices and communication technologies is a major challenge for expanding generic IoT technologies to e cient ICT-supported services for elderly. For instance, the ecarehome system is expected to inform the care giver of the elderly user when it realizes that his/her heart rate has suddenly increased without any reason such as exercising. As another feature of interoperability, the system allows to de ne high heart rate based on both the health pro le of the user (gender, age, health records, etc) and also the current state of the user (i.e., if he/she is resting or actively exercising, etc.). 13 https://w3id.org/smartenvironment/patterns/event.owl 14 http://ecareathome.se
The current version of SmartEnv allows us to represent the context in terms of environmental settings. To achieve semantic interoperability, SmartEnv needs to be extended and linked to other ontologies including those that represent health pro le of elderly users (e.g., PHR/EHR15) or general medical knowledge e.g., SNOMED CT16.
For instance, the reasoner applied on SmartEnv knowledge needs to also
know about the disease, their causes and their symptoms. Such information has
been already modeled in SNOMED CT ontology, however, not necessarily with
properties compatible with what de ned in patterns of SmartEnv. The question
is if we can interlink the SNOMED CT ontology to SmartEnv by rede ning a
disease as an event (sub class of the ComplexEvent class in SmartEnv), whose
preconditions are the same as its symptoms (For further information see Event
pattern [
Furthermore, many symptoms of diseases are conditional and might change
based on the user's health pro le (i.e., PHR/EHR). Apart from the user's pro le,
the threshold values indicating normal or abnormal state of speci c
physiological parameters such as heart rate or blood pressure also depends on the type of
sensors used in the measurement process. In other words, the representation of
the sensing pattern in the SmartEnv ontology (see sensing pattern [
In summary, the next step towards achieving semantic interoperability in health care includes integration of patterns in SmartEnv with other ontologies in the health-care domain.
Acknowledgments: The work is supported by the project E-care@home funded by the Swedish Knowledge Foundation 2015-2019. 15 http://sele.inf.um.es/CEM2Archetypes/ 16 http://purl.bioontology.org/ontology/SNOMEDCT